A relationship between eye movement patterns and performance in a precognitive tracking task

NASA Technical Reports Server (NTRS)

Repperger, D. W.; Hartzell, E. J.

1977-01-01

Eye movements made by various subjects in the performance of a precognitive tracking task are studied. The tracking task persented by an antiaircraft artillery (AAA) simulator has an input forcing function represented by a deterministic aircraft fly-by. The performance of subjects is ranked by two metrics. Good, mediocre, and poor trackers are selected for analysis based on performance during the difficult segment of the tracking task and over replications. Using phase planes to characterize both the eye movement patterns and the displayed error signal, a simple metric is developed to study these patterns. Two characterizations of eye movement strategies are defined and quantified. Using these two types of eye strategies, two conclusions are obtained about good, mediocre, and poor trackers. First, the eye tracker who used a fixed strategy will consistently perform better. Secondly, the best fixed strategy is defined as a Crosshair Fixator.

Performance metrics for the evaluation of hyperspectral chemical identification systems

NASA Astrophysics Data System (ADS)

Truslow, Eric; Golowich, Steven; Manolakis, Dimitris; Ingle, Vinay

2016-02-01

Remote sensing of chemical vapor plumes is a difficult but important task for many military and civilian applications. Hyperspectral sensors operating in the long-wave infrared regime have well-demonstrated detection capabilities. However, the identification of a plume's chemical constituents, based on a chemical library, is a multiple hypothesis testing problem which standard detection metrics do not fully describe. We propose using an additional performance metric for identification based on the so-called Dice index. Our approach partitions and weights a confusion matrix to develop both the standard detection metrics and identification metric. Using the proposed metrics, we demonstrate that the intuitive system design of a detector bank followed by an identifier is indeed justified when incorporating performance information beyond the standard detection metrics.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loughran, B; Singh, V; Jain, A

Purpose: Although generalized linear system analytic metrics such as GMTF and GDQE can evaluate performance of the whole imaging system including detector, scatter and focal-spot, a simplified task-specific measured metric may help to better compare detector systems. Methods: Low quantum-noise images of a neuro-vascular stent with a modified ANSI head phantom were obtained from the average of many exposures taken with the high-resolution Micro-Angiographic Fluoroscope (MAF) and with a Flat Panel Detector (FPD). The square of the Fourier Transform of each averaged image, equivalent to the measured product of the system GMTF and the object function in spatial-frequency space, wasmore » then divided by the normalized noise power spectra (NNPS) for each respective system to obtain a task-specific generalized signal-to-noise ratio. A generalized measured relative object detectability (GM-ROD) was obtained by taking the ratio of the integral of the resulting expressions for each detector system to give an overall metric that enables a realistic systems comparison for the given detection task. Results: The GM-ROD provides comparison of relative performance of detector systems from actual measurements of the object function as imaged by those detector systems. This metric includes noise correlations and spatial frequencies relevant to the specific object. Additionally, the integration bounds for the GM-ROD can be selected to emphasis the higher frequency band of each detector if high-resolution image details are to be evaluated. Examples of this new metric are discussed with a comparison of the MAF to the FPD for neuro-vascular interventional imaging. Conclusion: The GM-ROD is a new direct-measured task-specific metric that can provide clinically relevant comparison of the relative performance of imaging systems. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

Research and development on performance models of thermal imaging systems

NASA Astrophysics Data System (ADS)

Wang, Ji-hui; Jin, Wei-qi; Wang, Xia; Cheng, Yi-nan

2009-07-01

Traditional ACQUIRE models perform the discrimination tasks of detection (target orientation, recognition and identification) for military target based upon minimum resolvable temperature difference (MRTD) and Johnson criteria for thermal imaging systems (TIS). Johnson criteria is generally pessimistic for performance predict of sampled imager with the development of focal plane array (FPA) detectors and digital image process technology. Triangle orientation discrimination threshold (TOD) model, minimum temperature difference perceived (MTDP)/ thermal range model (TRM3) Model and target task performance (TTP) metric have been developed to predict the performance of sampled imager, especially TTP metric can provides better accuracy than the Johnson criteria. In this paper, the performance models above are described; channel width metrics have been presented to describe the synthesis performance including modulate translate function (MTF) channel width for high signal noise to ration (SNR) optoelectronic imaging systems and MRTD channel width for low SNR TIS; the under resolvable questions for performance assessment of TIS are indicated; last, the development direction of performance models for TIS are discussed.

Assessment of various supervised learning algorithms using different performance metrics

NASA Astrophysics Data System (ADS)

Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Development and preliminary reliability of a multitasking assessment for executive functioning after concussion.

PubMed

Smith, Laurel B; Radomski, Mary Vining; Davidson, Leslie Freeman; Finkelstein, Marsha; Weightman, Margaret M; McCulloch, Karen L; Scherer, Matthew R

2014-01-01

OBJECTIVES. Executive functioning deficits may result from concussion. The Charge of Quarters (CQ) Duty Task is a multitask assessment designed to assess executive functioning in servicemembers after concussion. In this article, we discuss the rationale and process used in the development of the CQ Duty Task and present pilot data from the preliminary evaluation of interrater reliability (IRR). METHOD. Three evaluators observed as 12 healthy participants performed the CQ Duty Task and measured performance using various metrics. Intraclass correlation coefficient (ICC) quantified IRR. RESULTS. The ICC for task completion was .94. ICCs for other assessment metrics were variable. CONCLUSION. Preliminary IRR data for the CQ Duty Task are encouraging, but further investigation is needed to improve IRR in some domains. Lessons learned in the development of the CQ Duty Task could benefit future test development efforts with populations other than the military. Copyright © 2014 by the American Occupational Therapy Association, Inc.

Development and Preliminary Reliability of a Multitasking Assessment for Executive Functioning After Concussion

PubMed Central

Radomski, Mary Vining; Davidson, Leslie Freeman; Finkelstein, Marsha; Weightman, Margaret M.; McCulloch, Karen L.; Scherer, Matthew R.

2014-01-01

OBJECTIVES. Executive functioning deficits may result from concussion. The Charge of Quarters (CQ) Duty Task is a multitask assessment designed to assess executive functioning in servicemembers after concussion. In this article, we discuss the rationale and process used in the development of the CQ Duty Task and present pilot data from the preliminary evaluation of interrater reliability (IRR). METHOD. Three evaluators observed as 12 healthy participants performed the CQ Duty Task and measured performance using various metrics. Intraclass correlation coefficient (ICC) quantified IRR. RESULTS. The ICC for task completion was .94. ICCs for other assessment metrics were variable. CONCLUSION. Preliminary IRR data for the CQ Duty Task are encouraging, but further investigation is needed to improve IRR in some domains. Lessons learned in the development of the CQ Duty Task could benefit future test development efforts with populations other than the military. PMID:25005507

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

Real-Time Performance Feedback for the Manual Control of Spacecraft

NASA Astrophysics Data System (ADS)

Karasinski, John Austin

Real-time performance metrics were developed to quantify workload, situational awareness, and manual task performance for use as visual feedback to pilots of aerospace vehicles. Results from prior lunar lander experiments with variable levels of automation were replicated and extended to provide insights for the development of real-time metrics. Increased levels of automation resulted in increased flight performance, lower workload, and increased situational awareness. Automated Speech Recognition (ASR) was employed to detect verbal callouts as a limited measure of subjects' situational awareness. A one-dimensional manual tracking task and simple instructor-model visual feedback scheme was developed. This feedback was indicated to the operator by changing the color of a guidance element on the primary flight display, similar to how a flight instructor points out elements of a display to a student pilot. Experiments showed that for this low-complexity task, visual feedback did not change subject performance, but did increase the subjects' measured workload. Insights gained from these experiments were applied to a Simplified Aid for EVA Rescue (SAFER) inspection task. The effects of variations of an instructor-model performance-feedback strategy on human performance in a novel SAFER inspection task were investigated. Real-time feedback was found to have a statistically significant effect of improving subject performance and decreasing workload in this complicated four degree of freedom manual control task with two secondary tasks.

Testing the Construct Validity of a Virtual Reality Hip Arthroscopy Simulator.

PubMed

Khanduja, Vikas; Lawrence, John E; Audenaert, Emmanuel

2017-03-01

To test the construct validity of the hip diagnostics module of a virtual reality hip arthroscopy simulator. Nineteen orthopaedic surgeons performed a simulated arthroscopic examination of a healthy hip joint using a 70° arthroscope in the supine position. Surgeons were categorized as either expert (those who had performed 250 hip arthroscopies or more) or novice (those who had performed fewer than this). Twenty-one specific targets were visualized within the central and peripheral compartments; 9 via the anterior portal, 9 via the anterolateral portal, and 3 via the posterolateral portal. This was immediately followed by a task testing basic probe examination of the joint in which a series of 8 targets were probed via the anterolateral portal. During the tasks, the surgeon's performance was evaluated by the simulator using a set of predefined metrics including task duration, number of soft tissue and bone collisions, and distance travelled by instruments. No repeat attempts at the tasks were permitted. Construct validity was then evaluated by comparing novice and expert group performance metrics over the 2 tasks using the Mann-Whitney test, with a P value of less than .05 considered significant. On the visualization task, the expert group outperformed the novice group on time taken (P = .0003), number of collisions with soft tissue (P = .001), number of collisions with bone (P = .002), and distance travelled by the arthroscope (P = .02). On the probe examination, the 2 groups differed only in the time taken to complete the task (P = .025) with no significant difference in other metrics. Increased experience in hip arthroscopy was reflected by significantly better performance on the virtual reality simulator across 2 tasks, supporting its construct validity. This study validates a virtual reality hip arthroscopy simulator and supports its potential for developing basic arthroscopic skills. Level III. Copyright © 2016 Arthroscopy Association of North America. All rights reserved.

Meaningful Assessment of Robotic Surgical Style using the Wisdom of Crowds.

PubMed

Ershad, M; Rege, R; Fey, A Majewicz

2018-07-01

Quantitative assessment of surgical skills is an important aspect of surgical training; however, the proposed metrics are sometimes difficult to interpret and may not capture the stylistic characteristics that define expertise. This study proposes a methodology for evaluating the surgical skill, based on metrics associated with stylistic adjectives, and evaluates the ability of this method to differentiate expertise levels. We recruited subjects from different expertise levels to perform training tasks on a surgical simulator. A lexicon of contrasting adjective pairs, based on important skills for robotic surgery, inspired by the global evaluative assessment of robotic skills tool, was developed. To validate the use of stylistic adjectives for surgical skill assessment, posture videos of the subjects performing the task, as well as videos of the task were rated by crowd-workers. Metrics associated with each adjective were found using kinematic and physiological measurements through correlation with the crowd-sourced adjective assignment ratings. To evaluate the chosen metrics' ability in distinguishing expertise levels, two classifiers were trained and tested using these metrics. Crowd-assignment ratings for all adjectives were significantly correlated with expertise levels. The results indicate that naive Bayes classifier performs the best, with an accuracy of [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] when classifying into four, three, and two levels of expertise, respectively. The proposed method is effective at mapping understandable adjectives of expertise to the stylistic movements and physiological response of trainees.

Further Development of the Assessment of Military Multitasking Performance: Iterative Reliability Testing

PubMed Central

McCulloch, Karen L.; Radomski, Mary V.; Finkelstein, Marsha; Cecchini, Amy S.; Davidson, Leslie F.; Heaton, Kristin J.; Smith, Laurel B.; Scherer, Matthew R.

2017-01-01

The Assessment of Military Multitasking Performance (AMMP) is a battery of functional dual-tasks and multitasks based on military activities that target known sensorimotor, cognitive, and exertional vulnerabilities after concussion/mild traumatic brain injury (mTBI). The AMMP was developed to help address known limitations in post concussive return to duty assessment and decision making. Once validated, the AMMP is intended for use in combination with other metrics to inform duty-readiness decisions in Active Duty Service Members following concussion. This study used an iterative process of repeated interrater reliability testing and feasibility feedback to drive modifications to the 9 tasks of the original AMMP which resulted in a final version of 6 tasks with metrics that demonstrated clinically acceptable ICCs of > 0.92 (range of 0.92–1.0) for the 3 dual tasks and > 0.87 (range 0.87–1.0) for the metrics of the 3 multitasks. Three metrics involved in recording subject errors across 2 tasks did not achieve ICCs above 0.85 set apriori for multitasks (0.64) and above 0.90 set for dual-tasks (0.77 and 0.86) and were not used for further analysis. This iterative process involved 3 phases of testing with between 13 and 26 subjects, ages 18–42 years, tested in each phase from a combined cohort of healthy controls and Service Members with mTBI. Study findings support continued validation of this assessment tool to provide rehabilitation clinicians further return to duty assessment methods robust to ceiling effects with strong face validity to injured Warriors and their leaders. PMID:28056045

Establishing a curriculum for the acquisition of laparoscopic psychomotor skills in the virtual reality environment.

PubMed

Sinitsky, Daniel M; Fernando, Bimbi; Berlingieri, Pasquale

2012-09-01

The unique psychomotor skills required in laparoscopy result in reduced patient safety during the early part of the learning curve. Evidence suggests that these may be safely acquired in the virtual reality (VR) environment. Several VR simulators are available, each preloaded with several psychomotor skills tasks that provide users with computer-generated performance metrics. This review aimed to evaluate the usefulness of specific psychomotor skills tasks and metrics, and how trainers might build an effective training curriculum. We performed a comprehensive literature search. The vast majority of VR psychomotor skills tasks show construct validity for one or more metrics. These are commonly for time and motion parameters. Regarding training schedules, distributed practice is preferred over massed practice. However, a degree of supervision may be needed to counter the limitations of VR training. In the future, standardized proficiency scores should facilitate local institutions in establishing VR laparoscopic psychomotor skills curricula. Copyright © 2012 Elsevier Inc. All rights reserved.

What Do Eye Gaze Metrics Tell Us about Motor Imagery?

PubMed

Poiroux, Elodie; Cavaro-Ménard, Christine; Leruez, Stéphanie; Lemée, Jean Michel; Richard, Isabelle; Dinomais, Mickael

2015-01-01

Many of the brain structures involved in performing real movements also have increased activity during imagined movements or during motor observation, and this could be the neural substrate underlying the effects of motor imagery in motor learning or motor rehabilitation. In the absence of any objective physiological method of measurement, it is currently impossible to be sure that the patient is indeed performing the task as instructed. Eye gaze recording during a motor imagery task could be a possible way to "spy" on the activity an individual is really engaged in. The aim of the present study was to compare the pattern of eye movement metrics during motor observation, visual and kinesthetic motor imagery (VI, KI), target fixation, and mental calculation. Twenty-two healthy subjects (16 females and 6 males), were required to perform tests in five conditions using imagery in the Box and Block Test tasks following the procedure described by Liepert et al. Eye movements were analysed by a non-invasive oculometric measure (SMI RED250 system). Two parameters describing gaze pattern were calculated: the index of ocular mobility (saccade duration over saccade + fixation duration) and the number of midline crossings (i.e. the number of times the subjects gaze crossed the midline of the screen when performing the different tasks). Both parameters were significantly different between visual imagery and kinesthesic imagery, visual imagery and mental calculation, and visual imagery and target fixation. For the first time we were able to show that eye movement patterns are different during VI and KI tasks. Our results suggest gaze metric parameters could be used as an objective unobtrusive approach to assess engagement in a motor imagery task. Further studies should define how oculomotor parameters could be used as an indicator of the rehabilitation task a patient is engaged in.

Product evaluation based in the association between intuition and tasks.

PubMed

Almeida e Silva, Caio Márcio; Okimoto, Maria Lúcia L R; Albertazzi, Deise; Calixto, Cyntia; Costa, Humberto

2012-01-01

This paper explores the importance of researching the intuitiveness in the product use. It approaches the intuitiveness influence for users that already had a visual experience of the product. Finally, it is suggested the use of a table that relates the tasks performed while using a product, the features for an intuitive use and the performance metric "task success".

Instrument Motion Metrics for Laparoscopic Skills Assessment in Virtual Reality and Augmented Reality.

PubMed

Fransson, Boel A; Chen, Chi-Ya; Noyes, Julie A; Ragle, Claude A

2016-11-01

To determine the construct and concurrent validity of instrument motion metrics for laparoscopic skills assessment in virtual reality and augmented reality simulators. Evaluation study. Veterinarian students (novice, n = 14) and veterinarians (experienced, n = 11) with no or variable laparoscopic experience. Participants' minimally invasive surgery (MIS) experience was determined by hospital records of MIS procedures performed in the Teaching Hospital. Basic laparoscopic skills were assessed by 5 tasks using a physical box trainer. Each participant completed 2 tasks for assessments in each type of simulator (virtual reality: bowel handling and cutting; augmented reality: object positioning and a pericardial window model). Motion metrics such as instrument path length, angle or drift, and economy of motion of each simulator were recorded. None of the motion metrics in a virtual reality simulator showed correlation with experience, or to the basic laparoscopic skills score. All metrics in augmented reality were significantly correlated with experience (time, instrument path, and economy of movement), except for the hand dominance metric. The basic laparoscopic skills score was correlated to all performance metrics in augmented reality. The augmented reality motion metrics differed between American College of Veterinary Surgeons diplomates and residents, whereas basic laparoscopic skills score and virtual reality metrics did not. Our results provide construct validity and concurrent validity for motion analysis metrics for an augmented reality system, whereas a virtual reality system was validated only for the time score. © Copyright 2016 by The American College of Veterinary Surgeons.

Hypoxic Hypoxia at Moderate Altitudes: State of the Science

DTIC Science & Technology

2011-05-01

neuropsychological metrics (surrogate investigational end points) with actual flight task metrics (desired end points of interest) under moderate hypoxic...conditions, (2) determine efficacy of potential neuropsychological performance-enhancing agents (e.g. tyrosine supplementation) for both acute and chronic...to air hunger ; may impact training fidelity Banderet et al. (1985) 4200 and 4700 m H 27 Tyrosine enhanced performance and reduced subjective

Metric Learning for Hyperspectral Image Segmentation

NASA Technical Reports Server (NTRS)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Analysis of Subjects' Vulnerability in a Touch Screen Game Using Behavioral Metrics.

PubMed

Parsinejad, Payam; Sipahi, Rifat

2017-12-01

In this article, we report results on an experimental study conducted with volunteer subjects playing a touch-screen game with two unique difficulty levels. Subjects have knowledge about the rules of both game levels, but only sufficient playing experience with the easy level of the game, making them vulnerable with the difficult level. Several behavioral metrics associated with subjects' playing the game are studied in order to assess subjects' mental-workload changes induced by their vulnerability. Specifically, these metrics are calculated based on subjects' finger kinematics and decision making times, which are then compared with baseline metrics, namely, performance metrics pertaining to how well the game is played and a physiological metric called pnn50 extracted from heart rate measurements. In balanced experiments and supported by comparisons with baseline metrics, it is found that some of the studied behavioral metrics have the potential to be used to infer subjects' mental workload changes through different levels of the game. These metrics, which are decoupled from task specifics, relate to subjects' ability to develop strategies to play the game, and hence have the advantage of offering insight into subjects' task-load and vulnerability assessment across various experimental settings.

The model for Fundamentals of Endovascular Surgery (FEVS) successfully defines the competent endovascular surgeon.

PubMed

Duran, Cassidy; Estrada, Sean; O'Malley, Marcia; Sheahan, Malachi G; Shames, Murray L; Lee, Jason T; Bismuth, Jean

2015-12-01

Fundamental skills testing is now required for certification in general surgery. No model for assessing fundamental endovascular skills exists. Our objective was to develop a model that tests the fundamental endovascular skills and differentiates competent from noncompetent performance. The Fundamentals of Endovascular Surgery model was developed in silicon and virtual-reality versions. Twenty individuals (with a range of experience) performed four tasks on each model in three separate sessions. Tasks on the silicon model were performed under fluoroscopic guidance, and electromagnetic tracking captured motion metrics for catheter tip position. Image processing captured tool tip position and motion on the virtual model. Performance was evaluated using a global rating scale, blinded video assessment of error metrics, and catheter tip movement and position. Motion analysis was based on derivations of speed and position that define proficiency of movement (spectral arc length, duration of submovement, and number of submovements). Performance was significantly different between competent and noncompetent interventionalists for the three performance measures of motion metrics, error metrics, and global rating scale. The mean error metric score was 6.83 for noncompetent individuals and 2.51 for the competent group (P < .0001). Median global rating scores were 2.25 for the noncompetent group and 4.75 for the competent users (P < .0001). The Fundamentals of Endovascular Surgery model successfully differentiates competent and noncompetent performance of fundamental endovascular skills based on a series of objective performance measures. This model could serve as a platform for skills testing for all trainees. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Predicting dual-task performance with the Multiple Resources Questionnaire (MRQ).

PubMed

Boles, David B; Bursk, Jonathan H; Phillips, Jeffrey B; Perdelwitz, Jason R

2007-02-01

The objective was to assess the validity of the Multiple Resources Questionnaire (MRQ) in predicting dual-task interference. Subjective workload measures such as the Subjective Workload Assessment Technique (SWAT) and NASA Task Load Index are sensitive to single-task parameters and dual-task loads but have not attempted to measure workload in particular mental processes. An alternative is the MRQ. In Experiment 1, participants completed simple laboratory tasks and the MRQ after each. Interference between tasks was then correlated to three different task similarity metrics: profile similarity, based on r(2) between ratings; overlap similarity, based on summed minima; and overall demand, based on summed ratings. Experiment 2 used similar methods but more complex computer-based games. In Experiment 1 the MRQ moderately predicted interference (r = +.37), with no significant difference between metrics. In Experiment 2 the metric effect was significant, with overlap similarity excelling in predicting interference (r = +.83). Mean ratings showed high diagnosticity in identifying specific mental processing bottlenecks. The MRQ shows considerable promise as a cognitive-process-sensitive workload measure. Potential applications of the MRQ include the identification of dual-processing bottlenecks as well as process overloads in single tasks, preparatory to redesign in areas such as air traffic management, advanced flight displays, and medical imaging.

Human Performance Optimization Metrics: Consensus Findings, Gaps, and Recommendations for Future Research.

PubMed

Nindl, Bradley C; Jaffin, Dianna P; Dretsch, Michael N; Cheuvront, Samuel N; Wesensten, Nancy J; Kent, Michael L; Grunberg, Neil E; Pierce, Joseph R; Barry, Erin S; Scott, Jonathan M; Young, Andrew J; OʼConnor, Francis G; Deuster, Patricia A

2015-11-01

Human performance optimization (HPO) is defined as "the process of applying knowledge, skills and emerging technologies to improve and preserve the capabilities of military members, and organizations to execute essential tasks." The lack of consensus for operationally relevant and standardized metrics that meet joint military requirements has been identified as the single most important gap for research and application of HPO. In 2013, the Consortium for Health and Military Performance hosted a meeting to develop a toolkit of standardized HPO metrics for use in military and civilian research, and potentially for field applications by commanders, units, and organizations. Performance was considered from a holistic perspective as being influenced by various behaviors and barriers. To accomplish the goal of developing a standardized toolkit, key metrics were identified and evaluated across a spectrum of domains that contribute to HPO: physical performance, nutritional status, psychological status, cognitive performance, environmental challenges, sleep, and pain. These domains were chosen based on relevant data with regard to performance enhancers and degraders. The specific objectives at this meeting were to (a) identify and evaluate current metrics for assessing human performance within selected domains; (b) prioritize metrics within each domain to establish a human performance assessment toolkit; and (c) identify scientific gaps and the needed research to more effectively assess human performance across domains. This article provides of a summary of 150 total HPO metrics across multiple domains that can be used as a starting point-the beginning of an HPO toolkit: physical fitness (29 metrics), nutrition (24 metrics), psychological status (36 metrics), cognitive performance (35 metrics), environment (12 metrics), sleep (9 metrics), and pain (5 metrics). These metrics can be particularly valuable as the military emphasizes a renewed interest in Human Dimension efforts, and leverages science, resources, programs, and policies to optimize the performance capacities of all Service members.

Automatic intersection map generation task 10 report.

DOT National Transportation Integrated Search

2016-02-29

This report describes the work conducted in Task 10 of the V2I Safety Applications Development Project. The work was performed by the University of Michigan Transportation Research Institute (UMTRI) under contract to the Crash Avoidance Metrics Partn...

EVA Health and Human Performance Benchmarking Study

NASA Technical Reports Server (NTRS)

Abercromby, A. F.; Norcross, J.; Jarvis, S. L.

2016-01-01

Multiple HRP Risks and Gaps require detailed characterization of human health and performance during exploration extravehicular activity (EVA) tasks; however, a rigorous and comprehensive methodology for characterizing and comparing the health and human performance implications of current and future EVA spacesuit designs does not exist. This study will identify and implement functional tasks and metrics, both objective and subjective, that are relevant to health and human performance, such as metabolic expenditure, suit fit, discomfort, suited postural stability, cognitive performance, and potentially biochemical responses for humans working inside different EVA suits doing functional tasks under the appropriate simulated reduced gravity environments. This study will provide health and human performance benchmark data for humans working in current EVA suits (EMU, Mark III, and Z2) as well as shirtsleeves using a standard set of tasks and metrics with quantified reliability. Results and methodologies developed during this test will provide benchmark data against which future EVA suits, and different suit configurations (eg, varied pressure, mass, CG) may be reliably compared in subsequent tests. Results will also inform fitness for duty standards as well as design requirements and operations concepts for future EVA suits and other exploration systems.

Asymptotically Optimal Motion Planning for Learned Tasks Using Time-Dependent Cost Maps

PubMed Central

Bowen, Chris; Ye, Gu; Alterovitz, Ron

2015-01-01

In unstructured environments in people’s homes and workspaces, robots executing a task may need to avoid obstacles while satisfying task motion constraints, e.g., keeping a plate of food level to avoid spills or properly orienting a finger to push a button. We introduce a sampling-based method for computing motion plans that are collision-free and minimize a cost metric that encodes task motion constraints. Our time-dependent cost metric, learned from a set of demonstrations, encodes features of a task’s motion that are consistent across the demonstrations and, hence, are likely required to successfully execute the task. Our sampling-based motion planner uses the learned cost metric to compute plans that simultaneously avoid obstacles and satisfy task constraints. The motion planner is asymptotically optimal and minimizes the Mahalanobis distance between the planned trajectory and the distribution of demonstrations in a feature space parameterized by the locations of task-relevant objects. The motion planner also leverages the distribution of the demonstrations to significantly reduce plan computation time. We demonstrate the method’s effectiveness and speed using a small humanoid robot performing tasks requiring both obstacle avoidance and satisfaction of learned task constraints. Note to Practitioners Motivated by the desire to enable robots to autonomously operate in cluttered home and workplace environments, this paper presents an approach for intuitively training a robot in a manner that enables it to repeat the task in novel scenarios and in the presence of unforeseen obstacles in the environment. Based on user-provided demonstrations of the task, our method learns features of the task that are consistent across the demonstrations and that we expect should be repeated by the robot when performing the task. We next present an efficient algorithm for planning robot motions to perform the task based on the learned features while avoiding obstacles. We demonstrate the effectiveness of our motion planner for scenarios requiring transferring a powder and pushing a button in environments with obstacles, and we plan to extend our results to more complex tasks in the future. PMID:26279642

Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics.

PubMed

Georgsson, Mattias; Staggers, Nancy

2016-01-01

Mobile health (mHealth) systems are becoming more common for chronic disease management, but usability studies are still needed on patients' perspectives and mHealth interaction performance. This deficiency is addressed by our quantitative usability study of a mHealth diabetes system evaluating patients' task performance, satisfaction, and the relationship of these measures to user characteristics. We used metrics in the International Organization for Standardization (ISO) 9241-11 standard. After standardized training, 10 patients performed representative tasks and were assessed on individual task success, errors, efficiency (time on task), satisfaction (System Usability Scale [SUS]) and user characteristics. Tasks of exporting and correcting values proved the most difficult, had the most errors, the lowest task success rates, and consumed the longest times on task. The average SUS satisfaction score was 80.5, indicating good but not excellent system usability. Data trends showed males were more successful in task completion, and younger participants had higher performance scores. Educational level did not influence performance, but a more recent diabetes diagnosis did. Patients with more experience in information technology (IT) also had higher performance rates. Difficult task performance indicated areas for redesign. Our methods can assist others in identifying areas in need of improvement. Data about user background and IT skills also showed how user characteristics influence performance and can provide future considerations for targeted mHealth designs. Using the ISO 9241-11 usability standard, the SUS instrument for satisfaction and measuring user characteristics provided objective measures of patients' experienced usability. These could serve as an exemplar for standardized, quantitative methods for usability studies on mHealth systems. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Quantifying usability: an evaluation of a diabetes mHealth system on effectiveness, efficiency, and satisfaction metrics with associated user characteristics

PubMed Central

Staggers, Nancy

2016-01-01

Objective Mobile health (mHealth) systems are becoming more common for chronic disease management, but usability studies are still needed on patients’ perspectives and mHealth interaction performance. This deficiency is addressed by our quantitative usability study of a mHealth diabetes system evaluating patients’ task performance, satisfaction, and the relationship of these measures to user characteristics. Materials and Methods We used metrics in the International Organization for Standardization (ISO) 9241-11 standard. After standardized training, 10 patients performed representative tasks and were assessed on individual task success, errors, efficiency (time on task), satisfaction (System Usability Scale [SUS]) and user characteristics. Results Tasks of exporting and correcting values proved the most difficult, had the most errors, the lowest task success rates, and consumed the longest times on task. The average SUS satisfaction score was 80.5, indicating good but not excellent system usability. Data trends showed males were more successful in task completion, and younger participants had higher performance scores. Educational level did not influence performance, but a more recent diabetes diagnosis did. Patients with more experience in information technology (IT) also had higher performance rates. Discussion Difficult task performance indicated areas for redesign. Our methods can assist others in identifying areas in need of improvement. Data about user background and IT skills also showed how user characteristics influence performance and can provide future considerations for targeted mHealth designs. Conclusion Using the ISO 9241-11 usability standard, the SUS instrument for satisfaction and measuring user characteristics provided objective measures of patients’ experienced usability. These could serve as an exemplar for standardized, quantitative methods for usability studies on mHealth systems. PMID:26377990

The influence of time management skill on the curvilinear relationship between organizational citizenship behavior and task performance.

PubMed

Rapp, Adam A; Bachrach, Daniel G; Rapp, Tammy L

2013-07-01

In this research we integrate resource allocation and social exchange perspectives to build and test theory focusing on the moderating role of time management skill in the nonmonotonic relationship between organizational citizenship behavior (OCB) and task performance. Results from matching survey data collected from 212 employees and 41 supervisors and from task performance metrics collected several months later indicate that the curvilinear association between OCB and task performance is significantly moderated by employees' time management skill. Implications for theory and practice are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Target detection cycle criteria when using the targeting task performance metric

NASA Astrophysics Data System (ADS)

Hixson, Jonathan G.; Jacobs, Eddie L.; Vollmerhausen, Richard H.

2004-12-01

The US Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate of the US Army (NVESD) has developed a new target acquisition metric to better predict the performance of modern electro-optical imagers. The TTP metric replaces the Johnson criteria. One problem with transitioning to the new model is that the difficulty of searching in a terrain has traditionally been quantified by an "N50." The N50 is the number of Johnson criteria cycles needed for the observer to detect the target half the time, assuming that the observer is not time limited. In order to make use of this empirical data base, a conversion must be found relating Johnson cycles for detection to TTP cycles for detection. This paper describes how that relationship is established. We have found that the relationship between Johnson and TTP is 1:2.7 for the recognition and identification tasks.

Task-oriented lossy compression of magnetic resonance images

NASA Astrophysics Data System (ADS)

Anderson, Mark C.; Atkins, M. Stella; Vaisey, Jacques

1996-04-01

A new task-oriented image quality metric is used to quantify the effects of distortion introduced into magnetic resonance images by lossy compression. This metric measures the similarity between a radiologist's manual segmentation of pathological features in the original images and the automated segmentations performed on the original and compressed images. The images are compressed using a general wavelet-based lossy image compression technique, embedded zerotree coding, and segmented using a three-dimensional stochastic model-based tissue segmentation algorithm. The performance of the compression system is then enhanced by compressing different regions of the image volume at different bit rates, guided by prior knowledge about the location of important anatomical regions in the image. Application of the new system to magnetic resonance images is shown to produce compression results superior to the conventional methods, both subjectively and with respect to the segmentation similarity metric.

Irregular large-scale computed tomography on multiple graphics processors improves energy-efficiency metrics for industrial applications

NASA Astrophysics Data System (ADS)

Jimenez, Edward S.; Goodman, Eric L.; Park, Ryeojin; Orr, Laurel J.; Thompson, Kyle R.

2014-09-01

This paper will investigate energy-efficiency for various real-world industrial computed-tomography reconstruction algorithms, both CPU- and GPU-based implementations. This work shows that the energy required for a given reconstruction is based on performance and problem size. There are many ways to describe performance and energy efficiency, thus this work will investigate multiple metrics including performance-per-watt, energy-delay product, and energy consumption. This work found that irregular GPU-based approaches1 realized tremendous savings in energy consumption when compared to CPU implementations while also significantly improving the performance-per- watt and energy-delay product metrics. Additional energy savings and other metric improvement was realized on the GPU-based reconstructions by improving storage I/O by implementing a parallel MIMD-like modularization of the compute and I/O tasks.

Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

NASA Astrophysics Data System (ADS)

Camp, H. A.; Moyer, Steven; Moore, Richard K.

2010-04-01

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

NERC Policy 10: Measurement of two generation and load balancing IOS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spicer, P.J.; Galow, G.G.

1999-11-01

Policy 10 will describe specific standards and metrics for most of the reliability functions described in the Interconnected Operations Services Working Group (IOS WG) report. The purpose of this paper is to discuss, in detail, the proposed metrics for two generation and load balancing IOSs: Regulation; Load Following. For purposes of this paper, metrics include both measurement and performance evaluation. The measurement methods discussed are included in the current draft of the proposed Policy 10. The performance evaluation method discussed is offered by the authors for consideration by the IOS ITF (Implementation Task Force) for inclusion into Policy 10.

Surgical task analysis of simulated laparoscopic cholecystectomy with a navigation system.

PubMed

Sugino, T; Kawahira, H; Nakamura, R

2014-09-01

   Advanced surgical procedures, which have become complex and difficult, increase the burden of surgeons. Quantitative analysis of surgical procedures can improve training, reduce variability, and enable optimization of surgical procedures. To this end, a surgical task analysis system was developed that uses only surgical navigation information.    Division of the surgical procedure, task progress analysis, and task efficiency analysis were done. First, the procedure was divided into five stages. Second, the operating time and progress rate were recorded to document task progress during specific stages, including the dissecting task. Third, the speed of the surgical instrument motion (mean velocity and acceleration), as well as the size and overlap ratio of the approximate ellipse of the location log data distribution, was computed to estimate the task efficiency during each stage. These analysis methods were evaluated based on experimental validation with two groups of surgeons, i.e., skilled and "other" surgeons. The performance metrics and analytical parameters included incidents during the operation, the surgical environment, and the surgeon's skills or habits.    Comparison of groups revealed that skilled surgeons tended to perform the procedure in less time and involved smaller regions; they also manipulated the surgical instruments more gently.    Surgical task analysis developed for quantitative assessment of surgical procedures and surgical performance may provide practical methods and metrics for objective evaluation of surgical expertise.

Robotics-based synthesis of human motion.

PubMed

Khatib, O; Demircan, E; De Sapio, V; Sentis, L; Besier, T; Delp, S

2009-01-01

The synthesis of human motion is a complex procedure that involves accurate reconstruction of movement sequences, modeling of musculoskeletal kinematics, dynamics and actuation, and characterization of reliable performance criteria. Many of these processes have much in common with the problems found in robotics research. Task-based methods used in robotics may be leveraged to provide novel musculoskeletal modeling methods and physiologically accurate performance predictions. In this paper, we present (i) a new method for the real-time reconstruction of human motion trajectories using direct marker tracking, (ii) a task-driven muscular effort minimization criterion and (iii) new human performance metrics for dynamic characterization of athletic skills. Dynamic motion reconstruction is achieved through the control of a simulated human model to follow the captured marker trajectories in real-time. The operational space control and real-time simulation provide human dynamics at any configuration of the performance. A new criteria of muscular effort minimization has been introduced to analyze human static postures. Extensive motion capture experiments were conducted to validate the new minimization criterion. Finally, new human performance metrics were introduced to study in details an athletic skill. These metrics include the effort expenditure and the feasible set of operational space accelerations during the performance of the skill. The dynamic characterization takes into account skeletal kinematics as well as muscle routing kinematics and force generating capacities. The developments draw upon an advanced musculoskeletal modeling platform and a task-oriented framework for the effective integration of biomechanics and robotics methods.

The Effects of Automation on Battle Manager Workload and Performance

DTIC Science & Technology

2008-01-01

such as the National Aeronautics and Space Administration ( NASA ) Task Load Index ( TLX ) (Hart & Staveland, 1988), the Subjec- tive Workload Assessment...Factor Metric Experience Demographic questionnaire Stress level NASA TLX SWAT Assessment Observer reports Confidence Logged performance data...Mahwah, New Jersey: Law- rence Erlbaum Associates. Hart, S. G., & Staveland, L. E. (1988). Development of NASA - TLX (Task Load Index): Results of

Zone calculation as a tool for assessing performance outcome in laparoscopic suturing.

PubMed

Buckley, Christina E; Kavanagh, Dara O; Nugent, Emmeline; Ryan, Donncha; Traynor, Oscar J; Neary, Paul C

2015-06-01

Simulator performance is measured by metrics, which are valued as an objective way of assessing trainees. Certain procedures such as laparoscopic suturing, however, may not be suitable for assessment under traditionally formulated metrics. Our aim was to assess if our new metric is a valid method of assessing laparoscopic suturing. A software program was developed to order to create a new metric, which would calculate the percentage of time spent operating within pre-defined areas called "zones." Twenty-five candidates (medical students N = 10, surgical residents N = 10, and laparoscopic experts N = 5) performed the laparoscopic suturing task on the ProMIS III(®) simulator. New metrics of "in-zone" and "out-zone" scores as well as traditional metrics of time, path length, and smoothness were generated. Performance was also assessed by two blinded observers using the OSATS and FLS rating scales. This novel metric was evaluated by comparing it to both traditional metrics and subjective scores. There was a significant difference in the average in-zone and out-zone scores between all three experience groups (p < 0.05). The new zone metrics scores correlated significantly with the subjective-blinded observer scores of OSATS and FLS (p = 0.0001). The new zone metric scores also correlated significantly with the traditional metrics of path length, time, and smoothness (p < 0.05). The new metric is a valid tool for assessing laparoscopic suturing objectively. This could be incorporated into a competency-based curriculum to monitor resident progression in the simulated setting.

Flight Tasks and Metrics to Evaluate Laser Eye Protection in Flight Simulators

DTIC Science & Technology

2017-07-07

AFRL-RH-FS-TR-2017-0026 Flight Tasks and Metrics to Evaluate Laser Eye Protection in Flight Simulators Thomas K. Kuyk Peter A. Smith Solangia...34Flight Tasks and Metrics to Evaluate Laser Eye Protection in Flight Simulators" (AFRL-RH-FS-TR- 2017 - 0026 SHORTER.PATRI CK.D.1023156390 Digitally...SUBTITLE Flight Tasks and Metrics to Evaluate Laser Eye Protection in Flight Simulators 5a. CONTRACT NUMBER FA8650-14-D-6519 5b. GRANT NUMBER 5c

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes.

PubMed

Kireeva, Natalia V; Ovchinnikova, Svetlana I; Kuznetsov, Sergey L; Kazennov, Andrey M; Tsivadze, Aslan Yu

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Impact of distance-based metric learning on classification and visualization model performance and structure-activity landscapes

NASA Astrophysics Data System (ADS)

Kireeva, Natalia V.; Ovchinnikova, Svetlana I.; Kuznetsov, Sergey L.; Kazennov, Andrey M.; Tsivadze, Aslan Yu.

2014-02-01

This study concerns large margin nearest neighbors classifier and its multi-metric extension as the efficient approaches for metric learning which aimed to learn an appropriate distance/similarity function for considered case studies. In recent years, many studies in data mining and pattern recognition have demonstrated that a learned metric can significantly improve the performance in classification, clustering and retrieval tasks. The paper describes application of the metric learning approach to in silico assessment of chemical liabilities. Chemical liabilities, such as adverse effects and toxicity, play a significant role in drug discovery process, in silico assessment of chemical liabilities is an important step aimed to reduce costs and animal testing by complementing or replacing in vitro and in vivo experiments. Here, to our knowledge for the first time, a distance-based metric learning procedures have been applied for in silico assessment of chemical liabilities, the impact of metric learning on structure-activity landscapes and predictive performance of developed models has been analyzed, the learned metric was used in support vector machines. The metric learning results have been illustrated using linear and non-linear data visualization techniques in order to indicate how the change of metrics affected nearest neighbors relations and descriptor space.

Reducing radiation dose to the female breast during CT coronary angiography: A simulation study comparing breast shielding, angular tube current modulation, reduced kV, and partial angle protocols using an unknown-location signal-detectability metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rupcich, Franco; Gilat Schmidt, Taly; Badal, Andreu

2013-08-15

Purpose: The authors compared the performance of five protocols intended to reduce dose to the breast during computed tomography (CT) coronary angiography scans using a model observer unknown-location signal-detectability metric.Methods: The authors simulated CT images of an anthropomorphic female thorax phantom for a 120 kV reference protocol and five “dose reduction” protocols intended to reduce dose to the breast: 120 kV partial angle (posteriorly centered), 120 kV tube-current modulated (TCM), 120 kV with shielded breasts, 80 kV, and 80 kV partial angle (posteriorly centered). Two image quality tasks were investigated: the detection and localization of 4-mm, 3.25 mg/ml and 1-mm,more » 6.0 mg/ml iodine contrast signals randomly located in the heart region. For each protocol, the authors plotted the signal detectability, as quantified by the area under the exponentially transformed free response characteristic curve estimator (A-caret{sub FE}), as well as noise and contrast-to-noise ratio (CNR) versus breast and lung dose. In addition, the authors quantified each protocol's dose performance as the percent difference in dose relative to the reference protocol achieved while maintaining equivalent A-caret{sub FE}.Results: For the 4-mm signal-size task, the 80 kV full scan and 80 kV partial angle protocols decreased dose to the breast (80.5% and 85.3%, respectively) and lung (80.5% and 76.7%, respectively) with A-caret{sub FE} = 0.96, but also resulted in an approximate three-fold increase in image noise. The 120 kV partial protocol reduced dose to the breast (17.6%) at the expense of increased lung dose (25.3%). The TCM algorithm decreased dose to the breast (6.0%) and lung (10.4%). Breast shielding increased breast dose (67.8%) and lung dose (103.4%). The 80 kV and 80 kV partial protocols demonstrated greater dose reductions for the 4-mm task than for the 1-mm task, and the shielded protocol showed a larger increase in dose for the 4-mm task than for the 1-mm task. In general, the CNR curves indicate a similar relative ranking of protocol performance as the corresponding A-caret{sub FE} curves, however, the CNR metric overestimated the performance of the shielded protocol for both tasks, leading to corresponding underestimates in the relative dose increases compared to those obtained when using the A-caret{sub FE} metric.Conclusions: The 80 kV and 80 kV partial angle protocols demonstrated the greatest reduction to breast and lung dose, however, the subsequent increase in image noise may be deemed clinically unacceptable. Tube output for these protocols can be adjusted to achieve a more desirable noise level with lesser breast dose savings. Breast shielding increased breast and lung dose when maintaining equivalent A-caret{sub FE}. The results demonstrated that comparisons of dose performance depend on both the image quality metric and the specific task, and that CNR may not be a reliable metric of signal detectability.« less

Development and validation of a composite scoring system for robot-assisted surgical training--the Robotic Skills Assessment Score.

PubMed

Chowriappa, Ashirwad J; Shi, Yi; Raza, Syed Johar; Ahmed, Kamran; Stegemann, Andrew; Wilding, Gregory; Kaouk, Jihad; Peabody, James O; Menon, Mani; Hassett, James M; Kesavadas, Thenkurussi; Guru, Khurshid A

2013-12-01

A standardized scoring system does not exist in virtual reality-based assessment metrics to describe safe and crucial surgical skills in robot-assisted surgery. This study aims to develop an assessment score along with its construct validation. All subjects performed key tasks on previously validated Fundamental Skills of Robotic Surgery curriculum, which were recorded, and metrics were stored. After an expert consensus for the purpose of content validation (Delphi), critical safety determining procedural steps were identified from the Fundamental Skills of Robotic Surgery curriculum and a hierarchical task decomposition of multiple parameters using a variety of metrics was used to develop Robotic Skills Assessment Score (RSA-Score). Robotic Skills Assessment mainly focuses on safety in operative field, critical error, economy, bimanual dexterity, and time. Following, the RSA-Score was further evaluated for construct validation and feasibility. Spearman correlation tests performed between tasks using the RSA-Scores indicate no cross correlation. Wilcoxon rank sum tests were performed between the two groups. The proposed RSA-Score was evaluated on non-robotic surgeons (n = 15) and on expert-robotic surgeons (n = 12). The expert group demonstrated significantly better performance on all four tasks in comparison to the novice group. Validation of the RSA-Score in this study was carried out on the Robotic Surgical Simulator. The RSA-Score is a valid scoring system that could be incorporated in any virtual reality-based surgical simulator to achieve standardized assessment of fundamental surgical tents during robot-assisted surgery. Copyright © 2013 Elsevier Inc. All rights reserved.

FAST COGNITIVE AND TASK ORIENTED, ITERATIVE DATA DISPLAY (FACTOID)

DTIC Science & Technology

2017-06-01

approaches. As a result, the following assumptions guided our efforts in developing modeling and descriptive metrics for evaluation purposes...Application Evaluation . Our analytic workflow for evaluation is to first provide descriptive statistics about applications across metrics (performance...distributions for evaluation purposes because the goal of evaluation is accurate description , not inference (e.g., prediction). Outliers depicted

Decomposition-based transfer distance metric learning for image classification.

PubMed

Luo, Yong; Liu, Tongliang; Tao, Dacheng; Xu, Chao

2014-09-01

Distance metric learning (DML) is a critical factor for image analysis and pattern recognition. To learn a robust distance metric for a target task, we need abundant side information (i.e., the similarity/dissimilarity pairwise constraints over the labeled data), which is usually unavailable in practice due to the high labeling cost. This paper considers the transfer learning setting by exploiting the large quantity of side information from certain related, but different source tasks to help with target metric learning (with only a little side information). The state-of-the-art metric learning algorithms usually fail in this setting because the data distributions of the source task and target task are often quite different. We address this problem by assuming that the target distance metric lies in the space spanned by the eigenvectors of the source metrics (or other randomly generated bases). The target metric is represented as a combination of the base metrics, which are computed using the decomposed components of the source metrics (or simply a set of random bases); we call the proposed method, decomposition-based transfer DML (DTDML). In particular, DTDML learns a sparse combination of the base metrics to construct the target metric by forcing the target metric to be close to an integration of the source metrics. The main advantage of the proposed method compared with existing transfer metric learning approaches is that we directly learn the base metric coefficients instead of the target metric. To this end, far fewer variables need to be learned. We therefore obtain more reliable solutions given the limited side information and the optimization tends to be faster. Experiments on the popular handwritten image (digit, letter) classification and challenge natural image annotation tasks demonstrate the effectiveness of the proposed method.

Task-Driven Comparison of Topic Models.

PubMed

Alexander, Eric; Gleicher, Michael

2016-01-01

Topic modeling, a method of statistically extracting thematic content from a large collection of texts, is used for a wide variety of tasks within text analysis. Though there are a growing number of tools and techniques for exploring single models, comparisons between models are generally reduced to a small set of numerical metrics. These metrics may or may not reflect a model's performance on the analyst's intended task, and can therefore be insufficient to diagnose what causes differences between models. In this paper, we explore task-centric topic model comparison, considering how we can both provide detail for a more nuanced understanding of differences and address the wealth of tasks for which topic models are used. We derive comparison tasks from single-model uses of topic models, which predominantly fall into the categories of understanding topics, understanding similarity, and understanding change. Finally, we provide several visualization techniques that facilitate these tasks, including buddy plots, which combine color and position encodings to allow analysts to readily view changes in document similarity.

Strategy quantification using body worn inertial sensors in a reactive agility task.

PubMed

Eke, Chika U; Cain, Stephen M; Stirling, Leia A

2017-11-07

Agility performance is often evaluated using time-based metrics, which provide little information about which factors aid or limit success. The objective of this study was to better understand agility strategy by identifying biomechanical metrics that were sensitive to performance speed, which were calculated with data from an array of body-worn inertial sensors. Five metrics were defined (normalized number of foot contacts, stride length variance, arm swing variance, mean normalized stride frequency, and number of body rotations) that corresponded to agility terms defined by experts working in athletic, clinical, and military environments. Eighteen participants donned 13 sensors to complete a reactive agility task, which involved navigating a set of cones in response to a vocal cue. Participants were grouped into fast, medium, and slow performance based on their completion time. Participants in the fast group had the smallest number of foot contacts (normalizing by height), highest stride length variance (normalizing by height), highest forearm angular velocity variance, and highest stride frequency (normalizing by height). The number of body rotations was not sensitive to speed and may have been determined by hand and foot dominance while completing the agility task. The results of this study have the potential to inform the development of a composite agility score constructed from the list of significant metrics. By quantifying the agility terms previously defined by expert evaluators through an agility score, this study can assist in strategy development for training and rehabilitation across athletic, clinical, and military domains. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Investigation of the Relationship Between Automated Machine Translation Evaluation Metrics and User Performance on an Information Extraction Task

DTIC Science & Technology

2007-01-01

parameter dimension between the two models). 93 were tested.3 Model 1 log( pHits 1− pHits ) = α + β1 ∗ MetricScore (6.6) The results for each of the...505.67 oTERavg .357 .13 .007 log( pHits 1− pHits ), that is, log-odds of correct task performance, of 2.79 over the intercept only model. All... pHits 1− pHits ) = −1.15− .418× I[MT=2] − .527× I[MT=3] + 1.78×METEOR+ 1.28×METEOR × I[MT=2] + 1.86×METEOR × I[MT=3] (6.7) Model 3 log( pHits 1− pHits

Cognitive skills assessment during robot-assisted surgery: separating the wheat from the chaff.

PubMed

Guru, Khurshid A; Esfahani, Ehsan T; Raza, Syed J; Bhat, Rohit; Wang, Katy; Hammond, Yana; Wilding, Gregory; Peabody, James O; Chowriappa, Ashirwad J

2015-01-01

To investigate the utility of cognitive assessment during robot-assisted surgery (RAS) to define skills in terms of cognitive engagement, mental workload, and mental state; while objectively differentiating between novice and expert surgeons. In all, 10 surgeons with varying operative experience were assigned to beginner (BG), combined competent and proficient (CPG), and expert (EG) groups based on the Dreyfus model. The participants performed tasks for basic, intermediate and advanced skills on the da Vinci Surgical System. Participant performance was assessed using both tool-based and cognitive metrics. Tool-based metrics showed significant differences between the BG vs CPG and the BG vs EG, in basic skills. While performing intermediate skills, there were significant differences only on the instrument-to-instrument collisions between the BG vs CPG (2.0 vs 0.2, P = 0.028), and the BG vs EG (2.0 vs 0.1, P = 0.018). There were no significant differences between the CPG and EG for both basic and intermediate skills. However, using cognitive metrics, there were significant differences between all groups for the basic and intermediate skills. In advanced skills, there were no significant differences between the CPG and the EG except time (1116 vs 599.6 s), using tool-based metrics. However, cognitive metrics revealed significant differences between both groups. Cognitive assessment of surgeons may aid in defining levels of expertise performing complex surgical tasks once competence is achieved. Cognitive assessment may be used as an adjunct to the traditional methods for skill assessment during RAS. © 2014 The Authors. BJU International © 2014 BJU International.

Temporal discounting and emotional self-regulation in children with attention-deficit/hyperactivity disorder.

PubMed

Utsumi, Daniel Augusto; Miranda, Mônica Carolina; Muszkat, Mauro

2016-12-30

Temporal Discounting (TD) reflects a tendency to discount a reward more deeply the longer its delivery is delayed. TD tasks and behavioral scales have been used to investigate 'hot' executive functions in ADHD. The present study analyzed TD task performance shown by ADHD and control groups for correlations with emotional self-regulation metrics from two scales, the Behavior Rating Inventory of Executive Functions (BRIEF) and the Child Behavior Checklist (CBCL). Children (ages 8-12) with ADHD (n=25) and controls (n=24) were assessed using material rewards (toys) for three types of task: Hypothetical (H); Hypothetical with temporal expectation (HTE); and Real (R). Between-group differences were found for the HTE task, on which the ADHD group showed a higher rate of discounting their favorite toy over time, especially at 10s and 20s. This was the only task on which performance significantly correlated with BRIEF metrics, thus suggesting associations between impulsivity and low emotional self-regulation, but no task was correlated with CBCL score. The conclusion is that tasks involving toys and HTE in particular may be used to investigate TD in children with ADHD and as a means of evaluating the interface between the reward system and emotional self-regulation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Objective Situation Awareness Measurement Based on Performance Self-Evaluation

NASA Technical Reports Server (NTRS)

DeMaio, Joe

1998-01-01

The research was conducted in support of the NASA Safe All-Weather Flight Operations for Rotorcraft (SAFOR) program. The purpose of the work was to investigate the utility of two measurement tools developed by the British Defense Evaluation Research Agency. These tools were a subjective workload assessment scale, the DRA Workload Scale and a situation awareness measurement tool. The situation awareness tool uses a comparison of the crew's self-evaluation of performance against actual performance in order to determine what information the crew attended to during the performance. These two measurement tools were evaluated in the context of a test of innovative approach to alerting the crew by way of a helmet mounted display. The situation assessment data are reported here. The performance self-evaluation metric of situation awareness was found to be highly effective. It was used to evaluate situation awareness on a tank reconnaissance task, a tactical navigation task, and a stylized task used to evaluated handling qualities. Using the self-evaluation metric, it was possible to evaluate situation awareness, without exact knowledge the relevant information in some cases and to identify information to which the crew attended or failed to attend in others.

Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination.

PubMed

Johnson, S J; Hunt, C M; Woolnough, H M; Crawshaw, M; Kilkenny, C; Gould, D A; England, A; Sinha, A; Villard, P F

2012-05-01

The aim of this article was to identify and prospectively investigate simulated ultrasound-guided targeted liver biopsy performance metrics as differentiators between levels of expertise in interventional radiology. Task analysis produced detailed procedural step documentation allowing identification of critical procedure steps and performance metrics for use in a virtual reality ultrasound-guided targeted liver biopsy procedure. Consultant (n=14; male=11, female=3) and trainee (n=26; male=19, female=7) scores on the performance metrics were compared. Ethical approval was granted by the Liverpool Research Ethics Committee (UK). Independent t-tests and analysis of variance (ANOVA) investigated differences between groups. Independent t-tests revealed significant differences between trainees and consultants on three performance metrics: targeting, p=0.018, t=-2.487 (-2.040 to -0.207); probe usage time, p = 0.040, t=2.132 (11.064 to 427.983); mean needle length in beam, p=0.029, t=-2.272 (-0.028 to -0.002). ANOVA reported significant differences across years of experience (0-1, 1-2, 3+ years) on seven performance metrics: no-go area touched, p=0.012; targeting, p=0.025; length of session, p=0.024; probe usage time, p=0.025; total needle distance moved, p=0.038; number of skin contacts, p<0.001; total time in no-go area, p=0.008. More experienced participants consistently received better performance scores on all 19 performance metrics. It is possible to measure and monitor performance using simulation, with performance metrics providing feedback on skill level and differentiating levels of expertise. However, a transfer of training study is required.

Distance and direction, but not light cues, support response reversal learning.

PubMed

Wright, S L; Martin, G M; Thorpe, C M; Haley, K; Skinner, D M

2018-03-05

Across three experiments, we examined the cuing properties of metric (distance and direction) and nonmetric (lighting) cues in different tasks. In Experiment 1, rats were trained on a response problem in a T-maze, followed by four reversals. Rats that experienced a change in maze orientation (Direction group) or a change in the length of the start arm (Distance group) across reversals showed facilitation of reversal learning relative to a group that experienced changes in room lighting across reversals. In Experiment 2, rats learned a discrimination task more readily when distance or direction cues were used than when light cues were used as the discriminative stimuli. In Experiment 3, performance on a go/no-go task was equivalent using both direction and lighting cues. The successful use of both metric and nonmetric cues in the go/no-go task indicates that rats are sensitive to both types of cues and that the usefulness of different cues is dependent on the nature of the task.

The correlation between fundamental characteristics and first-time performance in laparoscopic tasks.

PubMed

Harrington, Cuan M; Bresler, Richard; Ryan, Donncha; Dicker, Patrick; Traynor, Oscar; Kavanagh, Dara O

2018-04-01

The ability of characteristics to predict first time performance in laparoscopic tasks is not well described. Videogame experience predicts positive performance in laparoscopic experiences but its mechanism and confounding-association with aptitude remains to be elucidated. This study sought to evaluate for innate predictors of laparoscopic performance in surgically naive individuals with minimal videogame exposure. Participants with no prior laparoscopic exposure and minimal videogaming experience were recruited consecutively from preclinical years at a medical university. Participants completed four visuospatial, one psychomotor aptitude test and an electronic survey, followed by four laparoscopic tasks on a validated Virtual Reality simulator (LAP Mentor™). Twenty eligible individuals participated with a mean age of 20.8 (±3.8) years. Significant intra-aptitude performance correlations were present amongst 75% of the visuospatial tests. These visuospatial aptitudes correlated significantly with multiple laparoscopic task metrics: number of movements of a dominant instrument (r s  ≥ -0.46), accuracy rate of clip placement (r s  ≥ 0.50) and time taken (r s  ≥ -0.47) (p < 0.05). Musical Instrument experience predicted higher average speed of instruments (r s  ≥ 0.47) (p < 0.05). Participant's revised competitive index level predicted lower proficiency in laparoscopic metrics including: pathlength, economy and number of movements of dominant instrument (r s  ≥ 0.46) (p < 0.05). Multiple visuospatial aptitudes and innate competitive level influenced baseline laparoscopic performances across several tasks in surgically naïve individuals. Copyright © 2017 Elsevier Inc. All rights reserved.

Functional Task Test: 3. Skeletal Muscle Performance Adaptations to Space Flight

NASA Technical Reports Server (NTRS)

Ryder, Jeffrey W.; Wickwire, P. J.; Buxton, R. E.; Bloomberg, J. J.; Ploutz-Snyder, L.

2011-01-01

The functional task test is a multi-disciplinary study investigating how space-flight induced changes to physiological systems impacts functional task performance. Impairment of neuromuscular function would be expected to negatively affect functional performance of crewmembers following exposure to microgravity. This presentation reports the results for muscle performance testing in crewmembers. Functional task performance will be presented in the abstract "Functional Task Test 1: sensory motor adaptations associated with postflight alternations in astronaut functional task performance." METHODS: Muscle performance measures were obtained in crewmembers before and after short-duration space flight aboard the Space Shuttle and long-duration International Space Station (ISS) missions. The battery of muscle performance tests included leg press and bench press measures of isometric force, isotonic power and total work. Knee extension was used for the measurement of central activation and maximal isometric force. Upper and lower body force steadiness control were measured on the bench press and knee extension machine, respectively. Tests were implemented 60 and 30 days before launch, on landing day (Shuttle crew only), and 6, 10 and 30 days after landing. Seven Space Shuttle crew and four ISS crew have completed the muscle performance testing to date. RESULTS: Preliminary results for Space Shuttle crew reveal significant reductions in the leg press performance metrics of maximal isometric force, power and total work on R+0 (p<0.05). Bench press total work was also significantly impaired, although maximal isometric force and power were not significantly affected. No changes were noted for measurements of central activation or force steadiness. Results for ISS crew were not analyzed due to the current small sample size. DISCUSSION: Significant reductions in lower body muscle performance metrics were observed in returning Shuttle crew and these adaptations are likely contributors to impaired functional tasks that are ambulatory in nature (See abstract Functional Task Test: 1). Interestingly, no significant changes in central activation capacity were detected. Therefore, impairments in muscle function in response to short-duration space flight are likely myocellular rather than neuromotor in nature.

Behavioral and Neural Correlates of Executive Function: Interplay between Inhibition and Updating Processes.

PubMed

Kim, Na Young; Wittenberg, Ellen; Nam, Chang S

2017-01-01

This study investigated the interaction between two executive function processes, inhibition and updating, through analyses of behavioral, neurophysiological, and effective connectivity metrics. Although, many studies have focused on behavioral effects of executive function processes individually, few studies have examined the dynamic causal interactions between these two functions. A total of twenty participants from a local university performed a dual task combing flanker and n-back experimental paradigms, and completed the Operation Span Task designed to measure working memory capacity. We found that both behavioral (accuracy and reaction time) and neurophysiological (P300 amplitude and alpha band power) metrics on the inhibition task (i.e., flanker task) were influenced by the updating load (n-back level) and modulated by working memory capacity. Using independent component analysis, source localization (DIPFIT), and Granger Causality analysis of the EEG time-series data, the present study demonstrated that manipulation of cognitive demand in a dual executive function task influenced the causal neural network. We compared connectivity across three updating loads (n-back levels) and found that experimental manipulation of working memory load enhanced causal connectivity of a large-scale neurocognitive network. This network contains the prefrontal and parietal cortices, which are associated with inhibition and updating executive function processes. This study has potential applications in human performance modeling and assessment of mental workload, such as the design of training materials and interfaces for those performing complex multitasking under stress.

The three-class ideal observer for univariate normal data: Decision variable and ROC surface properties

PubMed Central

Edwards, Darrin C.; Metz, Charles E.

2012-01-01

Although a fully general extension of ROC analysis to classification tasks with more than two classes has yet to be developed, the potential benefits to be gained from a practical performance evaluation methodology for classification tasks with three classes have motivated a number of research groups to propose methods based on constrained or simplified observer or data models. Here we consider an ideal observer in a task with underlying data drawn from three univariate normal distributions. We investigate the behavior of the resulting ideal observer’s decision variables and ROC surface. In particular, we show that the pair of ideal observer decision variables is constrained to a parametric curve in two-dimensional likelihood ratio space, and that the decision boundary line segments used by the ideal observer can intersect this curve in at most six places. From this, we further show that the resulting ROC surface has at most four degrees of freedom at any point, and not the five that would be required, in general, for a surface in a six-dimensional space to be non-degenerate. In light of the difficulties we have previously pointed out in generalizing the well-known area under the ROC curve performance metric to tasks with three or more classes, the problem of developing a suitable and fully general performance metric for classification tasks with three or more classes remains unsolved. PMID:23162165

Checkpoint triggering in a computer system

DOEpatents

Cher, Chen-Yong

2016-09-06

According to an aspect, a method for triggering creation of a checkpoint in a computer system includes executing a task in a processing node of the computer system and determining whether it is time to read a monitor associated with a metric of the task. The monitor is read to determine a value of the metric based on determining that it is time to read the monitor. A threshold for triggering creation of the checkpoint is determined based on the value of the metric. Based on determining that the value of the metric has crossed the threshold, the checkpoint including state data of the task is created to enable restarting execution of the task upon a restart operation.

Virtual reality, ultrasound-guided liver biopsy simulator: development and performance discrimination

PubMed Central

Johnson, S J; Hunt, C M; Woolnough, H M; Crawshaw, M; Kilkenny, C; Gould, D A; England, A; Sinha, A; Villard, P F

2012-01-01

Objectives The aim of this article was to identify and prospectively investigate simulated ultrasound-guided targeted liver biopsy performance metrics as differentiators between levels of expertise in interventional radiology. Methods Task analysis produced detailed procedural step documentation allowing identification of critical procedure steps and performance metrics for use in a virtual reality ultrasound-guided targeted liver biopsy procedure. Consultant (n=14; male=11, female=3) and trainee (n=26; male=19, female=7) scores on the performance metrics were compared. Ethical approval was granted by the Liverpool Research Ethics Committee (UK). Independent t-tests and analysis of variance (ANOVA) investigated differences between groups. Results Independent t-tests revealed significant differences between trainees and consultants on three performance metrics: targeting, p=0.018, t=−2.487 (−2.040 to −0.207); probe usage time, p = 0.040, t=2.132 (11.064 to 427.983); mean needle length in beam, p=0.029, t=−2.272 (−0.028 to −0.002). ANOVA reported significant differences across years of experience (0–1, 1–2, 3+ years) on seven performance metrics: no-go area touched, p=0.012; targeting, p=0.025; length of session, p=0.024; probe usage time, p=0.025; total needle distance moved, p=0.038; number of skin contacts, p<0.001; total time in no-go area, p=0.008. More experienced participants consistently received better performance scores on all 19 performance metrics. Conclusion It is possible to measure and monitor performance using simulation, with performance metrics providing feedback on skill level and differentiating levels of expertise. However, a transfer of training study is required. PMID:21304005

No-reference image quality assessment for horizontal-path imaging scenarios

NASA Astrophysics Data System (ADS)

Rios, Carlos; Gladysz, Szymon

2013-05-01

There exist several image-enhancement algorithms and tasks associated with imaging through turbulence that depend on defining the quality of an image. Examples include: "lucky imaging", choosing the width of the inverse filter for image reconstruction, or stopping iterative deconvolution. We collected a number of image quality metrics found in the literature. Particularly interesting are the blind, "no-reference" metrics. We discuss ways of evaluating the usefulness of these metrics, even when a fully objective comparison is impossible because of the lack of a reference image. Metrics are tested on simulated and real data. Field data comes from experiments performed by the NATO SET 165 research group over a 7 km distance in Dayton, Ohio.

Energy-Based Metrics for Arthroscopic Skills Assessment.

PubMed

Poursartip, Behnaz; LeBel, Marie-Eve; McCracken, Laura C; Escoto, Abelardo; Patel, Rajni V; Naish, Michael D; Trejos, Ana Luisa

2017-08-05

Minimally invasive skills assessment methods are essential in developing efficient surgical simulators and implementing consistent skills evaluation. Although numerous methods have been investigated in the literature, there is still a need to further improve the accuracy of surgical skills assessment. Energy expenditure can be an indication of motor skills proficiency. The goals of this study are to develop objective metrics based on energy expenditure, normalize these metrics, and investigate classifying trainees using these metrics. To this end, different forms of energy consisting of mechanical energy and work were considered and their values were divided by the related value of an ideal performance to develop normalized metrics. These metrics were used as inputs for various machine learning algorithms including support vector machines (SVM) and neural networks (NNs) for classification. The accuracy of the combination of the normalized energy-based metrics with these classifiers was evaluated through a leave-one-subject-out cross-validation. The proposed method was validated using 26 subjects at two experience levels (novices and experts) in three arthroscopic tasks. The results showed that there are statistically significant differences between novices and experts for almost all of the normalized energy-based metrics. The accuracy of classification using SVM and NN methods was between 70% and 95% for the various tasks. The results show that the normalized energy-based metrics and their combination with SVM and NN classifiers are capable of providing accurate classification of trainees. The assessment method proposed in this study can enhance surgical training by providing appropriate feedback to trainees about their level of expertise and can be used in the evaluation of proficiency.

Role of quality of service metrics in visual target acquisition and tracking in resource constrained environments

NASA Astrophysics Data System (ADS)

Anderson, Monica; David, Phillip

2007-04-01

Implementation of an intelligent, automated target acquisition and tracking systems alleviates the need for operators to monitor video continuously. This system could identify situations that fatigued operators could easily miss. If an automated acquisition and tracking system plans motions to maximize a coverage metric, how does the performance of that system change when the user intervenes and manually moves the camera? How can the operator give input to the system about what is important and understand how that relates to the overall task balance between surveillance and coverage? In this paper, we address these issues by introducing a new formulation of the average linear uncovered length (ALUL) metric, specially designed for use in surveilling urban environments. This metric coordinates the often competing goals of acquiring new targets and tracking existing targets. In addition, it provides current system performance feedback to system users in terms of the system's theoretical maximum and minimum performance. We show the successful integration of the algorithm via simulation.

Constrained Metric Learning by Permutation Inducing Isometries.

PubMed

Bosveld, Joel; Mahmood, Arif; Huynh, Du Q; Noakes, Lyle

2016-01-01

The choice of metric critically affects the performance of classification and clustering algorithms. Metric learning algorithms attempt to improve performance, by learning a more appropriate metric. Unfortunately, most of the current algorithms learn a distance function which is not invariant to rigid transformations of images. Therefore, the distances between two images and their rigidly transformed pair may differ, leading to inconsistent classification or clustering results. We propose to constrain the learned metric to be invariant to the geometry preserving transformations of images that induce permutations in the feature space. The constraint that these transformations are isometries of the metric ensures consistent results and improves accuracy. Our second contribution is a dimension reduction technique that is consistent with the isometry constraints. Our third contribution is the formulation of the isometry constrained logistic discriminant metric learning (IC-LDML) algorithm, by incorporating the isometry constraints within the objective function of the LDML algorithm. The proposed algorithm is compared with the existing techniques on the publicly available labeled faces in the wild, viewpoint-invariant pedestrian recognition, and Toy Cars data sets. The IC-LDML algorithm has outperformed existing techniques for the tasks of face recognition, person identification, and object classification by a significant margin.

Metrics for TRUST in Integrated Circuits

DTIC Science & Technology

2008-06-01

metrics; Trojan ; detection Introduction In the Defense Science Board report, “DSB Task Force on High Performance Microchip Supply” [1] several...BETAINV C m M m= − + − + Where Ptd | lower is a lower bound on Ptd with confidence C, m is the number of detected Trojan transistors, and M is the...total number of Trojan transistors. From this relationship, in order to establish Ptd = 90% at 90% confidence on a single test article, we must

Prostate Cancer Biorepository Network

DTIC Science & Technology

2017-10-01

Department of the Army position, policy or decision unless so designated by other documentation. REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704...clinical data including pathology and outcome data are annotated with the biospecimens. Specialized processing consists of tissue microarray design ...Months 1- 6): Completed in 1st quarter Task 5. Report on performance metrics: Ongoing (accrual reports are provided on quarterly basis) Task 6

Assessment program for Kentucky traffic records.

DOT National Transportation Integrated Search

2015-02-01

During 2013, the Kentucky Transportation Center identified 117 potential performance metrics for the ten databases in : the Kentucky Traffic Records System. This report summarizes the findings of three main tasks completed in 2014: (1) : assessment o...

Person re-identification over camera networks using multi-task distance metric learning.

PubMed

Ma, Lianyang; Yang, Xiaokang; Tao, Dacheng

2014-08-01

Person reidentification in a camera network is a valuable yet challenging problem to solve. Existing methods learn a common Mahalanobis distance metric by using the data collected from different cameras and then exploit the learned metric for identifying people in the images. However, the cameras in a camera network have different settings and the recorded images are seriously affected by variability in illumination conditions, camera viewing angles, and background clutter. Using a common metric to conduct person reidentification tasks on different camera pairs overlooks the differences in camera settings; however, it is very time-consuming to label people manually in images from surveillance videos. For example, in most existing person reidentification data sets, only one image of a person is collected from each of only two cameras; therefore, directly learning a unique Mahalanobis distance metric for each camera pair is susceptible to over-fitting by using insufficiently labeled data. In this paper, we reformulate person reidentification in a camera network as a multitask distance metric learning problem. The proposed method designs multiple Mahalanobis distance metrics to cope with the complicated conditions that exist in typical camera networks. We address the fact that these Mahalanobis distance metrics are different but related, and learned by adding joint regularization to alleviate over-fitting. Furthermore, by extending, we present a novel multitask maximally collapsing metric learning (MtMCML) model for person reidentification in a camera network. Experimental results demonstrate that formulating person reidentification over camera networks as multitask distance metric learning problem can improve performance, and our proposed MtMCML works substantially better than other current state-of-the-art person reidentification methods.

The effect of acute tyrosine phenylalanine depletion on emotion-based decision-making in healthy adults.

PubMed

Vrshek-Schallhorn, Suzanne; Wahlstrom, Dustin; White, Tonya; Luciana, Monica

2013-04-01

Despite interest in dopamine's role in emotion-based decision-making, few reports of the effects of dopamine manipulations are available in this area in humans. This study investigates dopamine's role in emotion-based decision-making through a common measure of this construct, the Iowa Gambling Task (IGT), using Acute Tyrosine Phenylalanine Depletion (ATPD). In a between-subjects design, 40 healthy adults were randomized to receive either an ATPD beverage or a balanced amino acid beverage (a control) prior to completing the IGT, as well as pre- and post-manipulation blood draws for the neurohormone prolactin. Together with conventional IGT performance metrics, choice selections and response latencies were examined separately for good and bad choices before and after several key punishment events. Changes in response latencies were also used to predict total task performance. Prolactin levels increased significantly in the ATPD group but not in the control group. However, no significant group differences in performance metrics were detected, nor were there sex differences in outcome measures. However, the balanced group's bad deck latencies speeded up across the task, while the ATPD group's latencies remained adaptively hesitant. Additionally, modulation of latencies to the bad decks predicted total score for the ATPD group only. One interpretation is that ATPD subtly attenuated reward salience and altered the approach by which individuals achieved successful performance, without resulting in frank group differences in task performance. Copyright © 2013 Elsevier Inc. All rights reserved.

78 FR 28940 - Ninth Meeting: RTCA Next Gen Advisory Committee (NAC)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-16

.... Huerta FAA NextGen Performance SnapShots Featured PBN Implementation Location Data Sources for Measuring... by the Business Case and Performance Metrics Work Group Recommendation for Implementing Categorical Exclusion Contained in FAA Modernization Act of 2012 Recommendation developed by CatEx2 Task Group for...

Display/control requirements for VTOL aircraft

NASA Technical Reports Server (NTRS)

Hoffman, W. C.; Curry, R. E.; Kleinman, D. L.; Hollister, W. M.; Young, L. R.

1975-01-01

Quantative metrics were determined for system control performance, workload for control, monitoring performance, and workload for monitoring. Pilot tasks were allocated for navigation and guidance of automated commercial V/STOL aircraft in all weather conditions using an optimal control model of the human operator to determine display elements and design.

Does stereo-endoscopy improve neurosurgical targeting in 3rd ventriculostomy?

NASA Astrophysics Data System (ADS)

Abhari, Kamyar; de Ribaupierre, Sandrine; Peters, Terry; Eagleson, Roy

2011-03-01

Endoscopic third ventriculostomy is a minimally invasive surgical technique to treat hydrocephalus; a condition where patients suffer from excessive amounts of cerebrospinal fluid (CSF) in the ventricular system of their brain. This technique involves using a monocular endoscope to locate the third ventricle, where a hole can be made to drain excessive fluid. Since a monocular endoscope provides only a 2D view, it is difficult to make this perforation due to the lack of monocular cues and depth perception. In a previous study, we had investigated the use of a stereo-endoscope to allow neurosurgeons to locate and avoid hazardous areas on the surface of the third ventricle. In this paper, we extend our previous study by developing a new methodology to evaluate the targeting performance in piercing the hole in the membrane. We consider the accuracy of this surgical task and derive an index of performance for a task which does not have a well-defined position or width of target. Our performance metric is sensitive and can distinguish between experts and novices. We make use of this metric to demonstrate an objective learning curve on this task for each subject.

The development of a virtual reality training curriculum for colonoscopy.

PubMed

Sugden, Colin; Aggarwal, Rajesh; Banerjee, Amrita; Haycock, Adam; Thomas-Gibson, Siwan; Williams, Christopher B; Darzi, Ara

2012-07-01

The development of a structured virtual reality (VR) training curriculum for colonoscopy using high-fidelity simulation. Colonoscopy requires detailed knowledge and technical skill. Changes to working practices in recent times have reduced the availability of traditional training opportunities. Much might, therefore, be achieved by applying novel technologies such as VR simulation to colonoscopy. Scientifically developed device-specific curricula aim to maximize the yield of laboratory-based training by focusing on validated modules and linking progression to the attainment of benchmarked proficiency criteria. Fifty participants comprised of 30 novices (<10 colonoscopies), 10 intermediates (100 to 500 colonoscopies), and 10 experienced (>500 colonoscopies) colonoscopists were recruited to participate. Surrogates of proficiency, such as number of procedures undertaken, determined prospective allocation to 1 of 3 groups (novice, intermediate, and experienced). Construct validity and learning value (comparison between groups and within groups respectively) for each task and metric on the chosen simulator model determined suitability for inclusion in the curriculum. Eight tasks in possession of construct validity and significant learning curves were included in the curriculum: 3 abstract tasks, 4 part-procedural tasks, and 1 procedural task. The whole-procedure task was valid for 11 metrics including the following: "time taken to complete the task" (1238, 343, and 293 s; P < 0.001) and "insertion length with embedded tip" (23.8, 3.6, and 4.9 cm; P = 0.005). Learning curves consistently plateaued at or beyond the ninth attempt. Valid metrics were used to define benchmarks, derived from the performance of the experienced cohort, for each included task. A comprehensive, stratified, benchmarked, whole-procedure curriculum has been developed for a modern high-fidelity VR colonoscopy simulator.

Investigation of Two Models to Set and Evaluate Quality Targets for HbA1c: Biological Variation and Sigma-metrics

PubMed Central

Weykamp, Cas; John, Garry; Gillery, Philippe; English, Emma; Ji, Linong; Lenters-Westra, Erna; Little, Randie R.; Roglic, Gojka; Sacks, David B.; Takei, Izumi

2016-01-01

Background A major objective of the IFCC Task Force on implementation of HbA1c standardization is to develop a model to define quality targets for HbA1c. Methods Two generic models, the Biological Variation and Sigma-metrics model, are investigated. Variables in the models were selected for HbA1c and data of EQA/PT programs were used to evaluate the suitability of the models to set and evaluate quality targets within and between laboratories. Results In the biological variation model 48% of individual laboratories and none of the 26 instrument groups met the minimum performance criterion. In the Sigma-metrics model, with a total allowable error (TAE) set at 5 mmol/mol (0.46% NGSP) 77% of the individual laboratories and 12 of 26 instrument groups met the 2 sigma criterion. Conclusion The Biological Variation and Sigma-metrics model were demonstrated to be suitable for setting and evaluating quality targets within and between laboratories. The Sigma-metrics model is more flexible as both the TAE and the risk of failure can be adjusted to requirements related to e.g. use for diagnosis/monitoring or requirements of (inter)national authorities. With the aim of reaching international consensus on advice regarding quality targets for HbA1c, the Task Force suggests the Sigma-metrics model as the model of choice with default values of 5 mmol/mol (0.46%) for TAE, and risk levels of 2 and 4 sigma for routine laboratories and laboratories performing clinical trials, respectively. These goals should serve as a starting point for discussion with international stakeholders in the field of diabetes. PMID:25737535

Electro-Optic Identification Research Program

DTIC Science & Technology

2002-04-01

Electro - optic identification (EOID) sensors provide photographic quality images that can be used to identify mine-like contacts provided by long...tasks such as validating existing electro - optic models, development of performance metrics, and development of computer aided identification and

A Practical Method for Collecting Social Media Campaign Metrics

ERIC Educational Resources Information Center

Gharis, Laurie W.; Hightower, Mary F.

2017-01-01

Today's Extension professionals are tasked with more work and fewer resources. Integrating social media campaigns into outreach efforts can be an efficient way to meet work demands. If resources go toward social media, a practical method for collecting metrics is needed. Collecting metrics adds one more task to the workloads of Extension…

Fundamentals of neurosurgery: virtual reality tasks for training and evaluation of technical skills.

PubMed

Choudhury, Nusrat; Gélinas-Phaneuf, Nicholas; Delorme, Sébastien; Del Maestro, Rolando

2013-11-01

Technical skills training in neurosurgery is mostly done in the operating room. New educational paradigms are encouraging the development of novel training methods for surgical skills. Simulation could answer some of these needs. This article presents the development of a conceptual training framework for use on a virtual reality neurosurgical simulator. Appropriate tasks were identified by reviewing neurosurgical oncology curricula requirements and performing cognitive task analyses of basic techniques and representative surgeries. The tasks were then elaborated into training modules by including learning objectives, instructions, levels of difficulty, and performance metrics. Surveys and interviews were iteratively conducted with subject matter experts to delimitate, review, discuss, and approve each of the development stages. Five tasks were selected as representative of basic and advanced neurosurgical skill. These tasks were: 1) ventriculostomy, 2) endoscopic nasal navigation, 3) tumor debulking, 4) hemostasis, and 5) microdissection. The complete training modules were structured into easy, intermediate, and advanced settings. Performance metrics were also integrated to provide feedback on outcome, efficiency, and errors. The subject matter experts deemed the proposed modules as pertinent and useful for neurosurgical skills training. The conceptual framework presented here, the Fundamentals of Neurosurgery, represents a first attempt to develop standardized training modules for technical skills acquisition in neurosurgical oncology. The National Research Council Canada is currently developing NeuroTouch, a virtual reality simulator for cranial microneurosurgery. The simulator presently includes the five Fundamentals of Neurosurgery modules at varying stages of completion. A first pilot study has shown that neurosurgical residents obtained higher performance scores on the simulator than medical students. Further work will validate its components and use in a training curriculum. Copyright © 2013 N. Choudhury. Published by Elsevier Inc. All rights reserved.

Accounting for the phase, spatial frequency and orientation demands of the task improves metrics based on the visual Strehl ratio.

PubMed

Young, Laura K; Love, Gordon D; Smithson, Hannah E

2013-09-20

Advances in ophthalmic instrumentation have allowed high order aberrations to be measured in vivo. These measurements describe the distortions to a plane wavefront entering the eye, but not the effect they have on visual performance. One metric for predicting visual performance from a wavefront measurement uses the visual Strehl ratio, calculated in the optical transfer function (OTF) domain (VSOTF) (Thibos et al., 2004). We considered how well such a metric captures empirical measurements of the effects of defocus, coma and secondary astigmatism on letter identification and on reading. We show that predictions using the visual Strehl ratio can be significantly improved by weighting the OTF by the spatial frequency band that mediates letter identification and further improved by considering the orientation of phase and contrast changes imposed by the aberration. We additionally showed that these altered metrics compare well to a cross-correlation-based metric. We suggest a version of the visual Strehl ratio, VScombined, that incorporates primarily those phase disruptions and contrast changes that have been shown independently to affect object recognition processes. This metric compared well to VSOTF for letter identification and was the best predictor of reading performance, having a higher correlation with the data than either the VSOTF or cross-correlation-based metric. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Oculomotor Behavior Metrics Change According to Circadian Phase and Time Awake

NASA Technical Reports Server (NTRS)

Flynn-Evans, Erin E.; Tyson, Terence L.; Cravalho, Patrick; Feick, Nathan; Stone, Leland S.

2017-01-01

There is a need for non-invasive, objective measures to forecast performance impairment arising from sleep loss and circadian misalignment, particularly in safety-sensitive occupations. Eye-tracking devices have been used in some operational scenarios, but such devices typically focus on eyelid closures and slow rolling eye movements and are susceptible to the intrusion of head movement artifacts. We hypothesized that an expanded suite of oculomotor behavior metrics, collected during a visual tracking task, would change according to circadian phase and time awake, and could be used as a marker of performance impairment.

Validating models of target acquisition performance in the dismounted soldier context

NASA Astrophysics Data System (ADS)

Glaholt, Mackenzie G.; Wong, Rachel K.; Hollands, Justin G.

2018-04-01

The problem of predicting real-world operator performance with digital imaging devices is of great interest within the military and commercial domains. There are several approaches to this problem, including: field trials with imaging devices, laboratory experiments using imagery captured from these devices, and models that predict human performance based on imaging device parameters. The modeling approach is desirable, as both field trials and laboratory experiments are costly and time-consuming. However, the data from these experiments is required for model validation. Here we considered this problem in the context of dismounted soldiering, for which detection and identification of human targets are essential tasks. Human performance data were obtained for two-alternative detection and identification decisions in a laboratory experiment in which photographs of human targets were presented on a computer monitor and the images were digitally magnified to simulate range-to-target. We then compared the predictions of different performance models within the NV-IPM software package: Targeting Task Performance (TTP) metric model and the Johnson model. We also introduced a modification to the TTP metric computation that incorporates an additional correction for target angular size. We examined model predictions using NV-IPM default values for a critical model constant, V50, and we also considered predictions when this value was optimized to fit the behavioral data. When using default values, certain model versions produced a reasonably close fit to the human performance data in the detection task, while for the identification task all models substantially overestimated performance. When using fitted V50 values the models produced improved predictions, though the slopes of the performance functions were still shallow compared to the behavioral data. These findings are discussed in relation to the models' designs and parameters, and the characteristics of the behavioral paradigm.

Task-based detectability comparison of exponential transformation of free-response operating characteristic (EFROC) curve and channelized Hotelling observer (CHO)

NASA Astrophysics Data System (ADS)

Khobragade, P.; Fan, Jiahua; Rupcich, Franco; Crotty, Dominic J.; Gilat Schmidt, Taly

2016-03-01

This study quantitatively evaluated the performance of the exponential transformation of the free-response operating characteristic curve (EFROC) metric, with the Channelized Hotelling Observer (CHO) as a reference. The CHO has been used for image quality assessment of reconstruction algorithms and imaging systems and often it is applied to study the signal-location-known cases. The CHO also requires a large set of images to estimate the covariance matrix. In terms of clinical applications, this assumption and requirement may be unrealistic. The newly developed location-unknown EFROC detectability metric is estimated from the confidence scores reported by a model observer. Unlike the CHO, EFROC does not require a channelization step and is a non-parametric detectability metric. There are few quantitative studies available on application of the EFROC metric, most of which are based on simulation data. This study investigated the EFROC metric using experimental CT data. A phantom with four low contrast objects: 3mm (14 HU), 5mm (7HU), 7mm (5 HU) and 10 mm (3 HU) was scanned at dose levels ranging from 25 mAs to 270 mAs and reconstructed using filtered backprojection. The area under the curve values for CHO (AUC) and EFROC (AFE) were plotted with respect to different dose levels. The number of images required to estimate the non-parametric AFE metric was calculated for varying tasks and found to be less than the number of images required for parametric CHO estimation. The AFE metric was found to be more sensitive to changes in dose than the CHO metric. This increased sensitivity and the assumption of unknown signal location may be useful for investigating and optimizing CT imaging methods. Future work is required to validate the AFE metric against human observers.

Assessing colonoscopic inspection skill using a virtual withdrawal simulation: a preliminary validation of performance metrics.

PubMed

Zupanc, Christine M; Wallis, Guy M; Hill, Andrew; Burgess-Limerick, Robin; Riek, Stephan; Plooy, Annaliese M; Horswill, Mark S; Watson, Marcus O; de Visser, Hans; Conlan, David; Hewett, David G

2017-07-12

The effectiveness of colonoscopy for diagnosing and preventing colon cancer is largely dependent on the ability of endoscopists to fully inspect the colonic mucosa, which they achieve primarily through skilled manipulation of the colonoscope during withdrawal. Performance assessment during live procedures is problematic. However, a virtual withdrawal simulation can help identify and parameterise actions linked to successful inspection, and offer standardised assessments for trainees. Eleven experienced endoscopists and 18 endoscopy novices (medical students) completed a mucosal inspection task during three simulated colonoscopic withdrawals. The two groups were compared on 10 performance metrics to preliminarily assess the validity of these measures to describe inspection quality. Four metrics were related to aspects of polyp detection: percentage of polyp markers found; number of polyp markers found per minute; percentage of the mucosal surface illuminated by the colonoscope (≥0.5 s); and percentage of polyp markers illuminated (≥2.5 s) but not identified. A further six metrics described the movement of the colonoscope: withdrawal time; linear distance travelled by the colonoscope tip; total distance travelled by the colonoscope tip; and distance travelled by the colonoscope tip due to movement of the up/down angulation control, movement of the left/right angulation control, and axial shaft rotation. Statistically significant experienced-novice differences were found for 8 of the 10 performance metrics (p's < .005). Compared with novices, experienced endoscopists inspected more of the mucosa and detected more polyp markers, at a faster rate. Despite completing the withdrawals more quickly than the novices, the experienced endoscopists also moved the colonoscope more in terms of linear distance travelled and overall tip movement, with greater use of both the up/down angulation control and axial shaft rotation. However, the groups did not differ in the number of polyp markers visible on the monitor but not identified, or movement of the left/right angulation control. All metrics that yielded significant group differences had adequate to excellent internal consistency reliability (α = .79 to .90). These systematic differences confirm the potential of the simulated withdrawal task for evaluating inspection skills and strategies. It may be useful for training, and assessment of trainee competence.

Timesharing performance as an indicator of pilot mental workload

NASA Technical Reports Server (NTRS)

Casper, Patricia A.; Kantowitz, Barry H.; Sorkin, Robert D.

1988-01-01

Attentional deficits (workloads) were evaluated in a timesharing task. The results from this and other experiments were incorporated into an expert system designed to provide workload metric selection advice to non-experts in the field interested in operator workload.

Investigating the Association of Eye Gaze Pattern and Diagnostic Error in Mammography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Voisin, Sophie; Pinto, Frank M; Xu, Songhua

2013-01-01

The objective of this study was to investigate the association between eye-gaze patterns and the diagnostic accuracy of radiologists for the task of assessing the likelihood of malignancy of mammographic masses. Six radiologists (2 expert breast imagers and 4 Radiology residents of variable training) assessed the likelihood of malignancy of 40 biopsy-proven mammographic masses (20 malignant and 20 benign) on a computer monitor. Eye-gaze data were collected using a commercial remote eye-tracker. Upon reviewing each mass, the radiologists were also asked to provide their assessment regarding the probability of malignancy of the depicted mass as well as a rating regardingmore » the perceived difficulty of the diagnostic task. The collected data were analyzed using established algorithms and various quantitative metrics were extracted to characterize the recorded gaze patterns. The extracted metrics were correlated with the radiologists diagnostic decisions and perceived complexity scores. Results showed that the visual gaze pattern of radiologists varies substantially, not only depending on their experience level but also among individuals. However, some eye gaze metrics appear to correlate with diagnostic error and perceived complexity more consistently. These results suggest that although gaze patterns are generally associated with diagnostic error and the human perceived difficulty of the diagnostic task, there are substantially individual differences that are not explained simply by the experience level of the individual performing the diagnostic task.« less

Automated Neuropsychological Assessment Metrics, Version 4 (ANAM4): Examination of Select Psychometric Properties and Administration Procedures

DTIC Science & Technology

2016-12-01

2017 was approved in August 2016. The supplemental project has 2 primary objectives: • Recommend cognitive assessment tools/approaches ( toolkit ) from...strategies for use in future military-relevant environments The supplemental project has two primary deliverables: • Proposed Toolkit of cognitive...6 Vet Final Report and Cognitive performance recommendations through Steering Committee Task 7 Provide Toolkit Report 16 Months 8-12 Task 8

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

NASA Astrophysics Data System (ADS)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

Synergistic Effects on the Elderly People's Motor Control by Wearable Skin-Stretch Device Combined with Haptic Joystick

PubMed Central

Yoon, Han U.; Anil Kumar, Namita; Hur, Pilwon

2017-01-01

Cutaneous sensory feedback can be used to provide additional sensory cues to a person performing a motor task where vision is a dominant feedback signal. A haptic joystick has been widely used to guide a user by providing force feedback. However, the benefit of providing force feedback is still debatable due to performance dependency on factors such as the user's skill-level, task difficulty. Meanwhile, recent studies have shown the feasibility of improving a motor task performance by providing skin-stretch feedback. Therefore, a combination of two aforementioned feedback types is deemed to be promising to promote synergistic effects to consistently improve the person's motor performance. In this study, we aimed at identifying the effect of the combined haptic and skin-stretch feedbacks on the aged person's driving motor performance. For the experiment, 15 healthy elderly subjects (age 72.8 ± 6.6 years) were recruited and were instructed to drive a virtual power-wheelchair through four different courses with obstacles. Four augmented sensory feedback conditions were tested: no feedback, force feedback, skin-stretch feedback, and a combination of both force and skin-stretch feedbacks. While the haptic force was provided to the hand by the joystick, the skin-stretch was provided to the steering forearm by a custom-designed wearable skin-stretch device. We tested two hypotheses: (i) an elderly individual's motor control would benefit from receiving information about a desired trajectory from multiple sensory feedback sources, and (ii) the benefit does not depend on task difficulty. Various metrics related to skills and safety were used to evaluate the control performance. Repeated measure ANOVA was performed for those metrics with two factors: task scenario and the type of the augmented sensory feedback. The results revealed that elderly subjects' control performance significantly improved when the combined feedback of both haptic force and skin-stretch feedback was applied. The proposed approach suggest the feasibility to improve people's task performance by the synergistic effects of multiple augmented sensory feedback modalities. PMID:28690514

Usefulness of virtual reality in assessment of medical student laparoscopic skill.

PubMed

Matzke, Josh; Ziegler, Craig; Martin, Kevin; Crawford, Stuart; Sutton, Erica

2017-05-01

This study evaluates if undergraduate medical trainees' laparoscopic skills acquisition could be assessed using a virtual reality (VR) simulator and how the resultant metrics correlate with performance of Fundamentals of Laparoscopic Surgery (FLS) tasks. Our hypothesis is that the VR simulator metrics will correlate with passing results in a competency-based curriculum (FLS). Twenty-eight fourth-year medical students applying for surgical residency were recruited to participate in a VR training curriculum comprised of camera navigation, hand eye coordination, and FLS tasks: circle cutting (CC), ligating loop (LL), peg transfer (PT), and intracorporeal knot tying (IKT). Students were given 8 wk to achieve proficiency goals, after which they were observed performing FLS tasks. The ability of the VR simulator to detect penalties in each of the FLS tasks and correlations of time taken to complete tasks are reported. Twenty-five students trained in all components of the curriculum. All students were proficient in camera navigation and hand eye coordination tasks. Proficiency was achieved in CC, LL, PT, and IKT by 21, 19, 23, and one student, respectively. VR simulation showed high specificity for predicting zero penalties on the observed CC, LL, and PT tasks (80%, 75%, and 80%, respectively). VR can be used to assess medical student's acquisition of laparoscopic skills. The absence of penalties in the simulator reasonably predicts the absence of penalties in all FLS skills, except IKT. The skills acquired by trainees can be used in residency for further monitoring of progress toward proficiency. Copyright © 2016 Elsevier Inc. All rights reserved.

New paradigm for task switching strategies while performing multiple tasks: entropy and symbolic dynamics analysis of voluntary patterns.

PubMed

Guastello, Stephen J; Gorin, Hillary; Huschen, Samuel; Peters, Natalie E; Fabisch, Megan; Poston, Kirsten

2012-10-01

It has become well established in laboratory experiments that switching tasks, perhaps due to interruptions at work, incur costs in response time to complete the next task. Conditions are also known that exaggerate or lessen the switching costs. Although switching costs can contribute to fatigue, task switching can also be an adaptive response to fatigue. The present study introduces a new research paradigm for studying the emergence of voluntary task switching regimes, self-organizing processes therein, and the possibly conflicting roles of switching costs and minimum entropy. Fifty-four undergraduates performed 7 different computer-based cognitive tasks producing sets of 49 responses under instructional conditions requiring task quotas or no quotas. The sequences of task choices were analyzed using orbital decomposition to extract pattern types and lengths, which were then classified and compared with regard to Shannon entropy, topological entropy, number of task switches involved, and overall performance. Results indicated that similar but different patterns were generated under the two instructional conditions, and better performance was associated with lower topological entropy. Both entropy metrics were associated with the amount of voluntary task switching. Future research should explore conditions affecting the trade-off between switching costs and entropy, levels of automaticity between task elements, and the role of voluntary switching regimes on fatigue.

Person Re-Identification via Distance Metric Learning With Latent Variables.

PubMed

Sun, Chong; Wang, Dong; Lu, Huchuan

2017-01-01

In this paper, we propose an effective person re-identification method with latent variables, which represents a pedestrian as the mixture of a holistic model and a number of flexible models. Three types of latent variables are introduced to model uncertain factors in the re-identification problem, including vertical misalignments, horizontal misalignments and leg posture variations. The distance between two pedestrians can be determined by minimizing a given distance function with respect to latent variables, and then be used to conduct the re-identification task. In addition, we develop a latent metric learning method for learning the effective metric matrix, which can be solved via an iterative manner: once latent information is specified, the metric matrix can be obtained based on some typical metric learning methods; with the computed metric matrix, the latent variables can be determined by searching the state space exhaustively. Finally, extensive experiments are conducted on seven databases to evaluate the proposed method. The experimental results demonstrate that our method achieves better performance than other competing algorithms.

Force-Sensing Enhanced Simulation Environment (ForSense) for laparoscopic surgery training and assessment.

PubMed

Cundy, Thomas P; Thangaraj, Evelyn; Rafii-Tari, Hedyeh; Payne, Christopher J; Azzie, Georges; Sodergren, Mikael H; Yang, Guang-Zhong; Darzi, Ara

2015-04-01

Excessive or inappropriate tissue interaction force during laparoscopic surgery is a recognized contributor to surgical error, especially for robotic surgery. Measurement of force at the tool-tissue interface is, therefore, a clinically relevant skill assessment variable that may improve effectiveness of surgical simulation. Popular box trainer simulators lack the necessary technology to measure force. The aim of this study was to develop a force sensing unit that may be integrated easily with existing box trainer simulators and to (1) validate multiple force variables as objective measurements of laparoscopic skill, and (2) determine concurrent validity of a revised scoring metric. A base plate unit sensitized to a force transducer was retrofitted to a box trainer. Participants of 3 different levels of operative experience performed 5 repetitions of a peg transfer and suture task. Multiple outcome variables of force were assessed as well as a revised scoring metric that incorporated a penalty for force error. Mean, maximum, and overall magnitudes of force were significantly different among the 3 levels of experience, as well as force error. Experts were found to exert the least force and fastest task completion times, and vice versa for novices. Overall magnitude of force was the variable most correlated with experience level and task completion time. The revised scoring metric had similar predictive strength for experience level compared with the standard scoring metric. Current box trainer simulators can be adapted for enhanced objective measurements of skill involving force sensing. These outcomes are significantly influenced by level of expertise and are relevant to operative safety in laparoscopic surgery. Conventional proficiency standards that focus predominantly on task completion time may be integrated with force-based outcomes to be more accurately reflective of skill quality. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving Rural Emergency Medical Services (EMS) through transportation system enhancements Phase II : project brief.

DOT National Transportation Integrated Search

2015-12-01

This study used the National EMS Information System (NEMSIS) South Dakota data to develop datadriven performance metrics for EMS. Researchers used the data for three tasks: geospatial analysis of EMS events, optimization of station locations, and ser...

TOD to TTP calibration

NASA Astrophysics Data System (ADS)

Bijl, Piet; Reynolds, Joseph P.; Vos, Wouter K.; Hogervorst, Maarten A.; Fanning, Jonathan D.

2011-05-01

The TTP (Targeting Task Performance) metric, developed at NVESD, is the current standard US Army model to predict EO/IR Target Acquisition performance. This model however does not have a corresponding lab or field test to empirically assess the performance of a camera system. The TOD (Triangle Orientation Discrimination) method, developed at TNO in The Netherlands, provides such a measurement. In this study, we make a direct comparison between TOD performance for a range of sensors and the extensive historical US observer performance database built to develop and calibrate the TTP metric. The US perception data were collected doing an identification task by military personnel on a standard 12 target, 12 aspect tactical vehicle image set that was processed through simulated sensors for which the most fundamental sensor parameters such as blur, sampling, spatial and temporal noise were varied. In the present study, we measured TOD sensor performance using exactly the same sensors processing a set of TOD triangle test patterns. The study shows that good overall agreement is obtained when the ratio between target characteristic size and TOD test pattern size at threshold equals 6.3. Note that this number is purely based on empirical data without any intermediate modeling. The calibration of the TOD to the TTP is highly beneficial to the sensor modeling and testing community for a variety of reasons. These include: i) a connection between requirement specification and acceptance testing, and ii) a very efficient method to quickly validate or extend the TTP range prediction model to new systems and tasks.

The director task: A test of Theory-of-Mind use or selective attention?

PubMed

Rubio-Fernández, Paula

2017-08-01

Over two decades, the director task has increasingly been employed as a test of the use of Theory of Mind in communication, first in psycholinguistics and more recently in social cognition research. A new version of this task was designed to test two independent hypotheses. First, optimal performance in the director task, as established by the standard metrics of interference, is possible by using selective attention alone, and not necessarily Theory of Mind. Second, pragmatic measures of Theory-of-Mind use can reveal that people actively represent the director's mental states, contrary to recent claims that they only use domain-general cognitive processes to perform this task. The results of this study support both hypotheses and provide a new interactive paradigm to reliably test Theory-of-Mind use in referential communication.

Validation of a virtual reality-based robotic surgical skills curriculum.

PubMed

Connolly, Michael; Seligman, Johnathan; Kastenmeier, Andrew; Goldblatt, Matthew; Gould, Jon C

2014-05-01

The clinical application of robotic-assisted surgery (RAS) is rapidly increasing. The da Vinci Surgical System™ is currently the only commercially available RAS system. The skills necessary to perform robotic surgery are unique from those required for open and laparoscopic surgery. A validated laparoscopic surgical skills curriculum (fundamentals of laparoscopic surgery or FLS™) has transformed the way surgeons acquire laparoscopic skills. There is a need for a similar skills training and assessment tool specific for robotic surgery. Based on previously published data and expert opinion, we developed a robotic skills curriculum. We sought to evaluate this curriculum for evidence of construct validity (ability to discriminate between users of different skill levels). Four experienced surgeons (>20 RAS) and 20 novice surgeons (first-year medical students with no surgical or RAS experience) were evaluated. The curriculum comprised five tasks utilizing the da Vinci™ Skills Simulator (Pick and Place, Camera Targeting 2, Peg Board 2, Matchboard 2, and Suture Sponge 3). After an orientation to the robot and a period of acclimation in the simulator, all subjects completed three consecutive repetitions of each task. Computer-derived performance metrics included time, economy of motion, master work space, instrument collisions, excessive force, distance of instruments out of view, drops, missed targets, and overall scores (a composite of all metrics). Experienced surgeons significantly outperformed novice surgeons in most metrics. Statistically significant differences were detected for each task in regards to mean overall scores and mean time (seconds) to completion. The curriculum we propose is a valid method of assessing and distinguishing robotic surgical skill levels on the da Vinci Si™ Surgical System. Further study is needed to establish proficiency levels and to demonstrate that training on the simulator with the proposed curriculum leads to improved robotic surgical performance in the operating room.

Pitch ranking, electrode discrimination, and physiological spread of excitation using current steering in cochlear implants

PubMed Central

Goehring, Jenny L.; Neff, Donna L.; Baudhuin, Jacquelyn L.; Hughes, Michelle L.

2014-01-01

The first objective of this study was to determine whether adaptive pitch-ranking and electrode-discrimination tasks with cochlear-implant (CI) recipients produce similar results for perceiving intermediate “virtual-channel” pitch percepts using current steering. Previous studies have not examined both behavioral tasks in the same subjects with current steering. A second objective was to determine whether a physiological metric of spatial separation using the electrically evoked compound action potential spread-of-excitation (ECAP SOE) function could predict performance in the behavioral tasks. The metric was the separation index (Σ), defined as the difference in normalized amplitudes between two adjacent ECAP SOE functions, summed across all masker electrodes. Eleven CII or 90 K Advanced Bionics (Valencia, CA) recipients were tested using pairs of electrodes from the basal, middle, and apical portions of the electrode array. The behavioral results, expressed as d′, showed no significant differences across tasks. There was also no significant effect of electrode region for either task. ECAP Σ was not significantly correlated with pitch ranking or electrode discrimination for any of the electrode regions. Therefore, the ECAP separation index is not sensitive enough to predict perceptual resolution of virtual channels. PMID:25480063

Kinematics effectively delineate accomplished users of endovascular robotics with a physical training model.

PubMed

Duran, Cassidy; Estrada, Sean; O'Malley, Marcia; Lumsden, Alan B; Bismuth, Jean

2015-02-01

Endovascular robotics systems, now approved for clinical use in the United States and Europe, are seeing rapid growth in interest. Determining who has sufficient expertise for safe and effective clinical use remains elusive. Our aim was to analyze performance on a robotic platform to determine what defines an expert user. During three sessions, 21 subjects with a range of endovascular expertise and endovascular robotic experience (novices <2 hours to moderate-extensive experience with >20 hours) performed four tasks on a training model. All participants completed a 2-hour training session on the robot by a certified instructor. Completion times, global rating scores, and motion metrics were collected to assess performance. Electromagnetic tracking was used to capture and to analyze catheter tip motion. Motion analysis was based on derivations of speed and position including spectral arc length and total number of submovements (inversely proportional to proficiency of motion) and duration of submovements (directly proportional to proficiency). Ninety-eight percent of competent subjects successfully completed the tasks within the given time, whereas 91% of noncompetent subjects were successful. There was no significant difference in completion times between competent and noncompetent users except for the posterior branch (151 s:105 s; P = .01). The competent users had more efficient motion as evidenced by statistically significant differences in the metrics of motion analysis. Users with >20 hours of experience performed significantly better than those newer to the system, independent of prior endovascular experience. This study demonstrates that motion-based metrics can differentiate novice from trained users of flexible robotics systems for basic endovascular tasks. Efficiency of catheter movement, consistency of performance, and learning curves may help identify users who are sufficiently trained for safe clinical use of the system. This work will help identify the learning curve and specific movements that translate to expert robotic navigation. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Alternative Indices of Performance: An Exploration of Eye Gaze Metrics in a Visual Puzzle Task

DTIC Science & Technology

2014-07-01

strategy in which participants anchor their search on pieces in the correct positions results. Although there were significant effects for both...PERFORMANCE WING, HUMAN EFFECTIVENESS DIRECTORATE, WRIGHT-PATTERSON AIR FORCE BASE, OH 45433 AIR FORCE MATERIEL COMMAND UNITED STATES AIR FORCE...Interface Division //signed// WILLIAM E. RUSSELL Chief, Warfighter Interface Division Human Effectiveness Directorate 711 Human Performance

Automated Support for da Vinci Surgical System

DTIC Science & Technology

2011-05-01

MScore, which provides objective assessment measuring robotic surgery skills across all computed metrics (Figure 7). In addition to viewing single ...holding an object. Data Collection & Analysis (Task 5)  Preliminary Experiments  During the first phase of data collection, a single performance of...a single task (anastomosis) trial was recorded from six different users – three each for the da Vinci and the dV-Trainer platforms. On each platform

Speech intelligibility index predictions for young and old listeners in automobile noise: Can the index be improved by incorporating factors other than absolute threshold?

NASA Astrophysics Data System (ADS)

Saweikis, Meghan; Surprenant, Aimée M.; Davies, Patricia; Gallant, Don

2003-10-01

While young and old subjects with comparable audiograms tend to perform comparably on speech recognition tasks in quiet environments, the older subjects have more difficulty than the younger subjects with recognition tasks in degraded listening conditions. This suggests that factors other than an absolute threshold may account for some of the difficulty older listeners have on recognition tasks in noisy environments. Many metrics, including the Speech Intelligibility Index (SII), used to measure speech intelligibility, only consider an absolute threshold when accounting for age related hearing loss. Therefore these metrics tend to overestimate the performance for elderly listeners in noisy environments [Tobias et al., J. Acoust. Soc. Am. 83, 859-895 (1988)]. The present studies examine the predictive capabilities of the SII in an environment with automobile noise present. This is of interest because people's evaluation of the automobile interior sound is closely linked to their ability to carry on conversations with their fellow passengers. The four studies examine whether, for subjects with age related hearing loss, the accuracy of the SII can be improved by incorporating factors other than an absolute threshold into the model. [Work supported by Ford Motor Company.

A Comparison of Robotic Simulation Performance on Basic Virtual Reality Skills: Simulator Subjective Versus Objective Assessment Tools.

PubMed

Dubin, Ariel K; Smith, Roger; Julian, Danielle; Tanaka, Alyssa; Mattingly, Patricia

To answer the question of whether there is a difference between robotic virtual reality simulator performance assessment and validated human reviewers. Current surgical education relies heavily on simulation. Several assessment tools are available to the trainee, including the actual robotic simulator assessment metrics and the Global Evaluative Assessment of Robotic Skills (GEARS) metrics, both of which have been independently validated. GEARS is a rating scale through which human evaluators can score trainees' performances on 6 domains: depth perception, bimanual dexterity, efficiency, force sensitivity, autonomy, and robotic control. Each domain is scored on a 5-point Likert scale with anchors. We used 2 common robotic simulators, the dV-Trainer (dVT; Mimic Technologies Inc., Seattle, WA) and the da Vinci Skills Simulator (dVSS; Intuitive Surgical, Sunnyvale, CA), to compare the performance metrics of robotic surgical simulators with the GEARS for a basic robotic task on each simulator. A prospective single-blinded randomized study. A surgical education and training center. Surgeons and surgeons in training. Demographic information was collected including sex, age, level of training, specialty, and previous surgical and simulator experience. Subjects performed 2 trials of ring and rail 1 (RR1) on each of the 2 simulators (dVSS and dVT) after undergoing randomization and warm-up exercises. The second RR1 trial simulator performance was recorded, and the deidentified videos were sent to human reviewers using GEARS. Eight different simulator assessment metrics were identified and paired with a similar performance metric in the GEARS tool. The GEARS evaluation scores and simulator assessment scores were paired and a Spearman rho calculated for their level of correlation. Seventy-four subjects were enrolled in this randomized study with 9 subjects excluded for missing or incomplete data. There was a strong correlation between the GEARS score and the simulator metric score for time to complete versus efficiency, time to complete versus total score, economy of motion versus depth perception, and overall score versus total score with rho coefficients greater than or equal to 0.70; these were significant (p < .0001). Those with weak correlation (rho ≥0.30) were bimanual dexterity versus economy of motion, efficiency versus master workspace range, bimanual dexterity versus master workspace range, and robotic control versus instrument collisions. On basic VR tasks, several simulator metrics are well matched with GEARS scores assigned by human reviewers, but others are not. Identifying these matches/mismatches can improve the training and assessment process when using robotic surgical simulators. Copyright © 2017 American Association of Gynecologic Laparoscopists. Published by Elsevier Inc. All rights reserved.

Investigation of human-robot interface performance in household environments

NASA Astrophysics Data System (ADS)

Cremer, Sven; Mirza, Fahad; Tuladhar, Yathartha; Alonzo, Rommel; Hingeley, Anthony; Popa, Dan O.

2016-05-01

Today, assistive robots are being introduced into human environments at an increasing rate. Human environments are highly cluttered and dynamic, making it difficult to foresee all necessary capabilities and pre-program all desirable future skills of the robot. One approach to increase robot performance is semi-autonomous operation, allowing users to intervene and guide the robot through difficult tasks. To this end, robots need intuitive Human-Machine Interfaces (HMIs) that support fine motion control without overwhelming the operator. In this study we evaluate the performance of several interfaces that balance autonomy and teleoperation of a mobile manipulator for accomplishing several household tasks. Our proposed HMI framework includes teleoperation devices such as a tablet, as well as physical interfaces in the form of piezoresistive pressure sensor arrays. Mobile manipulation experiments were performed with a sensorized KUKA youBot, an omnidirectional platform with a 5 degrees of freedom (DOF) arm. The pick and place tasks involved navigation and manipulation of objects in household environments. Performance metrics included time for task completion and position accuracy.

Colonoscopy Quality: Metrics and Implementation

PubMed Central

Calderwood, Audrey H.; Jacobson, Brian C.

2013-01-01

Synopsis Colonoscopy is an excellent area for quality improvement 1 because it is high volume, has significant associated risk and expense, and there is evidence that variability in its performance affects outcomes. The best endpoint for validation of quality metrics in colonoscopy is colorectal cancer incidence and mortality, but because of feasibility issues, a more readily accessible metric is the adenoma detection rate (ADR). Fourteen quality metrics were proposed by the joint American Society of Gastrointestinal Endoscopy/American College of Gastroenterology Task Force on “Quality Indicators for Colonoscopy” in 2006, which are described in further detail below. Use of electronic health records and quality-oriented registries will facilitate quality measurement and reporting. Unlike traditional clinical research, implementation of quality improvement initiatives involves rapid assessments and changes on an iterative basis, and can be done at the individual, group, or facility level. PMID:23931862

Monitoring cognitive and emotional processes through pupil and cardiac response during dynamic versus logical task.

PubMed

Causse, Mickaël; Sénard, Jean-Michel; Démonet, Jean François; Pastor, Josette

2010-06-01

The paper deals with the links between physiological measurements and cognitive and emotional functioning. As long as the operator is a key agent in charge of complex systems, the definition of metrics able to predict his performance is a great challenge. The measurement of the physiological state is a very promising way but a very acute comprehension is required; in particular few studies compare autonomous nervous system reactivity according to specific cognitive processes during task performance and task related psychological stress is often ignored. We compared physiological parameters recorded on 24 healthy subjects facing two neuropsychological tasks: a dynamic task that require problem solving in a world that continually evolves over time and a logical task representative of cognitive processes performed by operators facing everyday problem solving. Results showed that the mean pupil diameter change was higher during the dynamic task; conversely, the heart rate was more elevated during the logical task. Finally, the systolic blood pressure seemed to be strongly sensitive to psychological stress. A better taking into account of the precise influence of a given cognitive activity and both workload and related task-induced psychological stress during task performance is a promising way to better monitor operators in complex working situations to detect mental overload or pejorative stress factor of error.

Early brain connectivity alterations and cognitive impairment in a rat model of Alzheimer's disease.

PubMed

Muñoz-Moreno, Emma; Tudela, Raúl; López-Gil, Xavier; Soria, Guadalupe

2018-02-07

Animal models of Alzheimer's disease (AD) are essential to understanding the disease progression and to development of early biomarkers. Because AD has been described as a disconnection syndrome, magnetic resonance imaging (MRI)-based connectomics provides a highly translational approach to characterizing the disruption in connectivity associated with the disease. In this study, a transgenic rat model of AD (TgF344-AD) was analyzed to describe both cognitive performance and brain connectivity at an early stage (5 months of age) before a significant concentration of β-amyloid plaques is present. Cognitive abilities were assessed by a delayed nonmatch-to-sample (DNMS) task preceded by a training phase where the animals learned the task. The number of training sessions required to achieve a learning criterion was recorded and evaluated. After DNMS, MRI acquisition was performed, including diffusion-weighted MRI and resting-state functional MRI, which were processed to obtain the structural and functional connectomes, respectively. Global and regional graph metrics were computed to evaluate network organization in both transgenic and control rats. The results pointed to a delay in learning the working memory-related task in the AD rats, which also completed a lower number of trials in the DNMS task. Regarding connectivity properties, less efficient organization of the structural brain networks of the transgenic rats with respect to controls was observed. Specific regional differences in connectivity were identified in both structural and functional networks. In addition, a strong correlation was observed between cognitive performance and brain networks, including whole-brain structural connectivity as well as functional and structural network metrics of regions related to memory and reward processes. In this study, connectivity and neurocognitive impairments were identified in TgF344-AD rats at a very early stage of the disease when most of the pathological hallmarks have not yet been detected. Structural and functional network metrics of regions related to reward, memory, and sensory performance were strongly correlated with the cognitive outcome. The use of animal models is essential for the early identification of these alterations and can contribute to the development of early biomarkers of the disease based on MRI connectomics.

Variability in spatio-temporal pattern of trapezius activity and coordination of hand-arm muscles during a sustained repetitive dynamic task.

PubMed

Samani, Afshin; Srinivasan, Divya; Mathiassen, Svend Erik; Madeleine, Pascal

2017-02-01

The spatio-temporal distribution of muscle activity has been suggested to be a determinant of fatigue development. Pursuing this hypothesis, we investigated the pattern of muscular activity in the shoulder and arm during a repetitive dynamic task performed until participants' rating of perceived exertion reached 8 on Borg's CR-10 scale. We collected high-density surface electromyogram (HD-EMG) over the upper trapezius, as well as bipolar EMG from biceps brachii, triceps brachii, deltoideus anterior, serratus anterior, upper and lower trapezius from 21 healthy women. Root-mean-square (RMS) and mean power frequency (MNF) were calculated for all EMG signals. The barycenter of RMS values over the HD-EMG grid was also determined, as well as normalized mutual information (NMI) for each pair of muscles. Cycle-to-cycle variability of these metrics was also assessed. With time, EMG RMS increased for most of the muscles, and MNF decreased. Trapezius activity became higher on the lateral side than on the medial side of the HD-EMG grid and the barycenter moved in a lateral direction. NMI between muscle pairs increased with time while its variability decreased. The variability of the metrics during the initial 10 % of task performance was not associated with the time to task termination. Our results suggest that the considerable variability in force and posture contained in the dynamic task per se masks any possible effects of differences between subjects in initial motor variability on the rate of fatigue development.

Integrated Resilient Aircraft Control Project Full Scale Flight Validation

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2009-01-01

Objective: Provide validation of adaptive control law concepts through full scale flight evaluation. Technical Approach: a) Engage failure mode - destabilizing or frozen surface. b) Perform formation flight and air-to-air tracking tasks. Evaluate adaptive algorithm: a) Stability metrics. b) Model following metrics. Full scale flight testing provides an ability to validate different adaptive flight control approaches. Full scale flight testing adds credence to NASA's research efforts. A sustained research effort is required to remove the road blocks and provide adaptive control as a viable design solution for increased aircraft resilience.

Evaluation of a mobile augmented reality application for image guidance of neurosurgical interventions.

PubMed

Kramers, Matthew; Armstrong, Ryan; Bakhshmand, Saeed M; Fenster, Aaron; de Ribaupierre, Sandrine; Eagleson, Roy

2014-01-01

Image guidance can provide surgeons with valuable contextual information during a medical intervention. Often, image guidance systems require considerable infrastructure, setup-time, and operator experience to be utilized. Certain procedures performed at bedside are susceptible to navigational errors that can lead to complications. We present an application for mobile devices that can provide image guidance using augmented reality to assist in performing neurosurgical tasks. A methodology is outlined that evaluates this mode of visualization from the standpoint of perceptual localization, depth estimation, and pointing performance, in scenarios derived from a neurosurgical targeting task. By measuring user variability and speed we can report objective metrics of performance for our augmented reality guidance system.

Grounding Undns

DTIC Science & Technology

2012-01-01

PROJECT NUMBER BYU1 5e. TASK NUMBER MA 5f. WORK UNIT NUMBER RY 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of Maryland Office of...Research Administration & Advancement College Park MD 20742-5100 8. PERFORMING ORGANIZATION REPORT NUMBER N/A 9. SPONSORING...Armed with these metrics, the Undns ruleset is better revised, vestigial rules removed or demoted for maintenance, and redundant locations distinguished

White Matter Microstructural Abnormalities in Type 2 Diabetes Mellitus: A Diffusional Kurtosis Imaging Analysis.

PubMed

Xie, Y; Zhang, Y; Qin, W; Lu, S; Ni, C; Zhang, Q

2017-03-01

Increasing DTI studies have demonstrated that white matter microstructural abnormalities play an important role in type 2 diabetes mellitus-related cognitive impairment. In this study, the diffusional kurtosis imaging method was used to investigate WM microstructural alterations in patients with type 2 diabetes mellitus and to detect associations between diffusional kurtosis imaging metrics and clinical/cognitive measurements. Diffusional kurtosis imaging and cognitive assessments were performed on 58 patients with type 2 diabetes mellitus and 58 controls. Voxel-based intergroup comparisons of diffusional kurtosis imaging metrics were conducted, and ROI-based intergroup comparisons were further performed. Correlations between the diffusional kurtosis imaging metrics and cognitive/clinical measurements were assessed after controlling for age, sex, and education in both patients and controls. Altered diffusion metrics were observed in the corpus callosum, the bilateral frontal WM, the right superior temporal WM, the left external capsule, and the pons in patients with type 2 diabetes mellitus compared with controls. The splenium of the corpus callosum and the pons had abnormal kurtosis metrics in patients with type 2 diabetes mellitus. Additionally, altered diffusion metrics in the right prefrontal WM were significantly correlated with disease duration and attention task performance in patients with type 2 diabetes mellitus. With both conventional diffusion and additional kurtosis metrics, diffusional kurtosis imaging can provide additional information on WM microstructural abnormalities in patients with type 2 diabetes mellitus. Our results indicate that WM microstructural abnormalities occur before cognitive decline and may be used as neuroimaging markers for predicting the early cognitive impairment in patients with type 2 diabetes mellitus. © 2017 by American Journal of Neuroradiology.

Demand curves for hypothetical cocaine in cocaine-dependent individuals.

PubMed

Bruner, Natalie R; Johnson, Matthew W

2014-03-01

Drug purchasing tasks have been successfully used to examine demand for hypothetical consumption of abused drugs including heroin, nicotine, and alcohol. In these tasks, drug users make hypothetical choices whether to buy drugs, and if so, at what quantity, at various potential prices. These tasks allow for behavioral economic assessment of that drug's intensity of demand (preferred level of consumption at extremely low prices) and demand elasticity (sensitivity of consumption to price), among other metrics. However, a purchasing task for cocaine in cocaine-dependent individuals has not been investigated. This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data. Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use. Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and O max (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, P max, were significantly correlated with real-world cocaine use. Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use.

Development of Management Metrics for Research and Technology

NASA Technical Reports Server (NTRS)

Sheskin, Theodore J.

2003-01-01

Professor Ted Sheskin from CSU will be tasked to research and investigate metrics that can be used to determine the technical progress for advanced development and research tasks. These metrics will be implemented in a software environment that hosts engineering design, analysis and management tools to be used to support power system and component research work at GRC. Professor Sheskin is an Industrial Engineer and has been involved in issues related to management of engineering tasks and will use his knowledge from this area to allow extrapolation into the research and technology management area. Over the course of the summer, Professor Sheskin will develop a bibliography of management papers covering current management methods that may be applicable to research management. At the completion of the summer work we expect to have him recommend a metric system to be reviewed prior to implementation in the software environment. This task has been discussed with Professor Sheskin and some review material has already been given to him.

Optimal Modality Selection for Cooperative Human-Robot Task Completion.

PubMed

Jacob, Mithun George; Wachs, Juan P

2016-12-01

Human-robot cooperation in complex environments must be fast, accurate, and resilient. This requires efficient communication channels where robots need to assimilate information using a plethora of verbal and nonverbal modalities such as hand gestures, speech, and gaze. However, even though hybrid human-robot communication frameworks and multimodal communication have been studied, a systematic methodology for designing multimodal interfaces does not exist. This paper addresses the gap by proposing a novel methodology to generate multimodal lexicons which maximizes multiple performance metrics over a wide range of communication modalities (i.e., lexicons). The metrics are obtained through a mixture of simulation and real-world experiments. The methodology is tested in a surgical setting where a robot cooperates with a surgeon to complete a mock abdominal incision and closure task by delivering surgical instruments. Experimental results show that predicted optimal lexicons significantly outperform predicted suboptimal lexicons (p <; 0.05) in all metrics validating the predictability of the methodology. The methodology is validated in two scenarios (with and without modeling the risk of a human-robot collision) and the differences in the lexicons are analyzed.

Automated Neuropsychological assessment Metrics Version 4 (ANAM4): Select Psychometric Properties and Administration Procedures

DTIC Science & Technology

2014-12-01

management structure set up for Study 4 - COMPLETED Task 17 (Months 37-48) Operationalize database for Study 4 analysis scheme – COMPLETED Task...Heaton, K.J., Laufer, A.S., Maule, A., Vincent, A.S. (abstract submitted). Effects of acute sleep deprivation on ANAM4 TBI Battery performance in...and visual tracking degradation during acute sleep deprivation in a military sample. Aviat Space Environ Med 2014; 85:497 – 503. Background: Fatigue

Beyond the hype: deep neural networks outperform established methods using a ChEMBL bioactivity benchmark set.

PubMed

Lenselink, Eelke B; Ten Dijke, Niels; Bongers, Brandon; Papadatos, George; van Vlijmen, Herman W T; Kowalczyk, Wojtek; IJzerman, Adriaan P; van Westen, Gerard J P

2017-08-14

The increase of publicly available bioactivity data in recent years has fueled and catalyzed research in chemogenomics, data mining, and modeling approaches. As a direct result, over the past few years a multitude of different methods have been reported and evaluated, such as target fishing, nearest neighbor similarity-based methods, and Quantitative Structure Activity Relationship (QSAR)-based protocols. However, such studies are typically conducted on different datasets, using different validation strategies, and different metrics. In this study, different methods were compared using one single standardized dataset obtained from ChEMBL, which is made available to the public, using standardized metrics (BEDROC and Matthews Correlation Coefficient). Specifically, the performance of Naïve Bayes, Random Forests, Support Vector Machines, Logistic Regression, and Deep Neural Networks was assessed using QSAR and proteochemometric (PCM) methods. All methods were validated using both a random split validation and a temporal validation, with the latter being a more realistic benchmark of expected prospective execution. Deep Neural Networks are the top performing classifiers, highlighting the added value of Deep Neural Networks over other more conventional methods. Moreover, the best method ('DNN_PCM') performed significantly better at almost one standard deviation higher than the mean performance. Furthermore, Multi-task and PCM implementations were shown to improve performance over single task Deep Neural Networks. Conversely, target prediction performed almost two standard deviations under the mean performance. Random Forests, Support Vector Machines, and Logistic Regression performed around mean performance. Finally, using an ensemble of DNNs, alongside additional tuning, enhanced the relative performance by another 27% (compared with unoptimized 'DNN_PCM'). Here, a standardized set to test and evaluate different machine learning algorithms in the context of multi-task learning is offered by providing the data and the protocols. Graphical Abstract .

On the correlation between reservoir metrics and performance for time series classification under the influence of synaptic plasticity.

PubMed

Chrol-Cannon, Joseph; Jin, Yaochu

2014-01-01

Reservoir computing provides a simpler paradigm of training recurrent networks by initialising and adapting the recurrent connections separately to a supervised linear readout. This creates a problem, though. As the recurrent weights and topology are now separated from adapting to the task, there is a burden on the reservoir designer to construct an effective network that happens to produce state vectors that can be mapped linearly into the desired outputs. Guidance in forming a reservoir can be through the use of some established metrics which link a number of theoretical properties of the reservoir computing paradigm to quantitative measures that can be used to evaluate the effectiveness of a given design. We provide a comprehensive empirical study of four metrics; class separation, kernel quality, Lyapunov's exponent and spectral radius. These metrics are each compared over a number of repeated runs, for different reservoir computing set-ups that include three types of network topology and three mechanisms of weight adaptation through synaptic plasticity. Each combination of these methods is tested on two time-series classification problems. We find that the two metrics that correlate most strongly with the classification performance are Lyapunov's exponent and kernel quality. It is also evident in the comparisons that these two metrics both measure a similar property of the reservoir dynamics. We also find that class separation and spectral radius are both less reliable and less effective in predicting performance.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

Value of Frequency Domain Resting-State Functional Magnetic Resonance Imaging Metrics Amplitude of Low-Frequency Fluctuation and Fractional Amplitude of Low-Frequency Fluctuation in the Assessment of Brain Tumor-Induced Neurovascular Uncoupling.

PubMed

Agarwal, Shruti; Lu, Hanzhang; Pillai, Jay J

2017-08-01

The aim of this study was to explore whether the phenomenon of brain tumor-related neurovascular uncoupling (NVU) in resting-state blood oxygen level-dependent functional magnetic resonance imaging (BOLD fMRI) (rsfMRI) may also affect the resting-state fMRI (rsfMRI) frequency domain metrics the amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). Twelve de novo brain tumor patients, who underwent clinical fMRI examinations, including task-based fMRI (tbfMRI) and rsfMRI, were included in this Institutional Review Board-approved study. Each patient displayed decreased/absent tbfMRI activation in the primary ipsilesional (IL) sensorimotor cortex in the absence of a corresponding motor deficit or suboptimal task performance, consistent with NVU. Z-score maps for the motor tasks were obtained from general linear model analysis (reflecting motor activation vs. rest). Seed-based correlation analysis (SCA) maps of sensorimotor network, ALFF, and fALFF were calculated from rsfMRI data. Precentral and postcentral gyri in contralesional (CL) and IL hemispheres were parcellated using an automated anatomical labeling template for each patient. Region of interest (ROI) analysis was performed on four maps: tbfMRI, SCA, ALFF, and fALFF. Voxel values in the CL and IL ROIs of each map were divided by the corresponding global mean of ALFF and fALFF in the cortical brain tissue. Group analysis revealed significantly decreased IL ALFF (p = 0.02) and fALFF (p = 0.03) metrics compared with CL ROIs, consistent with similar findings of significantly decreased IL BOLD signal for tbfMRI (p = 0.0005) and SCA maps (p = 0.0004). The frequency domain metrics ALFF and fALFF may be markers of lesion-induced NVU in rsfMRI similar to previously reported alterations in tbfMRI activation and SCA-derived resting-state functional connectivity maps.

Does video gaming affect orthopaedic skills acquisition? A prospective cohort-study.

PubMed

Khatri, Chetan; Sugand, Kapil; Anjum, Sharika; Vivekanantham, Sayinthen; Akhtar, Kash; Gupte, Chinmay

2014-01-01

Previous studies have suggested that there is a positive correlation between the extent of video gaming and efficiency of surgical skill acquisition on laparoscopic and endovascular surgical simulators amongst trainees. However, the link between video gaming and orthopaedic trauma simulation remains unexamined, in particular dynamic hip screw (DHS) stimulation. To assess effect of prior video gaming experience on virtual-reality (VR) haptic-enabled DHS simulator performance. 38 medical students, naïve to VR surgical simulation, were recruited and stratified relative to their video gaming exposure. Group 1 (n = 19, video-gamers) were defined as those who play more than one hour per day in the last calendar year. Group 2 (n = 19, non-gamers) were defined as those who play video games less than one hour per calendar year. Both cohorts performed five attempts on completing a VR DHS procedure and repeated the task after a week. Metrics assessed included time taken for task, simulated flouroscopy time and screw position. Median and Bonett-Price 95% confidence intervals were calculated for seven real-time objective performance metrics. Data was confirmed as non-parametric by the Kolmogorov-Smirnov test. Analysis was performed using the Mann-Whitney U test for independent data whilst the Wilcoxon signed ranked test was used for paired data. A result was deemed significant when a two-tailed p-value was less than 0.05. All 38 subjects completed the study. The groups were not significantly different at baseline. After ten attempts, there was no difference between Group 1 and Group 2 in any of the metrics tested. These included time taken for task, simulated fluoroscopy time, number of retries, tip-apex distance, percentage cut-out and global score. Contrary to previous literature findings, there was no correlation between video gaming experience and gaining competency on a VR DHS simulator.

Proof of Concept Study: Investigating Force Metrics of an Intracorporeal Suturing Knot Task.

PubMed

Wee, Justin; Azzie, Georges; Drake, James; Gerstle, J Ted

2018-06-19

Mastering proper force manipulation in minimally invasive surgery can take many hours of practice and training. Improper force control can lead to necrosis, infection, and scarring. A force-sensing skin (FSS) has been developed, which measures forces at the distal end of minimal access surgeries' (MAS) instruments without altering the instrument's structural integrity or the surgical workflow, and acts as a minimally disruptive add-on to any MAS instrument. A proof of concept study was conducted using a FSS-equipped 5 mm straight-tip needle holder. Participants (n = 19: 3 novices, 11 fellows, and 5 staff surgeons) performed one intracorporeal suturing knot task (ISKT). Using participant task video footage, each participant's two puncture forces (each wall of the Penrose drain) and three knot tightening forces were measured. Force metrics from the three expertise groups were compared using analysis of variance (ANOVA) and Tukey's honest significance test with statistical significance assessed at P < .05. Preliminary ISKT force metric data showed differences between novices and more experienced fellows and surgeons. Of the five stages of the ISKT evaluated, the first puncture force of the Penrose drain seemed to best reflect the difference in skill among participants. The study demonstrated ISKT knot tightening and puncture force ranges across three expertise levels (novices, surgical fellows, and staff surgeons) of 0.586 to 6.089 newtons (N) and 0.852 to 2.915 N, respectively. The investigation of force metrics is important for the implementation of future force feedback systems as it can provide real-time information to surgeons in training and the operating theater.

A Comparison of Evaluation Metrics for Biomedical Journals, Articles, and Websites in Terms of Sensitivity to Topic

PubMed Central

Fu, Lawrence D.; Aphinyanaphongs, Yindalon; Wang, Lily; Aliferis, Constantin F.

2011-01-01

Evaluating the biomedical literature and health-related websites for quality are challenging information retrieval tasks. Current commonly used methods include impact factor for journals, PubMed’s clinical query filters and machine learning-based filter models for articles, and PageRank for websites. Previous work has focused on the average performance of these methods without considering the topic, and it is unknown how performance varies for specific topics or focused searches. Clinicians, researchers, and users should be aware when expected performance is not achieved for specific topics. The present work analyzes the behavior of these methods for a variety of topics. Impact factor, clinical query filters, and PageRank vary widely across different topics while a topic-specific impact factor and machine learning-based filter models are more stable. The results demonstrate that a method may perform excellently on average but struggle when used on a number of narrower topics. Topic adjusted metrics and other topic robust methods have an advantage in such situations. Users of traditional topic-sensitive metrics should be aware of their limitations. PMID:21419864

Face and Construct Validation of a Virtual Peg Transfer Simulator

PubMed Central

Arikatla, Venkata S; Sankaranarayanan, Ganesh; Ahn, Woojin; Chellali, Amine; De, Suvranu; Caroline, GL; Hwabejire, John; DeMoya, Marc; Schwaitzberg, Steven; Jones, Daniel B.

2013-01-01

Background The Fundamentals of Laparascopic Surgery (FLS) trainer box is now established as a standard for evaluating minimally invasive surgical skills. A particularly simple task in this trainer box is the peg transfer task which is aimed at testing the surgeon’s bimanual dexterity, hand-eye coordination, speed and precision. The Virtual Basic Laparoscopic Skill Trainer (VBLaST©) is a virtual version of the FLS tasks which allows automatic scoring and real time, subjective quantification of performance without the need of a human proctor. In this paper we report validation studies of the VBLaST© peg transfer (VBLaST-PT©) simulator. Methods Thirty-five subjects with medical background were divided into two groups: experts (PGY 4-5, fellows and practicing surgeons) and novices (PGY 1-3). The subjects were asked to perform the peg transfer task on both the FLS trainer box and the VBLaST-PT© simulator and their performance was evaluated based on established metrics of error and time. A new length of trajectory (LOT) metric has also been introduced for offline analysis. A questionnaire was used to rate the realism of the virtual system on a 5-point Likert scale. Results Preliminary face validation of the VBLaST-PT© with 34 subjects rated on a 5-point Likert scale questionnaire revealed high scores for all aspects of simulation, with 3.53 being the lowest mean score across all questions. A two-tailed Mann-Whitney performed on the total scores showed significant (p=0.001) difference between the groups. A similar test performed on the task time (p=0.002) and the length of trajectory (p=0.004) separately showed statistically significant differences between the experts and novice groups (p<0.05). The experts appear to be traversing shorter overall trajectories in less time than the novices. Conclusion VBLaST-PT© showed both face and construct validity and has promise as a substitute for the FLS to training peg transfer skills. PMID:23263645

Evaluation of cassette-based digital radiography detectors using standardized image quality metrics: AAPM TG-150 Draft Image Detector Tests.

PubMed

Li, Guang; Greene, Travis C; Nishino, Thomas K; Willis, Charles E

2016-09-08

The purpose of this study was to evaluate several of the standardized image quality metrics proposed by the American Association of Physics in Medicine (AAPM) Task Group 150. The task group suggested region-of-interest (ROI)-based techniques to measure nonuniformity, minimum signal-to-noise ratio (SNR), number of anomalous pixels, and modulation transfer function (MTF). This study evaluated the effects of ROI size and layout on the image metrics by using four different ROI sets, assessed result uncertainty by repeating measurements, and compared results with two commercially available quality control tools, namely the Carestream DIRECTVIEW Total Quality Tool (TQT) and the GE Healthcare Quality Assurance Process (QAP). Seven Carestream DRX-1C (CsI) detectors on mobile DR systems and four GE FlashPad detectors in radiographic rooms were tested. Images were analyzed using MATLAB software that had been previously validated and reported. Our values for signal and SNR nonuniformity and MTF agree with values published by other investigators. Our results show that ROI size affects nonuniformity and minimum SNR measurements, but not detection of anomalous pixels. Exposure geometry affects all tested image metrics except for the MTF. TG-150 metrics in general agree with the TQT, but agree with the QAP only for local and global signal nonuniformity. The difference in SNR nonuniformity and MTF values between the TG-150 and QAP may be explained by differences in the calculation of noise and acquisition beam quality, respectively. TG-150's SNR nonuniformity metrics are also more sensitive to detector nonuniformity compared to the QAP. Our results suggest that fixed ROI size should be used for consistency because nonuniformity metrics depend on ROI size. Ideally, detector tests should be performed at the exact calibration position. If not feasible, a baseline should be established from the mean of several repeated measurements. Our study indicates that the TG-150 tests can be used as an independent standardized procedure for detector performance assessment. © 2016 The Authors.

Evaluation of cassette‐based digital radiography detectors using standardized image quality metrics: AAPM TG‐150 Draft Image Detector Tests

PubMed Central

Greene, Travis C.; Nishino, Thomas K.; Willis, Charles E.

2016-01-01

The purpose of this study was to evaluate several of the standardized image quality metrics proposed by the American Association of Physics in Medicine (AAPM) Task Group 150. The task group suggested region‐of‐interest (ROI)‐based techniques to measure nonuniformity, minimum signal‐to‐noise ratio (SNR), number of anomalous pixels, and modulation transfer function (MTF). This study evaluated the effects of ROI size and layout on the image metrics by using four different ROI sets, assessed result uncertainty by repeating measurements, and compared results with two commercially available quality control tools, namely the Carestream DIRECTVIEW Total Quality Tool (TQT) and the GE Healthcare Quality Assurance Process (QAP). Seven Carestream DRX‐1C (CsI) detectors on mobile DR systems and four GE FlashPad detectors in radiographic rooms were tested. Images were analyzed using MATLAB software that had been previously validated and reported. Our values for signal and SNR nonuniformity and MTF agree with values published by other investigators. Our results show that ROI size affects nonuniformity and minimum SNR measurements, but not detection of anomalous pixels. Exposure geometry affects all tested image metrics except for the MTF. TG‐150 metrics in general agree with the TQT, but agree with the QAP only for local and global signal nonuniformity. The difference in SNR nonuniformity and MTF values between the TG‐150 and QAP may be explained by differences in the calculation of noise and acquisition beam quality, respectively. TG‐150's SNR nonuniformity metrics are also more sensitive to detector nonuniformity compared to the QAP. Our results suggest that fixed ROI size should be used for consistency because nonuniformity metrics depend on ROI size. Ideally, detector tests should be performed at the exact calibration position. If not feasible, a baseline should be established from the mean of several repeated measurements. Our study indicates that the TG‐150 tests can be used as an independent standardized procedure for detector performance assessment. PACS number(s): 87.57.‐s, 87.57.C PMID:27685102

Comparison of task-based exposure metrics for an epidemiologic study of isocyanate inhalation exposures among autobody shop workers.

PubMed

Woskie, Susan R; Bello, Dhimiter; Gore, Rebecca J; Stowe, Meredith H; Eisen, Ellen A; Liu, Youcheng; Sparer, Judy A; Redlich, Carrie A; Cullen, Mark R

2008-09-01

Because many occupational epidemiologic studies use exposure surrogates rather than quantitative exposure metrics, the UMass Lowell and Yale study of autobody shop workers provided an opportunity to evaluate the relative utility of surrogates and quantitative exposure metrics in an exposure response analysis of cross-week change in respiratory function. A task-based exposure assessment was used to develop several metrics of inhalation exposure to isocyanates. The metrics included the surrogates, job title, counts of spray painting events during the day, counts of spray and bystander exposure events, and a quantitative exposure metric that incorporated exposure determinant models based on task sampling and a personal workplace protection factor for respirator use, combined with a daily task checklist. The result of the quantitative exposure algorithm was an estimate of the daily time-weighted average respirator-corrected total NCO exposure (microg/m(3)). In general, these four metrics were found to be variable in agreement using measures such as weighted kappa and Spearman correlation. A logistic model for 10% drop in FEV(1) from Monday morning to Thursday morning was used to evaluate the utility of each exposure metric. The quantitative exposure metric was the most favorable, producing the best model fit, as well as the greatest strength and magnitude of association. This finding supports the reports of others that reducing exposure misclassification can improve risk estimates that otherwise would be biased toward the null. Although detailed and quantitative exposure assessment can be more time consuming and costly, it can improve exposure-disease evaluations and is more useful for risk assessment purposes. The task-based exposure modeling method successfully produced estimates of daily time-weighted average exposures in the complex and changing autobody shop work environment. The ambient TWA exposures of all of the office workers and technicians and 57% of the painters were found to be below the current U.K. Health and Safety Executive occupational exposure limit (OEL) for total NCO of 20 microg/m(3). When respirator use was incorporated, all personal daily exposures were below the U.K. OEL.

Measuring Overcast Colors with All-Sky Imaging

DTIC Science & Technology

2008-04-01

NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) United States Naval Academy (USNA),Mathematics...Science Department,Annapolis,MD,21402 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) 10. SPONSOR...are vestigial (29 No- vember 2006 curve). A few overcasts are bluest near the horizon, and this causes particularly large colori- metric excursions

Can a virtual reality surgical simulation training provide a self-driven and mentor-free skills learning? Investigation of the practical influence of the performance metrics from the virtual reality robotic surgery simulator on the skill learning and associated cognitive workloads.

PubMed

Lee, Gyusung I; Lee, Mija R

2018-01-01

While it is often claimed that virtual reality (VR) training system can offer self-directed and mentor-free skill learning using the system's performance metrics (PM), no studies have yet provided evidence-based confirmation. This experimental study investigated what extent to which trainees achieved their self-learning with a current VR simulator and whether additional mentoring improved skill learning, skill transfer and cognitive workloads in robotic surgery simulation training. Thirty-two surgical trainees were randomly assigned to either the Control-Group (CG) or Experiment-Group (EG). While the CG participants reviewed the PM at their discretion, the EG participants had explanations about PM and instructions on how to improve scores. Each subject completed a 5-week training using four simulation tasks. Pre- and post-training data were collected using both a simulator and robot. Peri-training data were collected after each session. Skill learning, time spent on PM (TPM), and cognitive workloads were compared between groups. After the simulation training, CG showed substantially lower simulation task scores (82.9 ± 6.0) compared with EG (93.2 ± 4.8). Both groups demonstrated improved physical model tasks performance with the actual robot, but the EG had a greater improvement in two tasks. The EG exhibited lower global mental workload/distress, higher engagement, and a better understanding regarding using PM to improve performance. The EG's TPM was initially long but substantially shortened as the group became familiar with PM. Our study demonstrated that the current VR simulator offered limited self-skill learning and additional mentoring still played an important role in improving the robotic surgery simulation training.

Simulator training to automaticity leads to improved skill transfer compared with traditional proficiency-based training: a randomized controlled trial.

PubMed

Stefanidis, Dimitrios; Scerbo, Mark W; Montero, Paul N; Acker, Christina E; Smith, Warren D

2012-01-01

We hypothesized that novices will perform better in the operating room after simulator training to automaticity compared with traditional proficiency based training (current standard training paradigm). Simulator-acquired skill translates to the operating room, but the skill transfer is incomplete. Secondary task metrics reflect the ability of trainees to multitask (automaticity) and may improve performance assessment on simulators and skill transfer by indicating when learning is complete. Novices (N = 30) were enrolled in an IRB-approved, blinded, randomized, controlled trial. Participants were randomized into an intervention (n = 20) and a control (n = 10) group. The intervention group practiced on the FLS suturing task until they achieved expert levels of time and errors (proficiency), were tested on a live porcine fundoplication model, continued simulator training until they achieved expert levels on a visual spatial secondary task (automaticity) and were retested on the operating room (OR) model. The control group participated only during testing sessions. Performance scores were compared within and between groups during testing sessions. : Intervention group participants achieved proficiency after 54 ± 14 and automaticity after additional 109 ± 57 repetitions. Participants achieved better scores in the OR after automaticity training [345 (range, 0-537)] compared with after proficiency-based training [220 (range, 0-452; P < 0.001]. Simulator training to automaticity takes more time but is superior to proficiency-based training, as it leads to improved skill acquisition and transfer. Secondary task metrics that reflect trainee automaticity should be implemented during simulator training to improve learning and skill transfer.

Solving the optimal attention allocation problem in manual control

NASA Technical Reports Server (NTRS)

Kleinman, D. L.

1976-01-01

Within the context of the optimal control model of human response, analytic expressions for the gradients of closed-loop performance metrics with respect to human operator attention allocation are derived. These derivatives serve as the basis for a gradient algorithm that determines the optimal attention that a human should allocate among several display indicators in a steady-state manual control task. Application of the human modeling techniques are made to study the hover control task for a CH-46 VTOL flight tested by NASA.

A Metric to Quantify Shared Visual Attention in Two-Person Teams

NASA Technical Reports Server (NTRS)

Gontar, Patrick; Mulligan, Jeffrey B.

2015-01-01

Critical tasks in high-risk environments are often performed by teams, the members of which must work together efficiently. In some situations, the team members may have to work together to solve a particular problem, while in others it may be better for them to divide the work into separate tasks that can be completed in parallel. We hypothesize that these two team strategies can be differentiated on the basis of shared visual attention, measured by gaze tracking.

Motion generation of robotic surgical tasks: learning from expert demonstrations.

PubMed

Reiley, Carol E; Plaku, Erion; Hager, Gregory D

2010-01-01

Robotic surgical assistants offer the possibility of automating portions of a task that are time consuming and tedious in order to reduce the cognitive workload of a surgeon. This paper proposes using programming by demonstration to build generative models and generate smooth trajectories that capture the underlying structure of the motion data recorded from expert demonstrations. Specifically, motion data from Intuitive Surgical's da Vinci Surgical System of a panel of expert surgeons performing three surgical tasks are recorded. The trials are decomposed into subtasks or surgemes, which are then temporally aligned through dynamic time warping. Next, a Gaussian Mixture Model (GMM) encodes the experts' underlying motion structure. Gaussian Mixture Regression (GMR) is then used to extract a smooth reference trajectory to reproduce a trajectory of the task. The approach is evaluated through an automated skill assessment measurement. Results suggest that this paper presents a means to (i) extract important features of the task, (ii) create a metric to evaluate robot imitative performance (iii) generate smoother trajectories for reproduction of three common medical tasks.

Stimulus selectivity of drug purchase tasks: A preliminary study evaluating alcohol and cigarette demand.

PubMed

Strickland, Justin C; Stoops, William W

2017-06-01

The use of drug purchase tasks to measure drug demand in human behavioral pharmacology and addiction research has proliferated in recent years. Few studies have systematically evaluated the stimulus selectivity of drug purchase tasks to demonstrate that demand metrics are specific to valuation of or demand for the commodity under study. Stimulus selectivity is broadly defined for this purpose as a condition under which a specific stimulus input or target (e.g., alcohol, cigarettes) is the primary determinant of behavior (e.g., demand). The overall goal of the present study was to evaluate the stimulus selectivity of drug purchase tasks. Participants were sampled from the Amazon.com's crowdsourcing platform Mechanical Turk. Participants completed either alcohol and soda purchase tasks (Experiment 1; N = 139) or cigarette and chocolate purchase tasks (Experiment 2; N = 46), and demand metrics were compared to self-reported use behaviors. Demand metrics for alcohol and soda were closely associated with commodity-similar (e.g., alcohol demand and weekly alcohol use) but not commodity-different (e.g., alcohol demand and weekly soda use) variables. A similar pattern was observed for cigarette and chocolate demand, but selectivity was not as consistent as for alcohol and soda. Collectively, we observed robust selectivity for alcohol and soda purchase tasks and modest selectivity for cigarette and chocolate purchase tasks. These preliminary outcomes suggest that demand metrics adequately reflect the specific commodity under study and support the continued use of purchase tasks in substance use research. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Demand Curves for Hypothetical Cocaine in Cocaine-Dependent Individuals

PubMed Central

Bruner, Natalie R.; Johnson, Matthew W.

2013-01-01

Rationale Drug purchasing tasks have been successfully used to examine demand for hypothetical consumption of abused drugs including heroin, nicotine, and alcohol. In these tasks drug users make hypothetical choices whether to buy drugs, and if so, at what quantity, at various potential prices. These tasks allow for behavioral economic assessment of that drug's intensity of demand (preferred level of consumption at extremely low prices) and demand elasticity (sensitivity of consumption to price), among other metrics. However, a purchasing task for cocaine in cocaine-dependent individuals has not been investigated. Objectives This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data. Methods Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use. Results Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and Omax (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, Pmax, were significantly correlated with real-world cocaine use. Conclusions Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use. PMID:24217899

Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia.

PubMed

Caminiti, Silvia P; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F

2015-01-01

bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms.

Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol.

PubMed

Kasturi, Rangachar; Goldgof, Dmitry; Soundararajan, Padmanabhan; Manohar, Vasant; Garofolo, John; Bowers, Rachel; Boonstra, Matthew; Korzhova, Valentina; Zhang, Jing

2009-02-01

Common benchmark data sets, standardized performance metrics, and baseline algorithms have demonstrated considerable impact on research and development in a variety of application domains. These resources provide both consumers and developers of technology with a common framework to objectively compare the performance of different algorithms and algorithmic improvements. In this paper, we present such a framework for evaluating object detection and tracking in video: specifically for face, text, and vehicle objects. This framework includes the source video data, ground-truth annotations (along with guidelines for annotation), performance metrics, evaluation protocols, and tools including scoring software and baseline algorithms. For each detection and tracking task and supported domain, we developed a 50-clip training set and a 50-clip test set. Each data clip is approximately 2.5 minutes long and has been completely spatially/temporally annotated at the I-frame level. Each task/domain, therefore, has an associated annotated corpus of approximately 450,000 frames. The scope of such annotation is unprecedented and was designed to begin to support the necessary quantities of data for robust machine learning approaches, as well as a statistically significant comparison of the performance of algorithms. The goal of this work was to systematically address the challenges of object detection and tracking through a common evaluation framework that permits a meaningful objective comparison of techniques, provides the research community with sufficient data for the exploration of automatic modeling techniques, encourages the incorporation of objective evaluation into the development process, and contributes useful lasting resources of a scale and magnitude that will prove to be extremely useful to the computer vision research community for years to come.

Brain processing of meter and rhythm in music. Electrophysiological evidence of a common network.

PubMed

Kuck, Heleln; Grossbach, Michael; Bangert, Marc; Altenmüller, Eckart

2003-11-01

To determine cortical structures involved in "global" meter and "local" rhythm processing, slow brain potentials (DC potentials) were recorded from the scalp of 18 musically trained subjects while listening to pairs of monophonic sequences with both metric structure and rhythmic variations. The second sequence could be either identical to or different from the first one. Differences were either of a metric or a rhythmic nature. The subjects' task was to judge whether the sequences were identical or not. During processing of the auditory tasks, brain activation patterns along with the subjects' performance were assessed using 32-channel DC electroencephalography. Data were statistically analyzed using MANOVA. Processing of both meter and rhythm produced sustained cortical activation over bilateral frontal and temporal brain regions. A shift towards right hemispheric activation was pronounced during presentation of the second stimulus. Processing of rhythmic differences yielded a more centroparietal activation compared to metric processing. These results do not support Lerdhal and Jackendoff's two-component model, predicting a dissociation of left hemispheric rhythm and right hemispheric meter processing. We suggest that the uniform right temporofrontal predominance reflects auditory working memory and a pattern recognition module, which participates in both rhythm and meter processing. More pronounced parietal activation during rhythm processing may be related to switching of task-solving strategies towards mental imagination of the score.

Shape detection of Gaborized outline versions of everyday objects

PubMed Central

Sassi, Michaël; Machilsen, Bart; Wagemans, Johan

2012-01-01

We previously tested the identifiability of six versions of Gaborized outlines of everyday objects, differing in the orientations assigned to elements inside and outside the outline. We found significant differences in identifiability between the versions, and related a number of stimulus metrics to identifiability [Sassi, M., Vancleef, K., Machilsen, B., Panis, S., & Wagemans, J. (2010). Identification of everyday objects on the basis of Gaborized outline versions. i-Perception, 1(3), 121–142]. In this study, after retesting the identifiability of new variants of three of the stimulus versions, we tested their robustness to local orientation jitter in a detection experiment. In general, our results replicated the key findings from the previous study, and allowed us to substantiate our earlier interpretations of the effects of our stimulus metrics and of the performance differences between the different stimulus versions. The results of the detection task revealed a different ranking order of stimulus versions than the identification task. By examining the parallels and differences between the effects of our stimulus metrics in the two tasks, we found evidence for a trade-off between shape detectability and identifiability. The generally simple and smooth shapes that yield the strongest contour integration and most robust detectability tend to lack the distinguishing features necessary for clear-cut identification. Conversely, contours that do contain such identifying features tend to be inherently more complex and, therefore, yield weaker integration and less robust detectability. PMID:23483752

Low-dose cone-beam CT via raw counts domain low-signal correction schemes: Performance assessment and task-based parameter optimization (Part II. Task-based parameter optimization).

PubMed

Gomez-Cardona, Daniel; Hayes, John W; Zhang, Ran; Li, Ke; Cruz-Bastida, Juan Pablo; Chen, Guang-Hong

2018-05-01

Different low-signal correction (LSC) methods have been shown to efficiently reduce noise streaks and noise level in CT to provide acceptable images at low-radiation dose levels. These methods usually result in CT images with highly shift-variant and anisotropic spatial resolution and noise, which makes the parameter optimization process highly nontrivial. The purpose of this work was to develop a local task-based parameter optimization framework for LSC methods. Two well-known LSC methods, the adaptive trimmed mean (ATM) filter and the anisotropic diffusion (AD) filter, were used as examples to demonstrate how to use the task-based framework to optimize filter parameter selection. Two parameters, denoted by the set P, for each LSC method were included in the optimization problem. For the ATM filter, these parameters are the low- and high-signal threshold levels p l and p h ; for the AD filter, the parameters are the exponents δ and γ in the brightness gradient function. The detectability index d' under the non-prewhitening (NPW) mathematical observer model was selected as the metric for parameter optimization. The optimization problem was formulated as an unconstrained optimization problem that consisted of maximizing an objective function d'(P), where i and j correspond to the i-th imaging task and j-th spatial location, respectively. Since there is no explicit mathematical function to describe the dependence of d' on the set of parameters P for each LSC method, the optimization problem was solved via an experimentally measured d' map over a densely sampled parameter space. In this work, three high-contrast-high-frequency discrimination imaging tasks were defined to explore the parameter space of each of the LSC methods: a vertical bar pattern (task I), a horizontal bar pattern (task II), and a multidirectional feature (task III). Two spatial locations were considered for the analysis, a posterior region-of-interest (ROI) located within the noise streaks region and an anterior ROI, located further from the noise streaks region. Optimal results derived from the task-based detectability index metric were compared to other operating points in the parameter space with different noise and spatial resolution trade-offs. The optimal operating points determined through the d' metric depended on the interplay between the major spatial frequency components of each imaging task and the highly shift-variant and anisotropic noise and spatial resolution properties associated with each operating point in the LSC parameter space. This interplay influenced imaging performance the most when the major spatial frequency component of a given imaging task coincided with the direction of spatial resolution loss or with the dominant noise spatial frequency component; this was the case of imaging task II. The performance of imaging tasks I and III was influenced by this interplay in a smaller scale than imaging task II, since the major frequency component of task I was perpendicular to imaging task II, and because imaging task III did not have strong directional dependence. For both LSC methods, there was a strong dependence of the overall d' magnitude and shape of the contours on the spatial location within the phantom, particularly for imaging tasks II and III. The d' value obtained at the optimal operating point for each spatial location and imaging task was similar when comparing the LSC methods studied in this work. A local task-based detectability framework to optimize the selection of parameters for LSC methods was developed. The framework takes into account the potential shift-variant and anisotropic spatial resolution and noise properties to maximize the imaging performance of the CT system. Optimal parameters for a given LSC method depend strongly on the spatial location within the image object. © 2018 American Association of Physicists in Medicine.

Mental workload and cognitive task automaticity: an evaluation of subjective and time estimation metrics.

PubMed

Liu, Y; Wickens, C D

1994-11-01

The evaluation of mental workload is becoming increasingly important in system design and analysis. The present study examined the structure and assessment of mental workload in performing decision and monitoring tasks by focusing on two mental workload measurements: subjective assessment and time estimation. The task required the assignment of a series of incoming customers to the shortest of three parallel service lines displayed on a computer monitor. The subject was either in charge of the customer assignment (manual mode) or was monitoring an automated system performing the same task (automatic mode). In both cases, the subjects were required to detect the non-optimal assignments that they or the computer had made. Time pressure was manipulated by the experimenter to create fast and slow conditions. The results revealed a multi-dimensional structure of mental workload and a multi-step process of subjective workload assessment. The results also indicated that subjective workload was more influenced by the subject's participatory mode than by the factor of task speed. The time estimation intervals produced while performing the decision and monitoring tasks had significantly greater length and larger variability than those produced while either performing no other tasks or performing a well practised customer assignment task. This result seemed to indicate that time estimation was sensitive to the presence of perceptual/cognitive demands, but not to response related activities to which behavioural automaticity has developed.

Acquisition, retention and transfer of simulated laparoscopic tasks using fNIR and a contextual interference paradigm.

PubMed

Shewokis, Patricia A; Shariff, Faiz U; Liu, Yichuan; Ayaz, Hasan; Castellanos, Andres; Lind, D Scott

2017-02-01

Using functional near infrared spectroscopy, a noninvasive, optical brain imaging tool that monitors changes in hemodynamics within the prefrontal cortex (PFC), we assessed performance and cognitive effort during the acquisition, retention and transfer of multiple simulated laparoscopic tasks by novice learners within a contextual interference paradigm. Third-year medical students (n = 10) were randomized to either a blocked or random practice schedule. Across 3 days, students performed 108 acquisition trials of 3 laparoscopic tasks on the LapSim ® simulator followed by delayed retention and transfer tests. Performance metrics (Global score, Total time) and hemodynamic responses (total hemoglobin (μm)) were assessed during skill acquisition, retention and transfer. All acquisition tasks resulted in significant practice schedule X trial block interactions for the left medial anterior PFC. During retention and transfer, random performed the skills in less time and had lower total hemoglobin change in the right dorsolateral PFC than blocked. Compared with blocked, random practice resulted in enhanced learning through better performance and less cognitive load for retention and transfer of simulated laparoscopic tasks. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of oral surgery task performance in a virtual reality surgical simulator and an animal model using objective measures.

PubMed

Ioannou, Ioanna; Kazmierczak, Edmund; Stern, Linda

2015-01-01

The use of virtual reality (VR) simulation for surgical training has gathered much interest in recent years. Despite increasing popularity and usage, limited work has been carried out in the use of automated objective measures to quantify the extent to which performance in a simulator resembles performance in the operating theatre, and the effects of simulator training on real world performance. To this end, we present a study exploring the effects of VR training on the performance of dentistry students learning a novel oral surgery task. We compare the performance of trainees in a VR simulator and in a physical setting involving ovine jaws, using a range of automated metrics derived by motion analysis. Our results suggest that simulator training improved the motion economy of trainees without adverse effects on task outcome. Comparison of surgical technique on the simulator with the ovine setting indicates that simulator technique is similar, but not identical to real world technique.

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks.

PubMed

Berka, Chris; Levendowski, Daniel J; Lumicao, Michelle N; Yau, Alan; Davis, Gene; Zivkovic, Vladimir T; Olmstead, Richard E; Tremoulet, Patrice D; Craven, Patrick L

2007-05-01

The ability to continuously and unobtrusively monitor levels of task engagement and mental workload in an operational environment could be useful in identifying more accurate and efficient methods for humans to interact with technology. This information could also be used to optimize the design of safer, more efficient work environments that increase motivation and productivity. The present study explored the feasibility of monitoring electroencephalo-graphic (EEG) indices of engagement and workload acquired unobtrusively and quantified during performance of cognitive tests. EEG was acquired from 80 healthy participants with a wireless sensor headset (F3-F4,C3-C4,Cz-POz,F3-Cz,Fz-C3,Fz-POz) during tasks including: multi-level forward/backward-digit-span, grid-recall, trails, mental-addition, 20-min 3-Choice Vigilance, and image-learning and memory tests. EEG metrics for engagement and workload were calculated for each 1 -s of EEG. Across participants, engagement but not workload decreased over the 20-min vigilance test. Engagement and workload were significantly increased during the encoding period of verbal and image-learning and memory tests when compared with the recognition/ recall period. Workload but not engagement increased linearly as level of difficulty increased in forward and backward-digit-span, grid-recall, and mental-addition tests. EEG measures correlated with both subjective and objective performance metrics. These data in combination with previous studies suggest that EEG engagement reflects information-gathering, visual processing, and allocation of attention. EEG workload increases with increasing working memory load and during problem solving, integration of information, analytical reasoning, and may be more reflective of executive functions. Inspection of EEG on a second-by-second timescale revealed associations between workload and engagement levels when aligned with specific task events providing preliminary evidence that second-by-second classifications reflect parameters of task performance.

Toward a better understanding of task demands, workload, and performance during physician-computer interactions.

PubMed

Mazur, Lukasz M; Mosaly, Prithima R; Moore, Carlton; Comitz, Elizabeth; Yu, Fei; Falchook, Aaron D; Eblan, Michael J; Hoyle, Lesley M; Tracton, Gregg; Chera, Bhishamjit S; Marks, Lawrence B

2016-11-01

To assess the relationship between (1) task demands and workload, (2) task demands and performance, and (3) workload and performance, all during physician-computer interactions in a simulated environment. Two experiments were performed in 2 different electronic medical record (EMR) environments: WebCIS (n = 12) and Epic (n = 17). Each participant was instructed to complete a set of prespecified tasks on 3 routine clinical EMR-based scenarios: urinary tract infection (UTI), pneumonia (PN), and heart failure (HF). Task demands were quantified using behavioral responses (click and time analysis). At the end of each scenario, subjective workload was measured using the NASA-Task-Load Index (NASA-TLX). Physiological workload was measured using pupillary dilation and electroencephalography (EEG) data collected throughout the scenarios. Performance was quantified based on the maximum severity of omission errors. Data analysis indicated that the PN and HF scenarios were significantly more demanding than the UTI scenario for participants using WebCIS (P < .01), and that the PN scenario was significantly more demanding than the UTI and HF scenarios for participants using Epic (P < .01). In both experiments, the regression analysis indicated a significant relationship only between task demands and performance (P < .01). Results suggest that task demands as experienced by participants are related to participants' performance. Future work may support the notion that task demands could be used as a quality metric that is likely representative of performance, and perhaps patient outcomes. The present study is a reasonable next step in a systematic assessment of how task demands and workload are related to performance in EMR-evolving environments. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Transitioning Technology to Naval Ships

DTIC Science & Technology

2010-06-18

GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Dr. Norbert Doerry 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING...6.3.3 Evaluation of IPS and NGIPS........................................................................................ 48 6.4 Set Based Design on...56 7.2 Employ More Robust Metrics........................................................................................... 57 7.2.1 Knowledge

Assessing Upper Extremity Motor Function in Practice of Virtual Activities of Daily Living

PubMed Central

Adams, Richard J.; Lichter, Matthew D.; Krepkovich, Eileen T.; Ellington, Allison; White, Marga; Diamond, Paul T.

2015-01-01

A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An Unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user’s avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman’s rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs. PMID:25265612

Assessing upper extremity motor function in practice of virtual activities of daily living.

PubMed

Adams, Richard J; Lichter, Matthew D; Krepkovich, Eileen T; Ellington, Allison; White, Marga; Diamond, Paul T

2015-03-01

A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user's avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman's rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs.

Partially supervised speaker clustering.

PubMed

Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

2012-05-01

Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical model-based distance metrics, 2) our advocated use of the cosine distance metric yields consistent increases in the speaker clustering performance as compared to the commonly used euclidean distance metric, 3) our partially supervised speaker clustering concept and strategies significantly improve the speaker clustering performance over the baselines, and 4) our proposed LSDA algorithm further leads to state-of-the-art speaker clustering performance.

Unobtrusive monitoring of divided attention in a cognitive health coaching intervention for the elderly.

PubMed

McKanna, James A; Pavel, Misha; Jimison, Holly

2010-11-13

Assessment of cognitive functionality is an important aspect of care for elders. Unfortunately, few tools exist to measure divided attention, the ability to allocate attention to different aspects of tasks. An accurate determination of divided attention would allow inference of generalized cognitive decline, as well as providing a quantifiable indicator of an important component of driving skill. We propose a new method for determining relative divided attention ability through unobtrusive monitoring of computer use. Specifically, we measure performance on a dual-task cognitive computer exercise as part of a health coaching intervention. This metric indicates whether the user has the ability to pay attention to both tasks at once, or is primarily attending to one task at a time (sacrificing optimal performance). The monitoring of divided attention in a home environment is a key component of both the early detection of cognitive problems and for assessing the efficacy of coaching interventions.

Distributed computing feasibility in a non-dedicated homogeneous distributed system

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Sun, Xian-He

1993-01-01

The low cost and availability of clusters of workstations have lead researchers to re-explore distributed computing using independent workstations. This approach may provide better cost/performance than tightly coupled multiprocessors. In practice, this approach often utilizes wasted cycles to run parallel jobs. The feasibility of such a non-dedicated parallel processing environment assuming workstation processes have preemptive priority over parallel tasks is addressed. An analytical model is developed to predict parallel job response times. Our model provides insight into how significantly workstation owner interference degrades parallel program performance. A new term task ratio, which relates the parallel task demand to the mean service demand of nonparallel workstation processes, is introduced. It was proposed that task ratio is a useful metric for determining how large the demand of a parallel applications must be in order to make efficient use of a non-dedicated distributed system.

Saccadic eye movement metrics reflect surgical residents' fatigue.

PubMed

Di Stasi, Leandro L; McCamy, Michael B; Macknik, Stephen L; Mankin, James A; Hooft, Nicole; Catena, Andrés; Martinez-Conde, Susana

2014-04-01

Little is known about the effects of surgical residents' fatigue on patient safety. We monitored surgical residents' fatigue levels during their call day using (1) eye movement metrics, (2) objective measures of laparoscopic surgical performance, and (3) subjective reports based on standardized questionnaires. Prior attempts to investigate the effects of fatigue on surgical performance have suffered from methodological limitations, including inconsistent definitions and lack of objective measures of fatigue, and nonstandardized measures of surgical performance. Recent research has shown that fatigue can affect the characteristics of saccadic (fast ballistic) eye movements in nonsurgical scenarios. Here we asked whether fatigue induced by time-on-duty (~24 hours) might affect saccadic metrics in surgical residents. Because saccadic velocity is not under voluntary control, a fatigue index based on saccadic velocity has the potential to provide an accurate and unbiased measure of the resident's fatigue level. We measured the eye movements of members of the general surgery resident team at St. Joseph's Hospital and Medical Center (Phoenix, AZ) (6 males and 6 females), using a head-mounted video eye tracker (similar configuration to a surgical headlight), during the performance of 3 tasks: 2 simulated laparoscopic surgery tasks (peg transfer and precision cutting) and a guided saccade task, before and after their call day. Residents rated their perceived fatigue level every 3 hours throughout their 24-hour shift, using a standardized scale. Time-on-duty decreased saccadic velocity and increased subjective fatigue but did not affect laparoscopic performance. These results support the hypothesis that saccadic indices reflect graded changes in fatigue. They also indicate that fatigue due to prolonged time-on-duty does not result necessarily in medical error, highlighting the complicated relationship among continuity of care, patient safety, and fatigued providers. Our data show, for the first time, that saccadic velocity is a reliable indicator of the subjective fatigue of health care professionals during prolonged time-on-duty. These findings have potential impacts for the development of neuroergonomic tools to detect fatigue among health professionals and in the specifications of future guidelines regarding residents' duty hours.

An analysis of relational complexity in an air traffic control conflict detection task.

PubMed

Boag, Christine; Neal, Andrew; Loft, Shayne; Halford, Graeme S

2006-11-15

Theoretical analyses of air traffic complexity were carried out using the Method for the Analysis of Relational Complexity. Twenty-two air traffic controllers examined static air traffic displays and were required to detect and resolve conflicts. Objective measures of performance included conflict detection time and accuracy. Subjective perceptions of mental workload were assessed by a complexity-sorting task and subjective ratings of the difficulty of different aspects of the task. A metric quantifying the complexity of pair-wise relations among aircraft was able to account for a substantial portion of the variance in the perceived complexity and difficulty of conflict detection problems, as well as reaction time. Other variables that influenced performance included the mean minimum separation between aircraft pairs and the amount of time that aircraft spent in conflict.

The Complexity of Standing Postural Sway Associates with Future Falls in Community-Dwelling Older Adults: The MOBILIZE Boston Study.

PubMed

Zhou, Junhong; Habtemariam, Daniel; Iloputaife, Ikechukwu; Lipsitz, Lewis A; Manor, Brad

2017-06-07

Standing postural control is complex, meaning that it is dependent upon numerous inputs interacting across multiple temporal-spatial scales. Diminished physiologic complexity of postural sway has been linked to reduced ability to adapt to stressors. We hypothesized that older adults with lower postural sway complexity would experience more falls in the future. 738 adults aged ≥70 years completed the Short Physical Performance Battery test (SPPB) test and assessments of single and dual-task standing postural control. Postural sway complexity was quantified using multiscale entropy. Falls were subsequently tracked for 48 months. Negative binomial regression demonstrated that older adults with lower postural sway complexity in both single and dual-task conditions had higher future fall rate (incident rate ratio (IRR) = 0.98, p = 0.02, 95% Confidence Limits (CL) = 0.96-0.99). Notably, participants in the lowest quintile of complexity during dual-task standing suffered 48% more falls during the four-year follow-up as compared to those in the highest quintile (IRR = 1.48, p = 0.01, 95% CL = 1.09-1.99). Conversely, traditional postural sway metrics or SPPB performance did not associate with future falls. As compared to traditional metrics, the degree of multi-scale complexity contained within standing postural sway-particularly during dual task conditions- appears to be a better predictor of future falls in older adults.

Network Science and Crowd Behavior Metrics

DTIC Science & Technology

2008-12-01

and C. Tucker, 2003 Handbook of symbolic interactionism . L. Reynolds and N. Herman-Kinney. Walnut Creek, CA, AltaM Press: 721-741. ___, and R. T...PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME (S) AND ADDRESS(ES) Army, ARDEC, Target Behavioral Response...Laboratory,RDAR-EIQ-SD,Building 3518,Picatinny Arsenal,NJ,07806-5000 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME (S

The Fundamentals of Laparoscopic Surgery and LapVR evaluation metrics may not correlate with operative performance in a novice cohort

PubMed Central

Steigerwald, Sarah N.; Park, Jason; Hardy, Krista M.; Gillman, Lawrence; Vergis, Ashley S.

2015-01-01

Background Considerable resources have been invested in both low- and high-fidelity simulators in surgical training. The purpose of this study was to investigate if the Fundamentals of Laparoscopic Surgery (FLS, low-fidelity box trainer) and LapVR (high-fidelity virtual reality) training systems correlate with operative performance on the Global Operative Assessment of Laparoscopic Skills (GOALS) global rating scale using a porcine cholecystectomy model in a novice surgical group with minimal laparoscopic experience. Methods Fourteen postgraduate year 1 surgical residents with minimal laparoscopic experience performed tasks from the FLS program and the LapVR simulator as well as a live porcine laparoscopic cholecystectomy. Performance was evaluated using standardized FLS metrics, automatic computer evaluations, and a validated global rating scale. Results Overall, FLS score did not show an association with GOALS global rating scale score on the porcine cholecystectomy. None of the five LapVR task scores were significantly associated with GOALS score on the porcine cholecystectomy. Conclusions Neither the low-fidelity box trainer or the high-fidelity virtual simulator demonstrated significant correlation with GOALS operative scores. These findings offer caution against the use of these modalities for brief assessments of novice surgical trainees, especially for predictive or selection purposes. PMID:26641071

Usability testing of a mobile robotic system for in-home telerehabilitation.

PubMed

Boissy, Patrick; Brière, Simon; Corriveau, Hélène; Grant, Andrew; Lauria, Michel; Michaud, François

2011-01-01

Mobile robots designed to enhance telepresence in the support of telehealth services are being considered for numerous applications. TELEROBOT is a teleoperated mobile robotic platform equipped with videoconferencingcapabilities and designed to be used in a home environment to. In this study, learnability of the system's teleoperation interface and controls was evaluated with ten rehabilitation professionals during four training sessions in a laboratory environment and in an unknown home environment while performing the execution of a standardized evaluation protocol typically used in home care. Results show that the novice teleoperators' performances on two of the four metrics used (number of command and total time) improved significantly across training sessions (ANOVAS, p<0.05) and that performance in these metrics in the last training session reflected teleoperation abilities seen in the unknown home environment during navigation tasks (r=0,77 and 0,60). With only 4 hours of training, rehabilitation professionals were able learn to teleoperate successfully TELEROBOT. However teleoperation performances remained significantly less efficient then those of an expert. Under the home task condition (navigating the home environment from one point to the other as fast as possible) this translated to completion time between 350 seconds (best performance) and 850 seconds (worse performance). Improvements in other usability aspects of the system will be needed to meet the requirements of in-home telerehabilitation.

Estimating endogenous changes in task performance from EEG

PubMed Central

Touryan, Jon; Apker, Gregory; Lance, Brent J.; Kerick, Scott E.; Ries, Anthony J.; McDowell, Kaleb

2014-01-01

Brain wave activity is known to correlate with decrements in behavioral performance as individuals enter states of fatigue, boredom, or low alertness.Many BCI technologies are adversely affected by these changes in user state, limiting their application and constraining their use to relatively short temporal epochs where behavioral performance is likely to be stable. Incorporating a passive BCI that detects when the user is performing poorly at a primary task, and adapts accordingly may prove to increase overall user performance. Here, we explore the potential for extending an established method to generate continuous estimates of behavioral performance from ongoing neural activity; evaluating the extended method by applying it to the original task domain, simulated driving; and generalizing the method by applying it to a BCI-relevant perceptual discrimination task. Specifically, we used EEG log power spectra and sequential forward floating selection (SFFS) to estimate endogenous changes in behavior in both a simulated driving task and a perceptual discrimination task. For the driving task the average correlation coefficient between the actual and estimated lane deviation was 0.37 ± 0.22 (μ ± σ). For the perceptual discrimination task we generated estimates of accuracy, reaction time, and button press duration for each participant. The correlation coefficients between the actual and estimated behavior were similar for these three metrics (accuracy = 0.25 ± 0.37, reaction time = 0.33 ± 0.23, button press duration = 0.36 ± 0.30). These findings illustrate the potential for modeling time-on-task decrements in performance from concurrent measures of neural activity. PMID:24994968

Viewpoint matters: objective performance metrics for surgeon endoscope control during robot-assisted surgery.

PubMed

Jarc, Anthony M; Curet, Myriam J

2017-03-01

Effective visualization of the operative field is vital to surgical safety and education. However, additional metrics for visualization are needed to complement other common measures of surgeon proficiency, such as time or errors. Unlike other surgical modalities, robot-assisted minimally invasive surgery (RAMIS) enables data-driven feedback to trainees through measurement of camera adjustments. The purpose of this study was to validate and quantify the importance of novel camera metrics during RAMIS. New (n = 18), intermediate (n = 8), and experienced (n = 13) surgeons completed 25 virtual reality simulation exercises on the da Vinci Surgical System. Three camera metrics were computed for all exercises and compared to conventional efficiency measures. Both camera metrics and efficiency metrics showed construct validity (p < 0.05) across most exercises (camera movement frequency 23/25, camera movement duration 22/25, camera movement interval 19/25, overall score 24/25, completion time 25/25). Camera metrics differentiated new and experienced surgeons across all tasks as well as efficiency metrics. Finally, camera metrics significantly (p < 0.05) correlated with completion time (camera movement frequency 21/25, camera movement duration 21/25, camera movement interval 20/25) and overall score (camera movement frequency 20/25, camera movement duration 19/25, camera movement interval 20/25) for most exercises. We demonstrate construct validity of novel camera metrics and correlation between camera metrics and efficiency metrics across many simulation exercises. We believe camera metrics could be used to improve RAMIS proficiency-based curricula.

Using cognitive task analysis to develop simulation-based training for medical tasks.

PubMed

Cannon-Bowers, Jan; Bowers, Clint; Stout, Renee; Ricci, Katrina; Hildabrand, Annette

2013-10-01

Pressures to increase the efficacy and effectiveness of medical training are causing the Department of Defense to investigate the use of simulation technologies. This article describes a comprehensive cognitive task analysis technique that can be used to simultaneously generate training requirements, performance metrics, scenario requirements, and simulator/simulation requirements for medical tasks. On the basis of a variety of existing techniques, we developed a scenario-based approach that asks experts to perform the targeted task multiple times, with each pass probing a different dimension of the training development process. In contrast to many cognitive task analysis approaches, we argue that our technique can be highly cost effective because it is designed to accomplish multiple goals. The technique was pilot tested with expert instructors from a large military medical training command. These instructors were employed to generate requirements for two selected combat casualty care tasks-cricothyroidotomy and hemorrhage control. Results indicated that the technique is feasible to use and generates usable data to inform simulation-based training system design. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Virtual reality-based assessment of basic laparoscopic skills using the Leap Motion controller.

PubMed

Lahanas, Vasileios; Loukas, Constantinos; Georgiou, Konstantinos; Lababidi, Hani; Al-Jaroudi, Dania

2017-12-01

The majority of the current surgical simulators employ specialized sensory equipment for instrument tracking. The Leap Motion controller is a new device able to track linear objects with sub-millimeter accuracy. The aim of this study was to investigate the potential of a virtual reality (VR) simulator for assessment of basic laparoscopic skills, based on the low-cost Leap Motion controller. A simple interface was constructed to simulate the insertion point of the instruments into the abdominal cavity. The controller provided information about the position and orientation of the instruments. Custom tools were constructed to simulate the laparoscopic setup. Three basic VR tasks were developed: camera navigation (CN), instrument navigation (IN), and bimanual operation (BO). The experiments were carried out in two simulation centers: MPLSC (Athens, Greece) and CRESENT (Riyadh, Kingdom of Saudi Arabia). Two groups of surgeons (28 experts and 21 novices) participated in the study by performing the VR tasks. Skills assessment metrics included time, pathlength, and two task-specific errors. The face validity of the training scenarios was also investigated via a questionnaire completed by the participants. Expert surgeons significantly outperformed novices in all assessment metrics for IN and BO (p < 0.05). For CN, a significant difference was found in one error metric (p < 0.05). The greatest difference between the performances of the two groups occurred for BO. Qualitative analysis of the instrument trajectory revealed that experts performed more delicate movements compared to novices. Subjects' ratings on the feedback questionnaire highlighted the training value of the system. This study provides evidence regarding the potential use of the Leap Motion controller for assessment of basic laparoscopic skills. The proposed system allowed the evaluation of dexterity of the hand movements. Future work will involve comparison studies with validated simulators and development of advanced training scenarios on current Leap Motion controller.

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

NASA Astrophysics Data System (ADS)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

Assessment of pilot workload - Converging measures from performance based, subjective and psychophysiological techniques

NASA Technical Reports Server (NTRS)

Kramer, Arthur F.; Sirevaag, Erik J.; Braune, Rolf

1986-01-01

This study explores the relationship between the P300 component of the event-related brain potential (ERP) and the processing demands of a complex real-world task. Seven male volunteers enrolled in an Instrument Flight Rule (IFR) aviation course flew a series of missions in a single engine fixed-based simulator. In dual task conditions subjects were also required to discriminate between two tones differing in frequency. ERPs time-locked to the tones, subjective effort ratings and overt performance measures were collected during two 45 min flights differing in difficulty (manipulated by varying both atmospheric conditions and instrument reliability). The more difficult flight was associated with poorer performance, increased subjective effort ratings, and smaller secondary task P300s. Within each flight, P300 amplitude was negatively correlated with deviations from command headings indicating that P300 amplitude was a sensitive workload metric both between and within the flight missions.

The relationship between organ dose and patient size in tube current modulated adult thoracic CT scans

NASA Astrophysics Data System (ADS)

Khatonabadi, Maryam; Zhang, Di; Yang, Jeffrey; DeMarco, John J.; Cagnon, Chris C.; McNitt-Gray, Michael F.

2012-03-01

Recently published AAPM Task Group 204 developed conversion coefficients that use scanner reported CTDIvol to estimate dose to the center of patient undergoing fixed tube current body exam. However, most performed CT exams use TCM to reduce dose to patients. Therefore, the purpose of this study was to investigate the correlation between organ dose and a variety of patient size metrics in adult chest CT scans that use tube current modulation (TCM). Monte Carlo simulations were performed for 32 voxelized models with contoured lungs and glandular breasts tissue, consisting of females and males. These simulations made use of patient's actual TCM data to estimate organ dose. Using image data, different size metrics were calculated, these measurements were all performed on one slice, at the level of patient's nipple. Estimated doses were normalized by scanner-reported CTDIvol and plotted versus different metrics. CTDIvol values were plotted versus different metrics to look at scanner's output versus size. The metrics performed similarly in terms of correlating with organ dose. Looking at each gender separately, for male models normalized lung dose showed a better linear correlation (r2=0.91) with effective diameter, while female models showed higher correlation (r2=0.59) with the anterior-posterior measurement. There was essentially no correlation observed between size and CTDIvol-normalized breast dose. However, a linear relationship was observed between absolute breast dose and size. Dose to lungs and breasts were consistently higher in females with similar size as males which could be due to shape and composition differences between genders in the thoracic region.

Quantifying performance and effects of load carriage during a challenging balancing task using an array of wireless inertial sensors.

PubMed

Cain, Stephen M; McGinnis, Ryan S; Davidson, Steven P; Vitali, Rachel V; Perkins, Noel C; McLean, Scott G

2016-01-01

We utilize an array of wireless inertial measurement units (IMUs) to measure the movements of subjects (n=30) traversing an outdoor balance beam (zigzag and sloping) as quickly as possible both with and without load (20.5kg). Our objectives are: (1) to use IMU array data to calculate metrics that quantify performance (speed and stability) and (2) to investigate the effects of load on performance. We hypothesize that added load significantly decreases subject speed yet results in increased stability of subject movements. We propose and evaluate five performance metrics: (1) time to cross beam (less time=more speed), (2) percentage of total time spent in double support (more double support time=more stable), (3) stride duration (longer stride duration=more stable), (4) ratio of sacrum M-L to A-P acceleration (lower ratio=less lateral balance corrections=more stable), and (5) M-L torso range of motion (smaller range of motion=less balance corrections=more stable). We find that the total time to cross the beam increases with load (t=4.85, p<0.001). Stability metrics also change significantly with load, all indicating increased stability. In particular, double support time increases (t=6.04, p<0.001), stride duration increases (t=3.436, p=0.002), the ratio of sacrum acceleration RMS decreases (t=-5.56, p<0.001), and the M-L torso lean range of motion decreases (t=-2.82, p=0.009). Overall, the IMU array successfully measures subject movement and gait parameters that reveal the trade-off between speed and stability in this highly dynamic balance task. Copyright © 2015 Elsevier B.V. All rights reserved.

Collected notes from the Benchmarks and Metrics Workshop

NASA Technical Reports Server (NTRS)

Drummond, Mark E.; Kaelbling, Leslie P.; Rosenschein, Stanley J.

1991-01-01

In recent years there has been a proliferation of proposals in the artificial intelligence (AI) literature for integrated agent architectures. Each architecture offers an approach to the general problem of constructing an integrated agent. Unfortunately, the ways in which one architecture might be considered better than another are not always clear. There has been a growing realization that many of the positive and negative aspects of an architecture become apparent only when experimental evaluation is performed and that to progress as a discipline, we must develop rigorous experimental methods. In addition to the intrinsic intellectual interest of experimentation, rigorous performance evaluation of systems is also a crucial practical concern to our research sponsors. DARPA, NASA, and AFOSR (among others) are actively searching for better ways of experimentally evaluating alternative approaches to building intelligent agents. One tool for experimental evaluation involves testing systems on benchmark tasks in order to assess their relative performance. As part of a joint DARPA and NASA funded project, NASA-Ames and Teleos Research are carrying out a research effort to establish a set of benchmark tasks and evaluation metrics by which the performance of agent architectures may be determined. As part of this project, we held a workshop on Benchmarks and Metrics at the NASA Ames Research Center on June 25, 1990. The objective of the workshop was to foster early discussion on this important topic. We did not achieve a consensus, nor did we expect to. Collected here is some of the information that was exchanged at the workshop. Given here is an outline of the workshop, a list of the participants, notes taken on the white-board during open discussions, position papers/notes from some participants, and copies of slides used in the presentations.

Mapping Muscles Activation to Force Perception during Unloading

PubMed Central

Toma, Simone; Lacquaniti, Francesco

2016-01-01

It has been largely proved that while judging a force humans mainly rely on the motor commands produced to interact with that force (i.e., sense of effort). Despite of a large bulk of previous investigations interested in understanding the contributions of the descending and ascending signals in force perception, very few attempts have been made to link a measure of neural output (i.e., EMG) to the psychophysical performance. Indeed, the amount of correlation between EMG activity and perceptual decisions can be interpreted as an estimate of the contribution of central signals involved in the sensation of force. In this study we investigated this correlation by measuring the muscular activity of eight arm muscles while participants performed a quasi-isometric force detection task. Here we showed a method to quantitatively describe muscular activity (“muscle-metric function”) that was directly comparable to the description of the participants' psychophysical decisions about the stimulus force. We observed that under our experimental conditions, muscle-metric absolute thresholds and the shape of the muscle-metric curves were closely related to those provided by the psychophysics. In fact a global measure of the muscles considered was able to predict approximately 60% of the perceptual decisions total variance. Moreover the inter-subjects differences in psychophysical sensitivity showed high correlation with both participants' muscles sensitivity and participants' joint torques. Overall, our findings gave insights into both the role played by the corticospinal motor commands while performing a force detection task and the influence of the gravitational muscular torque on the estimation of vertical forces. PMID:27032087

Mapping Muscles Activation to Force Perception during Unloading.

PubMed

Toma, Simone; Lacquaniti, Francesco

2016-01-01

It has been largely proved that while judging a force humans mainly rely on the motor commands produced to interact with that force (i.e., sense of effort). Despite of a large bulk of previous investigations interested in understanding the contributions of the descending and ascending signals in force perception, very few attempts have been made to link a measure of neural output (i.e., EMG) to the psychophysical performance. Indeed, the amount of correlation between EMG activity and perceptual decisions can be interpreted as an estimate of the contribution of central signals involved in the sensation of force. In this study we investigated this correlation by measuring the muscular activity of eight arm muscles while participants performed a quasi-isometric force detection task. Here we showed a method to quantitatively describe muscular activity ("muscle-metric function") that was directly comparable to the description of the participants' psychophysical decisions about the stimulus force. We observed that under our experimental conditions, muscle-metric absolute thresholds and the shape of the muscle-metric curves were closely related to those provided by the psychophysics. In fact a global measure of the muscles considered was able to predict approximately 60% of the perceptual decisions total variance. Moreover the inter-subjects differences in psychophysical sensitivity showed high correlation with both participants' muscles sensitivity and participants' joint torques. Overall, our findings gave insights into both the role played by the corticospinal motor commands while performing a force detection task and the influence of the gravitational muscular torque on the estimation of vertical forces.

Efficiently Selecting the Best Web Services

NASA Astrophysics Data System (ADS)

Goncalves, Marlene; Vidal, Maria-Esther; Regalado, Alfredo; Yacoubi Ayadi, Nadia

Emerging technologies and linking data initiatives have motivated the publication of a large number of datasets, and provide the basis for publishing Web services and tools to manage the available data. This wealth of resources opens a world of possibilities to satisfy user requests. However, Web services may have similar functionality and assess different performance; therefore, it is required to identify among the Web services that satisfy a user request, the ones with the best quality. In this paper we propose a hybrid approach that combines reasoning tasks with ranking techniques to aim at the selection of the Web services that best implement a user request. Web service functionalities are described in terms of input and output attributes annotated with existing ontologies, non-functionality is represented as Quality of Services (QoS) parameters, and user requests correspond to conjunctive queries whose sub-goals impose restrictions on the functionality and quality of the services to be selected. The ontology annotations are used in different reasoning tasks to infer service implicit properties and to augment the size of the service search space. Furthermore, QoS parameters are considered by a ranking metric to classify the services according to how well they meet a user non-functional condition. We assume that all the QoS parameters of the non-functional condition are equally important, and apply the Top-k Skyline approach to select the k services that best meet this condition. Our proposal relies on a two-fold solution which fires a deductive-based engine that performs different reasoning tasks to discover the services that satisfy the requested functionality, and an efficient implementation of the Top-k Skyline approach to compute the top-k services that meet the majority of the QoS constraints. Our Top-k Skyline solution exploits the properties of the Skyline Frequency metric and identifies the top-k services by just analyzing a subset of the services that meet the non-functional condition. We report on the effects of the proposed reasoning tasks, the quality of the top-k services selected by the ranking metric, and the performance of the proposed ranking techniques. Our results suggest that the number of services can be augmented by up two orders of magnitude. In addition, our ranking techniques are able to identify services that have the best values in at least half of the QoS parameters, while the performance is improved.

A comparison of evaluation metrics for biomedical journals, articles, and websites in terms of sensitivity to topic.

PubMed

Fu, Lawrence D; Aphinyanaphongs, Yindalon; Wang, Lily; Aliferis, Constantin F

2011-08-01

Evaluating the biomedical literature and health-related websites for quality are challenging information retrieval tasks. Current commonly used methods include impact factor for journals, PubMed's clinical query filters and machine learning-based filter models for articles, and PageRank for websites. Previous work has focused on the average performance of these methods without considering the topic, and it is unknown how performance varies for specific topics or focused searches. Clinicians, researchers, and users should be aware when expected performance is not achieved for specific topics. The present work analyzes the behavior of these methods for a variety of topics. Impact factor, clinical query filters, and PageRank vary widely across different topics while a topic-specific impact factor and machine learning-based filter models are more stable. The results demonstrate that a method may perform excellently on average but struggle when used on a number of narrower topics. Topic-adjusted metrics and other topic robust methods have an advantage in such situations. Users of traditional topic-sensitive metrics should be aware of their limitations. Copyright © 2011 Elsevier Inc. All rights reserved.

Phase Two Feasibility Study for Software Safety Requirements Analysis Using Model Checking

NASA Technical Reports Server (NTRS)

Turgeon, Gregory; Price, Petra

2010-01-01

A feasibility study was performed on a representative aerospace system to determine the following: (1) the benefits and limitations to using SCADE , a commercially available tool for model checking, in comparison to using a proprietary tool that was studied previously [1] and (2) metrics for performing the model checking and for assessing the findings. This study was performed independently of the development task by a group unfamiliar with the system, providing a fresh, external perspective free from development bias.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Metrics Handbook (Air Force Systems Command)

NASA Astrophysics Data System (ADS)

1991-08-01

The handbook is designed to help one develop and use good metrics. It is intended to provide sufficient information to begin developing metrics for objectives, processes, and tasks, and to steer one toward appropriate actions based on the data one collects. It should be viewed as a road map to assist one in arriving at meaningful metrics and to assist in continuous process improvement.

Design strategies to improve patient motivation during robot-aided rehabilitation.

PubMed

Colombo, Roberto; Pisano, Fabrizio; Mazzone, Alessandra; Delconte, Carmen; Micera, Silvestro; Carrozza, M Chiara; Dario, Paolo; Minuco, Giuseppe

2007-02-19

Motivation is an important factor in rehabilitation and frequently used as a determinant of rehabilitation outcome. Several factors can influence patient motivation and so improve exercise adherence. This paper presents the design of two robot devices for use in the rehabilitation of upper limb movements, that can motivate patients during the execution of the assigned motor tasks by enhancing the gaming aspects of rehabilitation. In addition, a regular review of the obtained performance can reinforce in patients' minds the importance of exercising and encourage them to continue, so improving their motivation and consequently adherence to the program. In view of this, we also developed an evaluation metric that could characterize the rate of improvement and quantify the changes in the obtained performance. Two groups (G1, n = 8 and G2, n = 12) of patients with chronic stroke were enrolled in a 3-week rehabilitation program including standard physical therapy (45 min. daily) plus treatment by means of robot devices (40 min., twice daily) respectively for wrist (G1) and elbow-shoulder movements (G2). Both groups were evaluated by means of standard clinical assessment scales and the new robot measured evaluation metric. Patients' motivation was assessed in 9/12 G2 patients by means of the Intrinsic Motivation Inventory (IMI) questionnaire. Both groups reduced their motor deficit and showed a significant improvement in clinical scales and the robot measured parameters. The IMI assessed in G2 patients showed high scores for interest, usefulness and importance subscales and low values for tension and pain subscales. Thanks to the design features of the two robot devices the therapist could easily adapt training to the individual by selecting different difficulty levels of the motor task tailored to each patient's disability. The gaming aspects incorporated in the two rehabilitation robots helped maintain patients' interest high during execution of the assigned tasks by providing feedback on performance. The evaluation metric gave a precise measure of patients' performance and thus provides a tool to help therapists promote patient motivation and hence adherence to the training program.

Asynchronous decision making in a memorized paddle pressing task

NASA Astrophysics Data System (ADS)

Dankert, James R.; Olson, Byron; Si, Jennie

2008-12-01

This paper presents a method for asynchronous decision making using recorded neural data in a binary decision task. This is a demonstration of a technique for developing motor cortical neural prosthetics that do not rely on external cued timing information. The system presented in this paper uses support vector machines and leaky integrate-and-fire elements to predict directional paddle presses. In addition to the traditional metrics of accuracy, asynchronous systems must also optimize the time needed to make a decision. The system presented is able to predict paddle presses with a median accuracy of 88% and all decisions are made before the time of the actual paddle press. An alternative bit rate measure of performance is defined to show that the system proposed here is able to perform the task with the same efficiency as the rats.

Operating room metrics score card-creating a prototype for individualized feedback.

PubMed

Gabriel, Rodney A; Gimlich, Robert; Ehrenfeld, Jesse M; Urman, Richard D

2014-11-01

The balance between reducing costs and inefficiencies with that of patient safety is a challenging problem faced in the operating room suite. An ongoing challenge is the creation of effective strategies that reduce these inefficiencies and provide real-time personalized metrics and electronic feedback to anesthesia practitioners. We created a sample report card structure, utilizing existing informatics systems. This system allows to gather and analyze operating room metrics for each anesthesia provider and offer personalized feedback. To accomplish this task, we identified key metrics that represented time and quality parameters. We collected these data for individual anesthesiologists and compared performance to the overall group average. Data were presented as an electronic score card and made available to individual clinicians on a real-time basis in an effort to provide effective feedback. These metrics included number of cancelled cases, average turnover time, average time to operating room ready and patient in room, number of delayed first case starts, average induction time, average extubation time, average time to recovery room arrival to discharge, performance feedback from other providers, compliance to various protocols, and total anesthetic costs. The concept we propose can easily be generalized to a variety of operating room settings, types of facilities and OR health care professionals. Such a scorecard can be created using content that is important for operating room efficiency, research, and practice improvement for anesthesia providers.

Test-retest reliability of an fMRI paradigm for studies of cardiovascular reactivity.

PubMed

Sheu, Lei K; Jennings, J Richard; Gianaros, Peter J

2012-07-01

We examined the reliability of measures of fMRI, subjective, and cardiovascular reactions to standardized versions of a Stroop color-word task and a multisource interference task. A sample of 14 men and 12 women (30-49 years old) completed the tasks on two occasions, separated by a median of 88 days. The reliability of fMRI BOLD signal changes in brain areas engaged by the tasks was moderate, and aggregating fMRI BOLD signal changes across the tasks improved test-retest reliability metrics. These metrics included voxel-wise intraclass correlation coefficients (ICCs) and overlap ratio statistics. Task-aggregated ratings of subjective arousal, valence, and control, as well as cardiovascular reactions evoked by the tasks showed ICCs of 0.57 to 0.87 (ps < .001), indicating moderate-to-strong reliability. These findings support using these tasks as a battery for fMRI studies of cardiovascular reactivity. Copyright © 2012 Society for Psychophysiological Research.

C3 generic workstation: Performance metrics and applications

NASA Technical Reports Server (NTRS)

Eddy, Douglas R.

1988-01-01

The large number of integrated dependent measures available on a command, control, and communications (C3) generic workstation under development are described. In this system, embedded communications tasks will manipulate workload to assess the effects of performance-enhancing drugs (sleep aids and decongestants), work/rest cycles, biocybernetics, and decision support systems on performance. Task performance accuracy and latency will be event coded for correlation with other measures of voice stress and physiological functioning. Sessions will be videotaped to score non-verbal communications. Physiological recordings include spectral analysis of EEG, ECG, vagal tone, and EOG. Subjective measurements include SWAT, fatigue, POMS and specialized self-report scales. The system will be used primarily to evaluate the effects on performance of drugs, work/rest cycles, and biocybernetic concepts. Performance assessment algorithms will also be developed, including those used with small teams. This system provides a tool for integrating and synchronizing behavioral and psychophysiological measures in a complex decision-making environment.

Use of a machine learning algorithm to classify expertise: analysis of hand motion patterns during a simulated surgical task.

PubMed

Watson, Robert A

2014-08-01

To test the hypothesis that machine learning algorithms increase the predictive power to classify surgical expertise using surgeons' hand motion patterns. In 2012 at the University of North Carolina at Chapel Hill, 14 surgical attendings and 10 first- and second-year surgical residents each performed two bench model venous anastomoses. During the simulated tasks, the participants wore an inertial measurement unit on the dorsum of their dominant (right) hand to capture their hand motion patterns. The pattern from each bench model task performed was preprocessed into a symbolic time series and labeled as expert (attending) or novice (resident). The labeled hand motion patterns were processed and used to train a Support Vector Machine (SVM) classification algorithm. The trained algorithm was then tested for discriminative/predictive power against unlabeled (blinded) hand motion patterns from tasks not used in the training. The Lempel-Ziv (LZ) complexity metric was also measured from each hand motion pattern, with an optimal threshold calculated to separately classify the patterns. The LZ metric classified unlabeled (blinded) hand motion patterns into expert and novice groups with an accuracy of 70% (sensitivity 64%, specificity 80%). The SVM algorithm had an accuracy of 83% (sensitivity 86%, specificity 80%). The results confirmed the hypothesis. The SVM algorithm increased the predictive power to classify blinded surgical hand motion patterns into expert versus novice groups. With further development, the system used in this study could become a viable tool for low-cost, objective assessment of procedural proficiency in a competency-based curriculum.

Effects of low to moderate acute doses of pramipexole on impulsivity and cognition in healthy volunteers.

PubMed

Hamidovic, Ajna; Kang, Un Jung; de Wit, Harriet

2008-02-01

The neurotransmitter dopamine is integrally involved in the rewarding effects of drugs, and it has also been thought to mediate impulsive behaviors in animal models. Most of the studies of drug effects on impulsive behaviors in humans have involved drugs with complex actions on different transmitter systems and different receptor subtypes. The present study was designed to characterize the effect of single doses of pramipexole, a D2/D3 agonist, on measures of cognitive and impulsive behavior, as well as on mood in healthy volunteers. Healthy men and women (N = 10) received placebo and 2 doses of pramipexole, 0.25 and 0.50 mg, in a within-subject, double-blinded study. Outcome measures included changes in cognitive performance, assessed by the Automated Neuropsychological Assessment Metrics, several behavioral measures related to impulsive behavior, including the Balloon Analogue Risk Task, Delay Discounting Task, Go/No-Go Task, Card Perseveration Task, and subjective ratings of mood assessed by Addiction Research Center Inventory, Profile of Mood States, and Drug Effects Questionnaire. Pramipexole decreased positive ratings of mood (euphoria, intellectual efficiency, and energy) and increased both subjectively reported sedation and behavioral sedation indicated by impaired cognitive performance on several measures of the Automated Neuropsychological Assessment Metrics. Single low to medium doses of this drug did not produce a decrease in impulsive responding on behavioral measures included in this study. The sedative-like effects observed in this study may reflect presynaptic actions of the drug. Higher doses with postsynaptic actions may be needed to produce either behavioral or subjective stimulant-like effects.

Defining and quantifying users' mental Imagery-based BCI skills: a first step.

PubMed

Lotte, Fabien; Jeunet, Camille

2018-05-17

While promising for many applications, Electroencephalography (EEG)-based Brain-Computer Interfaces (BCIs) are still scarcely used outside laboratories, due to a poor reliability. It is thus necessary to study and fix this reliability issue. Doing so requires the use of appropriate reliability metrics to quantify both the classification algorithm and the BCI user's performances. So far, Classification Accuracy (CA) is the typical metric used for both aspects. However, we argue in this paper that CA is a poor metric to study BCI users' skills. Here, we propose a definition and new metrics to quantify such BCI skills for Mental Imagery (MI) BCIs, independently of any classification algorithm. Approach: We first show in this paper that CA is notably unspecific, discrete, training data and classifier dependent, and as such may not always reflect successful self-modulation of EEG patterns by the user. We then propose a definition of MI-BCI skills that reflects how well the user can self-modulate EEG patterns, and thus how well he could control an MI-BCI. Finally, we propose new performance metrics, classDis, restDist and classStab that specifically measure how distinct and stable the EEG patterns produced by the user are, independently of any classifier. Main results: By re-analyzing EEG data sets with such new metrics, we indeed confirmed that CA may hide some increase in MI-BCI skills or hide the user inability to self-modulate a given EEG pattern. On the other hand, our new metrics could reveal such skill improvements as well as identify when a mental task performed by a user was no different than rest EEG. Significance: Our results showed that when studying MI-BCI users' skills, CA should be used with care, and complemented with metrics such as the new ones proposed. Our results also stressed the need to redefine BCI user training by considering the different BCI subskills and their measures. To promote the complementary use of our new metrics, we provide the Matlab code to compute them for free and open-source. © 2018 IOP Publishing Ltd.

Common Metrics for Human-Robot Interaction

NASA Technical Reports Server (NTRS)

Steinfeld, Aaron; Lewis, Michael; Fong, Terrence; Scholtz, Jean; Schultz, Alan; Kaber, David; Goodrich, Michael

2006-01-01

This paper describes an effort to identify common metrics for task-oriented human-robot interaction (HRI). We begin by discussing the need for a toolkit of HRI metrics. We then describe the framework of our work and identify important biasing factors that must be taken into consideration. Finally, we present suggested common metrics for standardization and a case study. Preparation of a larger, more detailed toolkit is in progress.

Rhythm synchronization performance and auditory working memory in early- and late-trained musicians.

PubMed

Bailey, Jennifer A; Penhune, Virginia B

2010-07-01

Behavioural and neuroimaging studies provide evidence for a possible "sensitive" period in childhood development during which musical training results in long-lasting changes in brain structure and auditory and motor performance. Previous work from our laboratory has shown that adult musicians who begin training before the age of 7 (early-trained; ET) perform better on a visuomotor task than those who begin after the age of 7 (late-trained; LT), even when matched on total years of musical training and experience. Two questions were raised regarding the findings from this experiment. First, would this group performance difference be observed using a more familiar, musically relevant task such as auditory rhythms? Second, would cognitive abilities mediate this difference in task performance? To address these questions, ET and LT musicians, matched on years of musical training, hours of current practice and experience, were tested on an auditory rhythm synchronization task. The task consisted of six woodblock rhythms of varying levels of metrical complexity. In addition, participants were tested on cognitive subtests measuring vocabulary, working memory and pattern recognition. The two groups of musicians differed in their performance of the rhythm task, such that the ET musicians were better at reproducing the temporal structure of the rhythms. There were no group differences on the cognitive measures. Interestingly, across both groups, individual task performance correlated with auditory working memory abilities and years of formal training. These results support the idea of a sensitive period during the early years of childhood for developing sensorimotor synchronization abilities via musical training.

Timesharing performance as an indicator of pilot mental workload

NASA Technical Reports Server (NTRS)

Casper, Patricia A.

1988-01-01

The research was performed in two simultaneous phases, each intended to identify and manipulate factors related to operator mental workload. The first phase concerned evaluation of attentional deficits (workloads) in a timesharing task. Work in the second phase involved incorporating the results from these and other experiments into an expert system designed to provide workload metric selection advice to nonexperts in the field interested in operator workload. The results of the experiments conducted are summarized.

An Evaluation of Detect and Avoid (DAA) Displays for Unmanned Aircraft Systems: The Effect of Information Level and Display Location on Pilot Performance

NASA Technical Reports Server (NTRS)

Fern, Lisa; Rorie, R. Conrad; Pack, Jessica S.; Shively, R. Jay; Draper, Mark H.

2015-01-01

A consortium of government, industry and academia is currently working to establish minimum operational performance standards for Detect and Avoid (DAA) and Control and Communications (C2) systems in order to enable broader integration of Unmanned Aircraft Systems (UAS) into the National Airspace System (NAS). One subset of these performance standards will need to address the DAA display requirements that support an acceptable level of pilot performance. From a pilot's perspective, the DAA task is the maintenance of self separation and collision avoidance from other aircraft, utilizing the available information and controls within the Ground Control Station (GCS), including the DAA display. The pilot-in-the-loop DAA task requires the pilot to carry out three major functions: 1) detect a potential threat, 2) determine an appropriate resolution maneuver, and 3) execute that resolution maneuver via the GCS control and navigation interface(s). The purpose of the present study was to examine two main questions with respect to DAA display considerations that could impact pilots' ability to maintain well clear from other aircraft. First, what is the effect of a minimum (or basic) information display compared to an advanced information display on pilot performance? Second, what is the effect of display location on UAS pilot performance? Two levels of information level (basic, advanced) were compared across two levels of display location (standalone, integrated), for a total of four displays. The authors propose an eight-stage pilot-DAA interaction timeline from which several pilot response time metrics can be extracted. These metrics were compared across the four display conditions. The results indicate that the advanced displays had faster overall response times compared to the basic displays, however, there were no significant differences between the standalone and integrated displays. Implications of the findings on understanding pilot performance on the DAA task, the development of DAA display performance standards, as well as the need for future research are discussed.

The MPC&A Questionnaire

DOE Office of Scientific and Technical Information (OSTI.GOV)

Powell, Danny H; Elwood Jr, Robert H

The questionnaire is the instrument used for recording performance data on the nuclear material protection, control, and accountability (MPC&A) system at a nuclear facility. The performance information provides a basis for evaluating the effectiveness of the MPC&A system. The goal for the questionnaire is to provide an accurate representation of the performance of the MPC&A system as it currently exists in the facility. Performance grades for all basic MPC&A functions should realistically reflect the actual level of performance at the time the survey is conducted. The questionnaire was developed after testing and benchmarking the material control and accountability (MC&A) systemmore » effectiveness tool (MSET) in the United States. The benchmarking exercise at the Idaho National Laboratory (INL) proved extremely valuable for improving the content and quality of the early versions of the questionnaire. Members of the INL benchmark team identified many areas of the questionnaire where questions should be clarified and areas where additional questions should be incorporated. The questionnaire addresses all elements of the MC&A system. Specific parts pertain to the foundation for the facility's overall MPC&A system, and other parts pertain to the specific functions of the operational MPC&A system. The questionnaire includes performance metrics for each of the basic functions or tasks performed in the operational MPC&A system. All of those basic functions or tasks are represented as basic events in the MPC&A fault tree. Performance metrics are to be used during completion of the questionnaire to report what is actually being done in relation to what should be done in the performance of MPC&A functions.« less

Changes in Brain Network Efficiency and Working Memory Performance in Aging

PubMed Central

Stanley, Matthew L.; Simpson, Sean L.; Dagenbach, Dale; Lyday, Robert G.; Burdette, Jonathan H.; Laurienti, Paul J.

2015-01-01

Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory. PMID:25875001

Changes in brain network efficiency and working memory performance in aging.

PubMed

Stanley, Matthew L; Simpson, Sean L; Dagenbach, Dale; Lyday, Robert G; Burdette, Jonathan H; Laurienti, Paul J

2015-01-01

Working memory is a complex psychological construct referring to the temporary storage and active processing of information. We used functional connectivity brain network metrics quantifying local and global efficiency of information transfer for predicting individual variability in working memory performance on an n-back task in both young (n = 14) and older (n = 15) adults. Individual differences in both local and global efficiency during the working memory task were significant predictors of working memory performance in addition to age (and an interaction between age and global efficiency). Decreases in local efficiency during the working memory task were associated with better working memory performance in both age cohorts. In contrast, increases in global efficiency were associated with much better working performance for young participants; however, increases in global efficiency were associated with a slight decrease in working memory performance for older participants. Individual differences in local and global efficiency during resting-state sessions were not significant predictors of working memory performance. Significant group whole-brain functional network decreases in local efficiency also were observed during the working memory task compared to rest, whereas no significant differences were observed in network global efficiency. These results are discussed in relation to recently developed models of age-related differences in working memory.

Immersive training and mentoring for laparoscopic surgery

NASA Astrophysics Data System (ADS)

Nistor, Vasile; Allen, Brian; Dutson, E.; Faloutsos, P.; Carman, G. P.

2007-04-01

We describe in this paper a training system for minimally invasive surgery (MIS) that creates an immersive training simulation by recording the pathways of the instruments from an expert surgeon while performing an actual training task. Instrument spatial pathway data is stored and later accessed at the training station in order to visualize the ergonomic experience of the expert surgeon and trainees. Our system is based on tracking the spatial position and orientation of the instruments on the console for both the expert surgeon and the trainee. The technology is the result of recent developments in miniaturized position sensors that can be integrated seamlessly into the MIS instruments without compromising functionality. In order to continuously monitor the positions of laparoscopic tool tips, DC magnetic tracking sensors are used. A hardware-software interface transforms the coordinate data points into instrument pathways, while an intuitive graphic user interface displays the instruments spatial position and orientation for the mentor/trainee, and endoscopic video information. These data are recorded and saved in a database for subsequent immersive training and training performance analysis. We use two 6 DOF DC magnetic trackers with a sensor diameter of just 1.3 mm - small enough for insertion into 4 French catheters, embedded in the shaft of a endoscopic grasper and a needle driver. One sensor is located at the distal end of the shaft while the second sensor is located at the proximal end of the shaft. The placement of these sensors does not impede the functionally of the instrument. Since the sensors are located inside the shaft there are no sealing issues between the valve of the trocar and the instrument. We devised a peg transfer training task in accordance to validated training procedures, and tested our system on its ability to differentiate between the expert surgeon and the novices, based on a set of performance metrics. These performance metrics: motion smoothness, total path length, and time to completion, are derived from the kinematics of the instrument. An affine combination of the above mentioned metrics is provided to give a general score for the training performance. Clear differentiation between the expert surgeons and the novice trainees is visible in the test results. Strictly kinematics based performance metrics can be used to evaluate the training progress of MIS trainees in the context of UCLA - LTS.

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

PubMed

Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

2017-12-01

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

Analysis of Dependencies and Impacts of Metroplex Operations

NASA Technical Reports Server (NTRS)

DeLaurentis, Daniel A.; Ayyalasomayajula, Sricharan

2010-01-01

This report documents research performed by Purdue University under subcontract to the George Mason University (GMU) for the Metroplex Operations effort sponsored by NASA's Airportal Project. Purdue University conducted two tasks in support of the larger efforts led by GMU: a) a literature review on metroplex operations followed by identification and analysis of metroplex dependencies, and b) the analysis of impacts of metroplex operations on the larger U.S. domestic airline service network. The tasks are linked in that the ultimate goal is an understanding of the role of dependencies among airports in a metroplex in causing delays both locally and network-wide. The Purdue team has formulated a system-of-systems framework to analyze metroplex dependencies (including simple metrics to quantify them) and develop compact models to predict delays based on network structure. These metrics and models were developed to provide insights for planners to formulate tailored policies and operational strategies that streamline metroplex operations and mitigate delays and congestion.

The singer's voice range profile: female professional opera soloists.

PubMed

Lamarche, Anick; Ternström, Sten; Pabon, Peter

2010-07-01

This work concerns the collection of 30 voice range profiles (VRPs) of female operatic voice. We address the questions: Is there a need for a singer's protocol in VRP acquisition? Are physiological measurements sufficient or should the measurement of performance capabilities also be included? Can we address the female singing voice in general or is there a case for categorizing voices when studying phonetographic data? Subjects performed a series of structured tasks involving both standard speech voice protocols and additional singing tasks. Singers also completed an extensive questionnaire. Physiological VRPs differ from performance VRPs. Two new VRP metrics, the voice area above a defined level threshold and the dynamic range independent from the fundamental frequency (F(0)), were found to be useful in the analysis of singer VRPs. Task design had no effect on performance VRP outcomes. Voice category differences were mainly attributable to phonation frequency-based information. Results support the clinical importance of addressing the vocal instrument as it is used in performance. Equally important is the elaboration of a protocol suitable for the singing voice. The given context and instructions can be more important than task design for performance VRPs. Yet, for physiological VRP recordings, task design remains critical. Both types of VRPs are suggested for a singer's voice evaluation. Copyright (c) 2010 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Affective mentalizing and brain activity at rest in the behavioral variant of frontotemporal dementia

PubMed Central

Caminiti, Silvia P.; Canessa, Nicola; Cerami, Chiara; Dodich, Alessandra; Crespi, Chiara; Iannaccone, Sandro; Marcone, Alessandra; Falini, Andrea; Cappa, Stefano F.

2015-01-01

Background bvFTD patients display an impairment in the attribution of cognitive and affective states to others, reflecting GM atrophy in brain regions associated with social cognition, such as amygdala, superior temporal cortex and posterior insula. Distinctive patterns of abnormal brain functioning at rest have been reported in bvFTD, but their relationship with defective attribution of affective states has not been investigated. Objective To investigate the relationship among resting-state brain activity, gray matter (GM) atrophy and the attribution of mental states in the behavioral variant of fronto-temporal degeneration (bvFTD). Methods We compared 12 bvFTD patients with 30 age- and education-matched healthy controls on a) performance in a task requiring the attribution of affective vs. cognitive mental states; b) metrics of resting-state activity in known functional networks; and c) the relationship between task-performances and resting-state metrics. In addition, we assessed a connection between abnormal resting-state metrics and GM atrophy. Results Compared with controls, bvFTD patients showed a reduction of intra-network coherent activity in several components, as well as decreased strength of activation in networks related to attentional processing. Anomalous resting-state activity involved networks which also displayed a significant reduction of GM density. In patients, compared with controls, higher affective mentalizing performance correlated with stronger functional connectivity between medial prefrontal sectors of the default-mode and attentional/performance monitoring networks, as well as with increased coherent activity in components of the executive, sensorimotor and fronto-limbic networks. Conclusions Some of the observed effects may reflect specific compensatory mechanisms for the atrophic changes involving regions in charge of affective mentalizing. The analysis of specific resting-state networks thus highlights an intermediate level of analysis between abnormal brain structure and impaired behavioral performance in bvFTD, reflecting both dysfunction and compensation mechanisms. PMID:26594631

Prediction of user preference over shared-control paradigms for a robotic wheelchair.

PubMed

Erdogan, Ahmetcan; Argall, Brenna D

2017-07-01

The design of intelligent powered wheelchairs has traditionally focused heavily on providing effective and efficient navigation assistance. Significantly less attention has been given to the end-user's preference between different assistance paradigms. It is possible to include these subjective evaluations in the design process, for example by soliciting feedback in post-experiment questionnaires. However, constantly querying the user for feedback during real-world operation is not practical. In this paper, we present a model that correlates objective performance metrics and subjective evaluations of autonomous wheelchair control paradigms. Using off-the-shelf machine learning techniques, we show that it is possible to build a model that can predict the most preferred shared-control method from task execution metrics such as effort, safety, performance and utilization. We further characterize the relative contributions of each of these metrics to the individual choice of most preferred assistance paradigm. Our evaluation includes Spinal Cord Injured (SCI) and uninjured subject groups. The results show that our proposed correlation model enables the continuous tracking of user preference and offers the possibility of autonomy that is customized to each user.

Five-way smoking status classification using text hot-spot identification and error-correcting output codes.

PubMed

Cohen, Aaron M

2008-01-01

We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2b2 task organizers, using micro- and macro-averaged F1 as the primary performance metric. Our best performing system achieved a micro-F1 of 0.9000 on the test collection, equivalent to the best performing system submitted to the i2b2 challenge. Hot-spot identification, zero-vector filtering, classifier weighting, and error correcting output coding contributed additively to increased performance, with hot-spot identification having by far the largest positive effect. High performance on automatic identification of patient smoking status from discharge summaries is achievable with the efficient and straightforward machine learning techniques studied here.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications.

PubMed

Le, Duc V; Nguyen, Thuong; Scholten, Hans; Havinga, Paul J M

2017-11-29

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring.

Symbiotic Sensing for Energy-Intensive Tasks in Large-Scale Mobile Sensing Applications

PubMed Central

Scholten, Hans; Havinga, Paul J. M.

2017-01-01

Energy consumption is a critical performance and user experience metric when developing mobile sensing applications, especially with the significantly growing number of sensing applications in recent years. As proposed a decade ago when mobile applications were still not popular and most mobile operating systems were single-tasking, conventional sensing paradigms such as opportunistic sensing and participatory sensing do not explore the relationship among concurrent applications for energy-intensive tasks. In this paper, inspired by social relationships among living creatures in nature, we propose a symbiotic sensing paradigm that can conserve energy, while maintaining equivalent performance to existing paradigms. The key idea is that sensing applications should cooperatively perform common tasks to avoid acquiring the same resources multiple times. By doing so, this sensing paradigm executes sensing tasks with very little extra resource consumption and, consequently, extends battery life. To evaluate and compare the symbiotic sensing paradigm with the existing ones, we develop mathematical models in terms of the completion probability and estimated energy consumption. The quantitative evaluation results using various parameters obtained from real datasets indicate that symbiotic sensing performs better than opportunistic sensing and participatory sensing in large-scale sensing applications, such as road condition monitoring, air pollution monitoring, and city noise monitoring. PMID:29186037

Subrandom methods for multidimensional nonuniform sampling.

PubMed

Worley, Bradley

2016-08-01

Methods of nonuniform sampling that utilize pseudorandom number sequences to select points from a weighted Nyquist grid are commonplace in biomolecular NMR studies, due to the beneficial incoherence introduced by pseudorandom sampling. However, these methods require the specification of a non-arbitrary seed number in order to initialize a pseudorandom number generator. Because the performance of pseudorandom sampling schedules can substantially vary based on seed number, this can complicate the task of routine data collection. Approaches such as jittered sampling and stochastic gap sampling are effective at reducing random seed dependence of nonuniform sampling schedules, but still require the specification of a seed number. This work formalizes the use of subrandom number sequences in nonuniform sampling as a means of seed-independent sampling, and compares the performance of three subrandom methods to their pseudorandom counterparts using commonly applied schedule performance metrics. Reconstruction results using experimental datasets are also provided to validate claims made using these performance metrics. Copyright © 2016 Elsevier Inc. All rights reserved.

A novel onset detection technique for brain-computer interfaces using sound-production related cognitive tasks in simulated-online system

NASA Astrophysics Data System (ADS)

Song, YoungJae; Sepulveda, Francisco

2017-02-01

Objective. Self-paced EEG-based BCIs (SP-BCIs) have traditionally been avoided due to two sources of uncertainty: (1) precisely when an intentional command is sent by the brain, i.e., the command onset detection problem, and (2) how different the intentional command is when compared to non-specific (or idle) states. Performance evaluation is also a problem and there are no suitable standard metrics available. In this paper we attempted to tackle these issues. Approach. Self-paced covert sound-production cognitive tasks (i.e., high pitch and siren-like sounds) were used to distinguish between intentional commands (IC) and idle states. The IC states were chosen for their ease of execution and negligible overlap with common cognitive states. Band power and a digital wavelet transform were used for feature extraction, and the Davies-Bouldin index was used for feature selection. Classification was performed using linear discriminant analysis. Main results. Performance was evaluated under offline and simulated-online conditions. For the latter, a performance score called true-false-positive (TFP) rate, ranging from 0 (poor) to 100 (perfect), was created to take into account both classification performance and onset timing errors. Averaging the results from the best performing IC task for all seven participants, an 77.7% true-positive (TP) rate was achieved in offline testing. For simulated-online analysis the best IC average TFP score was 76.67% (87.61% TP rate, 4.05% false-positive rate). Significance. Results were promising when compared to previous IC onset detection studies using motor imagery, in which best TP rates were reported as 72.0% and 79.7%, and which, crucially, did not take timing errors into account. Moreover, based on our literature review, there is no previous covert sound-production onset detection system for spBCIs. Results showed that the proposed onset detection technique and TFP performance metric have good potential for use in SP-BCIs.

Enhanced timing abilities in percussionists generalize to rhythms without a musical beat.

PubMed

Cameron, Daniel J; Grahn, Jessica A

2014-01-01

The ability to entrain movements to music is arguably universal, but it is unclear how specialized training may influence this. Previous research suggests that percussionists have superior temporal precision in perception and production tasks. Such superiority may be limited to temporal sequences that resemble real music or, alternatively, may generalize to musically implausible sequences. To test this, percussionists and nonpercussionists completed two tasks that used rhythmic sequences varying in musical plausibility. In the beat tapping task, participants tapped with the beat of a rhythmic sequence over 3 stages: finding the beat (as an initial sequence played), continuation of the beat (as a second sequence was introduced and played simultaneously), and switching to a second beat (the initial sequence finished, leaving only the second). The meters of the two sequences were either congruent or incongruent, as were their tempi (minimum inter-onset intervals). In the rhythm reproduction task, participants reproduced rhythms of four types, ranging from high to low musical plausibility: Metric simple rhythms induced a strong sense of the beat, metric complex rhythms induced a weaker sense of the beat, nonmetric rhythms had no beat, and jittered nonmetric rhythms also had no beat as well as low temporal predictability. For both tasks, percussionists performed more accurately than nonpercussionists. In addition, both groups were better with musically plausible than implausible conditions. Overall, the percussionists' superior abilities to entrain to, and reproduce, rhythms generalized to musically implausible sequences.

Comparing Resource Adequacy Metrics and Their Influence on Capacity Value: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ibanez, E.; Milligan, M.

2014-04-01

Traditional probabilistic methods have been used to evaluate resource adequacy. The increasing presence of variable renewable generation in power systems presents a challenge to these methods because, unlike thermal units, variable renewable generation levels change over time because they are driven by meteorological events. Thus, capacity value calculations for these resources are often performed to simple rules of thumb. This paper follows the recommendations of the North American Electric Reliability Corporation?s Integration of Variable Generation Task Force to include variable generation in the calculation of resource adequacy and compares different reliability metrics. Examples are provided using the Western Interconnection footprintmore » under different variable generation penetrations.« less

Getting it right the first time: predicted performance guarantees from the analysis of emergent behavior in autonomous and semi-autonomous systems

NASA Astrophysics Data System (ADS)

Arkin, Ronald C.; Lyons, Damian; Shu, Jiang; Nirmal, Prem; Zafar, Munzir

2012-06-01

A crucially important aspect for mission-critical robotic operations is ensuring as best as possible that an autonomous system be able to complete its task. In a project for the Defense Threat Reduction Agency (DTRA) we are developing methods to provide such guidance, specifically for counter-Weapons of Mass Destruction (C-WMD) missions. In this paper, we describe the scenarios under consideration, the performance measures and metrics being developed, and an outline of the mechanisms for providing performance guarantees.

Empirical Analysis of Human Capital, Learning Culture, and Knowledge Management as Antecedents to Organizational Performance: Theoretical and Practical Implications for Logistics Readiness Officer Force Development

DTIC Science & Technology

2014-03-27

Much of the DoD’s force shaping problems in the active duty military stem from the way in which it chose to absorb the force reductions at the end...indicated the need for more joint oriented education and training to help them in the performance of their primary duties. CLL 016 (Joint Logistics... CLL 054 (Joint Task Force Port Opening) and CLL 055 (Joint Deployment and Distribution Performance Metrics Framework) all received high potential

Determining optimal parameters of the self-referent encoding task: A large-scale examination of self-referent cognition and depression.

PubMed

Dainer-Best, Justin; Lee, Hae Yeon; Shumake, Jason D; Yeager, David S; Beevers, Christopher G

2018-06-07

Although the self-referent encoding task (SRET) is commonly used to measure self-referent cognition in depression, many different SRET metrics can be obtained. The current study used best subsets regression with cross-validation and independent test samples to identify the SRET metrics most reliably associated with depression symptoms in three large samples: a college student sample (n = 572), a sample of adults from Amazon Mechanical Turk (n = 293), and an adolescent sample from a school field study (n = 408). Across all 3 samples, SRET metrics associated most strongly with depression severity included number of words endorsed as self-descriptive and rate of accumulation of information required to decide whether adjectives were self-descriptive (i.e., drift rate). These metrics had strong intratask and split-half reliability and high test-retest reliability across a 1-week period. Recall of SRET stimuli and traditional reaction time (RT) metrics were not robustly associated with depression severity. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Assessing Arthroscopic Skills Using Wireless Elbow-Worn Motion Sensors.

PubMed

Kirby, Georgina S J; Guyver, Paul; Strickland, Louise; Alvand, Abtin; Yang, Guang-Zhong; Hargrove, Caroline; Lo, Benny P L; Rees, Jonathan L

2015-07-01

Assessment of surgical skill is a critical component of surgical training. Approaches to assessment remain predominantly subjective, although more objective measures such as Global Rating Scales are in use. This study aimed to validate the use of elbow-worn, wireless, miniaturized motion sensors to assess the technical skill of trainees performing arthroscopic procedures in a simulated environment. Thirty participants were divided into three groups on the basis of their surgical experience: novices (n = 15), intermediates (n = 10), and experts (n = 5). All participants performed three standardized tasks on an arthroscopic virtual reality simulator while wearing wireless wrist and elbow motion sensors. Video output was recorded and a validated Global Rating Scale was used to assess performance; dexterity metrics were recorded from the simulator. Finally, live motion data were recorded via Bluetooth from the wireless wrist and elbow motion sensors and custom algorithms produced an arthroscopic performance score. Construct validity was demonstrated for all tasks, with Global Rating Scale scores and virtual reality output metrics showing significant differences between novices, intermediates, and experts (p < 0.001). The correlation of the virtual reality path length to the number of hand movements calculated from the wireless sensors was very high (p < 0.001). A comparison of the arthroscopic performance score levels with virtual reality output metrics also showed highly significant differences (p < 0.01). Comparisons of the arthroscopic performance score levels with the Global Rating Scale scores showed strong and highly significant correlations (p < 0.001) for both sensor locations, but those of the elbow-worn sensors were stronger and more significant (p < 0.001) than those of the wrist-worn sensors. A new wireless assessment of surgical performance system for objective assessment of surgical skills has proven valid for assessing arthroscopic skills. The elbow-worn sensors were shown to achieve an accurate assessment of surgical dexterity and performance. The validation of an entirely objective assessment of arthroscopic skill with wireless elbow-worn motion sensors introduces, for the first time, a feasible assessment system for the live operating theater with the added potential to be applied to other surgical and interventional specialties. Copyright © 2015 by The Journal of Bone and Joint Surgery, Incorporated.

A Correlation Between Quality Management Metrics and Technical Performance Measurement

DTIC Science & Technology

2007-03-01

Engineering Working Group SME Subject Matter Expert SoS System of Systems SPI Schedule performance Index SSEI System of Systems Engineering and...and stated as such [Q, M , M &G]. The QMM equation is given by: 12 QMM=0.92RQM+0.67EPM+0.55RKM+1.86PM, where: RGM is the requirements management...schedule. Now if corrective action is not taken, the project/task will be completed behind schedule and over budget. m . As well as the derived

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance.

PubMed

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies.

Structure and Topology Dynamics of Hyper-Frequency Networks during Rest and Auditory Oddball Performance

PubMed Central

Müller, Viktor; Perdikis, Dionysios; von Oertzen, Timo; Sleimen-Malkoun, Rita; Jirsa, Viktor; Lindenberger, Ulman

2016-01-01

Resting-state and task-related recordings are characterized by oscillatory brain activity and widely distributed networks of synchronized oscillatory circuits. Electroencephalographic recordings (EEG) were used to assess network structure and network dynamics during resting state with eyes open and closed, and auditory oddball performance through phase synchronization between EEG channels. For this assessment, we constructed a hyper-frequency network (HFN) based on within- and cross-frequency coupling (WFC and CFC, respectively) at 10 oscillation frequencies ranging between 2 and 20 Hz. We found that CFC generally differentiates between task conditions better than WFC. CFC was the highest during resting state with eyes open. Using a graph-theoretical approach (GTA), we found that HFNs possess small-world network (SWN) topology with a slight tendency to random network characteristics. Moreover, analysis of the temporal fluctuations of HFNs revealed specific network topology dynamics (NTD), i.e., temporal changes of different graph-theoretical measures such as strength, clustering coefficient, characteristic path length (CPL), local, and global efficiency determined for HFNs at different time windows. The different topology metrics showed significant differences between conditions in the mean and standard deviation of these metrics both across time and nodes. In addition, using an artificial neural network approach, we found stimulus-related dynamics that varied across the different network topology metrics. We conclude that functional connectivity dynamics (FCD), or NTD, which was found using the HFN approach during rest and stimulus processing, reflects temporal and topological changes in the functional organization and reorganization of neuronal cell assemblies. PMID:27799906

Photometer Performance Assessment in TESS SPOC Pipeline

NASA Astrophysics Data System (ADS)

Li, Jie; Caldwell, Douglas A.; Jenkins, Jon Michael; Twicken, Joseph D.; Wohler, Bill; Chen, Xiaolan; Rose, Mark; TESS Science Processing Operations Center

2018-06-01

This poster describes the Photometer Performance Assessment (PPA) software component in the Transiting Exoplanet Survey Satellite (TESS) Science Processing Operations Center (SPOC) pipeline, which is developed based on the Kepler science pipeline. The PPA component performs two tasks: the first task is to assess the health and performance of the instrument based on the science data sets collected during each observation sector, identifying out of bounds conditions and generating alerts. The second is to combine the astrometric data collected for each CCD readout channel to construct a high fidelity record of the pointing history for each of the 4 cameras and an attitude solution for the TESS spacecraft for each 2-min data collection interval. PPA is implemented with multiple pipeline modules: PPA Metrics Determination (PMD), PMD Aggregator (PAG), and PPA Attitude Determination (PAD). The TESS Mission is funded by NASA's Science Mission Directorate. The SPOC is managed and operated by NASA Ames Research Center.

Optimal SSN Tasking to Enhance Real-time Space Situational Awareness

NASA Astrophysics Data System (ADS)

Ferreira, J., III; Hussein, I.; Gerber, J.; Sivilli, R.

2016-09-01

Space Situational Awareness (SSA) is currently constrained by an overwhelming number of resident space objects (RSOs) that need to be tracked and the amount of data these observations produce. The Joint Centralized Autonomous Tasking System (JCATS) is an autonomous, net-centric tool that approaches these SSA concerns from an agile, information-based stance. Finite set statistics and stochastic optimization are used to maintain an RSO catalog and develop sensor tasking schedules based on operator configured, state information-gain metrics to determine observation priorities. This improves the efficiency of sensors to target objects as awareness changes and new information is needed, not at predefined frequencies solely. A net-centric, service-oriented architecture (SOA) allows for JCATS integration into existing SSA systems. Testing has shown operationally-relevant performance improvements and scalability across multiple types of scenarios and against current sensor tasking tools.

Quantitative evaluation of muscle synergy models: a single-trial task decoding approach

PubMed Central

Delis, Ioannis; Berret, Bastien; Pozzo, Thierry; Panzeri, Stefano

2013-01-01

Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements. Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies encodes task-discriminating variations of muscle activity in individual trials. To address this question, here we conceive and develop a novel computational framework to evaluate muscle synergy decompositions in task space. Unlike previous methods considering the total variance of muscle patterns (VAF based metrics), our approach focuses on variance discriminating execution of different tasks. The procedure is based on single-trial task decoding from muscle synergy activation features. The task decoding based metric evaluates quantitatively the mapping between synergy recruitment and task identification and automatically determines the minimal number of synergies that captures all the task-discriminating variability in the synergy activations. In this paper, we first validate the method on plausibly simulated EMG datasets. We then show that it can be applied to different types of muscle synergy decomposition and illustrate its applicability to real data by using it for the analysis of EMG recordings during an arm pointing task. We find that time-varying and synchronous synergies with similar number of parameters are equally efficient in task decoding, suggesting that in this experimental paradigm they are equally valid representations of muscle synergies. Overall, these findings stress the effectiveness of the decoding metric in systematically assessing muscle synergy decompositions in task space. PMID:23471195

Spatial frequency dependence of target signature for infrared performance modeling

NASA Astrophysics Data System (ADS)

Du Bosq, Todd; Olson, Jeffrey

2011-05-01

The standard model used to describe the performance of infrared imagers is the U.S. Army imaging system target acquisition model, based on the targeting task performance metric. The model is characterized by the resolution and sensitivity of the sensor as well as the contrast and task difficulty of the target set. The contrast of the target is defined as a spatial average contrast. The model treats the contrast of the target set as spatially white, or constant, over the bandlimit of the sensor. Previous experiments have shown that this assumption is valid under normal conditions and typical target sets. However, outside of these conditions, the treatment of target signature can become the limiting factor affecting model performance accuracy. This paper examines target signature more carefully. The spatial frequency dependence of the standard U.S. Army RDECOM CERDEC Night Vision 12 and 8 tracked vehicle target sets is described. The results of human perception experiments are modeled and evaluated using both frequency dependent and independent target signature definitions. Finally the function of task difficulty and its relationship to a target set is discussed.

The Importance of Visual Experience, Gender, and Emotion in the Assessment of an Assistive Tactile Mouse.

PubMed

Brayda, Luca; Campus, Claudio; Memeo, Mariacarla; Lucagrossi, Laura

2015-01-01

Tactile maps are efficient tools to improve spatial understanding and mobility skills of visually impaired people. Their limited adaptability can be compensated with haptic devices which display graphical information, but their assessment is frequently limited to performance-based metrics only which can hide potential spatial abilities in O&M protocols. We assess a low-tech tactile mouse able to deliver three-dimensional content considering how performance, mental workload, behavior, and anxiety status vary with task difficulty and gender in congenitally blind, late blind, and sighted subjects. Results show that task difficulty coherently modulates the efficiency and difficulty to build mental maps, regardless of visual experience. Although exhibiting attitudes that were similar and gender-independent, the females had lower performance and higher cognitive load, especially when congenitally blind. All groups showed a significant decrease in anxiety after using the device. Tactile graphics with our device seems therefore to be applicable with different visual experiences, with no negative emotional consequences of mentally demanding spatial tasks. Going beyond performance-based assessment, our methodology can help with better targeting technological solutions in orientation and mobility protocols.

Correlative feature analysis on FFDM

PubMed Central

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-01-01

Identifying the corresponding images of a lesion in different views is an essential step in improving the diagnostic ability of both radiologists and computer-aided diagnosis (CAD) systems. Because of the nonrigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this pilot study, we present a computerized framework that differentiates between corresponding images of the same lesion in different views and noncorresponding images, i.e., images of different lesions. A dual-stage segmentation method, which employs an initial radial gradient index (RGI) based segmentation and an active contour model, is applied to extract mass lesions from the surrounding parenchyma. Then various lesion features are automatically extracted from each of the two views of each lesion to quantify the characteristics of density, size, texture and the neighborhood of the lesion, as well as its distance to the nipple. A two-step scheme is employed to estimate the probability that the two lesion images from different mammographic views are of the same physical lesion. In the first step, a correspondence metric for each pairwise feature is estimated by a Bayesian artificial neural network (BANN). Then, these pairwise correspondence metrics are combined using another BANN to yield an overall probability of correspondence. Receiver operating characteristic (ROC) analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing corresponding pairs from noncorresponding pairs. Using a FFDM database with 123 corresponding image pairs and 82 noncorresponding pairs, the distance feature yielded an area under the ROC curve (AUC) of 0.81±0.02 with leave-one-out (by physical lesion) evaluation, and the feature metric subset, which included distance, gradient texture, and ROI-based correlation, yielded an AUC of 0.87±0.02. The improvement by using multiple feature metrics was statistically significant compared to single feature performance. PMID:19175108

78 FR 24817 - Visual-Manual NHTSA Driver Distraction Guidelines for In-Vehicle Electronic Devices

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-26

...The National Highway Traffic Safety Administration (NHTSA) is concerned about the effects of distraction on motor vehicle safety due to drivers' use of electronic devices. Consequently, NHTSA is issuing nonbinding, voluntary Driver Distraction Guidelines (NHTSA Guidelines) to promote safety by discouraging the introduction of excessively distracting devices in vehicles. This notice announces the issuance of the final version of the first phase of the NHTSA Guidelines. This first phase applies to original equipment (OE) in-vehicle electronic devices used by the driver to perform secondary tasks (communications, entertainment, information gathering, navigation tasks, etc. are considered secondary tasks) through visual-manual means (i.e., the driver looks at a device, manipulates a device-related control with his or her hand, and/or watches for visual feedback). The NHTSA Guidelines list certain secondary tasks believed by the agency to interfere inherently with a driver's ability to safely control the vehicle. The NHTSA Guidelines recommend that in-vehicle devices be designed so that they cannot be used by the driver to perform these inherently distracting secondary tasks while driving. For all other visual-manual secondary tasks, the NHTSA Guidelines specify a test method for measuring eye glance behavior during those tasks. Eye glance metrics are compared to acceptance criteria to evaluate whether a task interferes too much with driver attention, rendering it unsuitable for a driver to perform while driving. If a task does not meet the acceptance criteria, the NHTSA Guidelines recommend that the task be made inaccessible for performance by the driver while driving. In addition, the NHTSA Guidelines contain several recommendations to limit and reduce the potential for distraction associated with the use of OE in-vehicle electronic devices.

Systematic methods for knowledge acquisition and expert system development

NASA Technical Reports Server (NTRS)

Belkin, Brenda L.; Stengel, Robert F.

1991-01-01

Nine cooperating rule-based systems, collectively called AUTOCREW, were designed to automate functions and decisions associated with a combat aircraft's subsystem. The organization of tasks within each system is described; performance metrics were developed to evaluate the workload of each rule base, and to assess the cooperation between the rule-bases. Each AUTOCREW subsystem is composed of several expert systems that perform specific tasks. AUTOCREW's NAVIGATOR was analyzed in detail to understand the difficulties involved in designing the system and to identify tools and methodologies that ease development. The NAVIGATOR determines optimal navigation strategies from a set of available sensors. A Navigation Sensor Management (NSM) expert system was systematically designed from Kalman filter covariance data; four ground-based, a satellite-based, and two on-board INS-aiding sensors were modeled and simulated to aid an INS. The NSM Expert was developed using the Analysis of Variance (ANOVA) and the ID3 algorithm. Navigation strategy selection is based on an RSS position error decision metric, which is computed from the covariance data. Results show that the NSM Expert predicts position error correctly between 45 and 100 percent of the time for a specified navaid configuration and aircraft trajectory. The NSM Expert adapts to new situations, and provides reasonable estimates of hybrid performance. The systematic nature of the ANOVA/ID3 method makes it broadly applicable to expert system design when experimental or simulation data is available.

Generalized two-dimensional (2D) linear system analysis metrics (GMTF, GDQE) for digital radiography systems including the effect of focal spot, magnification, scatter, and detector characteristics.

PubMed

Jain, Amit; Kuhls-Gilcrist, Andrew T; Gupta, Sandesh K; Bednarek, Daniel R; Rudin, Stephen

2010-03-01

The MTF, NNPS, and DQE are standard linear system metrics used to characterize intrinsic detector performance. To evaluate total system performance for actual clinical conditions, generalized linear system metrics (GMTF, GNNPS and GDQE) that include the effect of the focal spot distribution, scattered radiation, and geometric unsharpness are more meaningful and appropriate. In this study, a two-dimensional (2D) generalized linear system analysis was carried out for a standard flat panel detector (FPD) (194-micron pixel pitch and 600-micron thick CsI) and a newly-developed, high-resolution, micro-angiographic fluoroscope (MAF) (35-micron pixel pitch and 300-micron thick CsI). Realistic clinical parameters and x-ray spectra were used. The 2D detector MTFs were calculated using the new Noise Response method and slanted edge method and 2D focal spot distribution measurements were done using a pin-hole assembly. The scatter fraction, generated for a uniform head equivalent phantom, was measured and the scatter MTF was simulated with a theoretical model. Different magnifications and scatter fractions were used to estimate the 2D GMTF, GNNPS and GDQE for both detectors. Results show spatial non-isotropy for the 2D generalized metrics which provide a quantitative description of the performance of the complete imaging system for both detectors. This generalized analysis demonstrated that the MAF and FPD have similar capabilities at lower spatial frequencies, but that the MAF has superior performance over the FPD at higher frequencies even when considering focal spot blurring and scatter. This 2D generalized performance analysis is a valuable tool to evaluate total system capabilities and to enable optimized design for specific imaging tasks.

Introducing Co-Activation Pattern Metrics to Quantify Spontaneous Brain Network Dynamics

PubMed Central

Chen, Jingyuan E.; Chang, Catie; Greicius, Michael D.; Glover, Gary H.

2015-01-01

Recently, fMRI researchers have begun to realize that the brain's intrinsic network patterns may undergo substantial changes during a single resting state (RS) scan. However, despite the growing interest in brain dynamics, metrics that can quantify the variability of network patterns are still quite limited. Here, we first introduce various quantification metrics based on the extension of co-activation pattern (CAP) analysis, a recently proposed point-process analysis that tracks state alternations at each individual time frame and relies on very few assumptions; then apply these proposed metrics to quantify changes of brain dynamics during a sustained 2-back working memory (WM) task compared to rest. We focus on the functional connectivity of two prominent RS networks, the default-mode network (DMN) and executive control network (ECN). We first demonstrate less variability of global Pearson correlations with respect to the two chosen networks using a sliding-window approach during WM task compared to rest; then we show that the macroscopic decrease in variations in correlations during a WM task is also well characterized by the combined effect of a reduced number of dominant CAPs, increased spatial consistency across CAPs, and increased fractional contributions of a few dominant CAPs. These CAP metrics may provide alternative and more straightforward quantitative means of characterizing brain network dynamics than time-windowed correlation analyses. PMID:25662866

Metrics to assess ecological condition, change, and impacts in sandy beach ecosystems.

PubMed

Schlacher, Thomas A; Schoeman, David S; Jones, Alan R; Dugan, Jenifer E; Hubbard, David M; Defeo, Omar; Peterson, Charles H; Weston, Michael A; Maslo, Brooke; Olds, Andrew D; Scapini, Felicita; Nel, Ronel; Harris, Linda R; Lucrezi, Serena; Lastra, Mariano; Huijbers, Chantal M; Connolly, Rod M

2014-11-01

Complexity is increasingly the hallmark in environmental management practices of sandy shorelines. This arises primarily from meeting growing public demands (e.g., real estate, recreation) whilst reconciling economic demands with expectations of coastal users who have modern conservation ethics. Ideally, shoreline management is underpinned by empirical data, but selecting ecologically-meaningful metrics to accurately measure the condition of systems, and the ecological effects of human activities, is a complex task. Here we construct a framework for metric selection, considering six categories of issues that authorities commonly address: erosion; habitat loss; recreation; fishing; pollution (litter and chemical contaminants); and wildlife conservation. Possible metrics were scored in terms of their ability to reflect environmental change, and against criteria that are widely used for judging the performance of ecological indicators (i.e., sensitivity, practicability, costs, and public appeal). From this analysis, four types of broadly applicable metrics that also performed very well against the indicator criteria emerged: 1.) traits of bird populations and assemblages (e.g., abundance, diversity, distributions, habitat use); 2.) breeding/reproductive performance sensu lato (especially relevant for birds and turtles nesting on beaches and in dunes, but equally applicable to invertebrates and plants); 3.) population parameters and distributions of vertebrates associated primarily with dunes and the supralittoral beach zone (traditionally focused on birds and turtles, but expandable to mammals); 4.) compound measurements of the abundance/cover/biomass of biota (plants, invertebrates, vertebrates) at both the population and assemblage level. Local constraints (i.e., the absence of birds in highly degraded urban settings or lack of dunes on bluff-backed beaches) and particular issues may require alternatives. Metrics - if selected and applied correctly - provide empirical evidence of environmental condition and change, but often do not reflect deeper environmental values per se. Yet, values remain poorly articulated for many beach systems; this calls for a comprehensive identification of environmental values and the development of targeted programs to conserve these values on sandy shorelines globally. Copyright © 2014 Elsevier Ltd. All rights reserved.

Data-driven management using quantitative metric and automatic auditing program (QMAP) improves consistency of radiation oncology processes.

PubMed

Yu, Naichang; Xia, Ping; Mastroianni, Anthony; Kolar, Matthew D; Chao, Samuel T; Greskovich, John F; Suh, John H

Process consistency in planning and delivery of radiation therapy is essential to maintain patient safety and treatment quality and efficiency. Ensuring the timely completion of each critical clinical task is one aspect of process consistency. The purpose of this work is to report our experience in implementing a quantitative metric and automatic auditing program (QMAP) with a goal of improving the timely completion of critical clinical tasks. Based on our clinical electronic medical records system, we developed a software program to automatically capture the completion timestamp of each critical clinical task while providing frequent alerts of potential delinquency. These alerts were directed to designated triage teams within a time window that would offer an opportunity to mitigate the potential for late completion. Since July 2011, 18 metrics were introduced in our clinical workflow. We compared the delinquency rates for 4 selected metrics before the implementation of the metric with the delinquency rate of 2016. One-tailed Student t test was used for statistical analysis RESULTS: With an average of 150 daily patients on treatment at our main campus, the late treatment plan completion rate and late weekly physics check were reduced from 18.2% and 8.9% in 2011 to 4.2% and 0.1% in 2016, respectively (P < .01). The late weekly on-treatment physician visit rate was reduced from 7.2% in 2012 to <1.6% in 2016. The yearly late cone beam computed tomography review rate was reduced from 1.6% in 2011 to <0.1% in 2016. QMAP is effective in reducing late completions of critical tasks, which can positively impact treatment quality and patient safety by reducing the potential for errors resulting from distractions, interruptions, and rush in completion of critical tasks. Copyright © 2016 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

EEG amplitude modulation analysis for semi-automated diagnosis of Alzheimer's disease

NASA Astrophysics Data System (ADS)

Falk, Tiago H.; Fraga, Francisco J.; Trambaiolli, Lucas; Anghinah, Renato

2012-12-01

Recent experimental evidence has suggested a neuromodulatory deficit in Alzheimer's disease (AD). In this paper, we present a new electroencephalogram (EEG) based metric to quantitatively characterize neuromodulatory activity. More specifically, the short-term EEG amplitude modulation rate-of-change (i.e., modulation frequency) is computed for five EEG subband signals. To test the performance of the proposed metric, a classification task was performed on a database of 32 participants partitioned into three groups of approximately equal size: healthy controls, patients diagnosed with mild AD, and those with moderate-to-severe AD. To gauge the benefits of the proposed metric, performance results were compared with those obtained using EEG spectral peak parameters which were recently shown to outperform other conventional EEG measures. Using a simple feature selection algorithm based on area-under-the-curve maximization and a support vector machine classifier, the proposed parameters resulted in accuracy gains, relative to spectral peak parameters, of 21.3% when discriminating between the three groups and by 50% when mild and moderate-to-severe groups were merged into one. The preliminary findings reported herein provide promising insights that automated tools may be developed to assist physicians in very early diagnosis of AD as well as provide researchers with a tool to automatically characterize cross-frequency interactions and their changes with disease.

Developing a Measurement for Task Complexity in Flight.

PubMed

Zheng, Yiyuan; Lu, Yanyu; Wang, Zhen; Huang, Dan; Fu, Shan

2015-08-01

Task complexity is regarded as an essential metric that is related to a pilot's performance and workload. Normally, pilots follow Standard Operating Procedures (SOPs) during a flight. In this study, we developed a measurement named Task Complexity in Flight (TCIF) to represent the task complexity in the SOPs. The TCIF measurement combined four complexity components into one index: actions logic complexity (ALC), actions size complexity (ASC), information control exchange complexity (ICEC), and control mode complexity (CMC).To verify the measurement, we calculated 11 tasks during the takeoff and landing phases from the SOPs, and invited 10 pilots to perform the same tasks in a flight simulator. After flight, the TCIF results were compared with two workload measurements: the Bedford scale and heart rate. The results of TCIF and the 4 components of the 11 tasks were calculated. Further, the TCIF results showed a significant correlation with the Bedford scores (R=0.851) and were also consistent with the difference in heart rate (R=0.816). Therefore, with the increased TCIF results, both the Bedford scale and the difference in heart rate increased. TCIF was proposed based on the flight operating conditions. Although additional studies of TCIF are necessary, the results of this study suggest this measurement could effectively indicate task complexity in flight, and could also be used to guide pilot training and task allocation on the flight deck.

Numerical distance effect size is a poor metric of approximate number system acuity.

PubMed

Chesney, Dana

2018-04-12

Individual differences in the ability to compare and evaluate nonsymbolic numerical magnitudes-approximate number system (ANS) acuity-are emerging as an important predictor in many research areas. Unfortunately, recent empirical studies have called into question whether a historically common ANS-acuity metric-the size of the numerical distance effect (NDE size)-is an effective measure of ANS acuity. NDE size has been shown to frequently yield divergent results from other ANS-acuity metrics. Given these concerns and the measure's past popularity, it behooves us to question whether the use of NDE size as an ANS-acuity metric is theoretically supported. This study seeks to address this gap in the literature by using modeling to test the basic assumption underpinning use of NDE size as an ANS-acuity metric: that larger NDE size indicates poorer ANS acuity. This assumption did not hold up under test. Results demonstrate that the theoretically ideal relationship between NDE size and ANS acuity is not linear, but rather resembles an inverted J-shaped distribution, with the inflection points varying based on precise NDE task methodology. Thus, depending on specific methodology and the distribution of ANS acuity in the tested population, positive, negative, or null correlations between NDE size and ANS acuity could be predicted. Moreover, peak NDE sizes would be found for near-average ANS acuities on common NDE tasks. This indicates that NDE size has limited and inconsistent utility as an ANS-acuity metric. Past results should be interpreted on a case-by-case basis, considering both specifics of the NDE task and expected ANS acuity of the sampled population.

Sleep restriction and cognitive load affect performance on a simulated marksmanship task.

PubMed

Smith, Carl D; Cooper, Adam D; Merullo, Donna J; Cohen, Bruce S; Heaton, Kristin J; Claro, Pedro J; Smith, Tracey

2017-11-24

Sleep restriction degrades cognitive and motor performance, which can adversely impact job performance and increase the risk of accidents. Military personnel are prone to operating under sleep restriction, and previous work suggests that military marksmanship may be negatively affected under such conditions. Results of these studies, however, are mixed and have often incorporated additional stressors (e.g. energy restriction) beyond sleep restriction. Moreover, few studies have investigated how the degree of difficulty of a marksmanship task impacts performance following sleep restriction. The purpose of the current experiment was to study the effects of sleep restriction on marksmanship while minimizing the potential influence of other forms of stress. A friend-foe discrimination challenge with greater or lesser degrees of complexity (high versus low load) was used as the primary marksmanship task. Active duty Soldiers were recruited, and allowed 2 h of sleep every 24 h over a 72-h testing period. Marksmanship tasks, cognitive assessment metrics and the NASA-Task Load Index were administered daily. Results indicated that reaction times to shoot foe targets and signal friendly targets slowed over time. In addition, the ability to correctly discriminate between friend and foe targets significantly decreased in the high-cognitive-load condition over time despite shot accuracy remaining stable. The NASA-Task Load Index revealed that, although marksmanship performance degraded, participants believed their performance did not change over time. These results further characterize the consequences of sleep restriction on marksmanship performance and the perception of performance, and reinforce the importance of adequate sleep among service members when feasible. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Utility functions and resource management in an oversubscribed heterogeneous computing environment

DOE PAGES

Khemka, Bhavesh; Friese, Ryan; Briceno, Luis Diego; ...

2014-09-26

We model an oversubscribed heterogeneous computing system where tasks arrive dynamically and a scheduler maps the tasks to machines for execution. The environment and workloads are based on those being investigated by the Extreme Scale Systems Center at Oak Ridge National Laboratory. Utility functions that are designed based on specifications from the system owner and users are used to create a metric for the performance of resource allocation heuristics. Each task has a time-varying utility (importance) that the enterprise will earn based on when the task successfully completes execution. We design multiple heuristics, which include a technique to drop lowmore » utility-earning tasks, to maximize the total utility that can be earned by completing tasks. The heuristics are evaluated using simulation experiments with two levels of oversubscription. The results show the benefit of having fast heuristics that account for the importance of a task and the heterogeneity of the environment when making allocation decisions in an oversubscribed environment. Furthermore, the ability to drop low utility-earning tasks allow the heuristics to tolerate the high oversubscription as well as earn significant utility.« less

Laparoscopic baseline ability assessment by virtual reality.

PubMed

Madan, Atul K; Frantzides, Constantine T; Sasso, Lisa M

2005-02-01

Assessment of any surgical skill is time-consuming and difficult. Currently, there are no accepted metrics for most surgical skills, especially laparoscopic skills. Virtual reality has been utilized for laparoscopic training of surgical residents. Our hypothesis is that this technology can be utilized for laparoscopic ability metrics. This study involved medical students with no previous laparoscopic experience. All students were taken into a porcine laboratory in order to assess two operative tasks (measuring a piece of bowel and placing a piece of bowel into a laparoscopic bag). Then they were taken into an inanimate lab with a Minimally Invasive Surgery Trainer-Virtual Reality (MIST-VR). Each student repeatedly performed one task (placing a virtual reality ball into a receptacle). The students' scores and times from the animate lab were compared with average economy of movement and times from the MIST-VR. The MIST-VR scored both hands individually. Thirty-two first- and second-year medical students were included in the study. There was statistically significant (P < 0.05) correlation between 11 of 16 possible relationships between the virtual reality trainer and operative tasks. While not all of the possible relationships demonstrated statistically significant correlation, the majority of the possible relationships demonstrated statistically significant correlation. Virtual reality may be an avenue for measuring laparoscopic surgical ability.

Asynchronous threat awareness by observer trials using crowd simulation

NASA Astrophysics Data System (ADS)

Dunau, Patrick; Huber, Samuel; Stein, Karin U.; Wellig, Peter

2016-10-01

The last few years showed that a high risk of asynchronous threats is given in every day life. Especially in large crowds a high probability of asynchronous attacks is evident. High observational abilities to detect threats are desirable. Consequently highly trained security and observation personal is needed. This paper evaluates the effectiveness of a training methodology to enhance performance of observation personnel engaging in a specific target identification task. For this purpose a crowd simulation video is utilized. The study first provides a measurement of the base performance before the training sessions. Furthermore a training procedure will be performed. Base performance will then be compared to the after training performance in order to look for a training effect. A thorough evaluation of both the training sessions as well as the overall performance will be done in this paper. A specific hypotheses based metric is used. Results will be discussed in order to provide guidelines for the design of training for observational tasks.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011.

PubMed

Pyysalo, Sampo; Ohta, Tomoko; Rak, Rafal; Sullivan, Dan; Mao, Chunhong; Wang, Chunxia; Sobral, Bruno; Tsujii, Jun'ichi; Ananiadou, Sophia

2012-06-26

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties.

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011

PubMed Central

2012-01-01

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties. PMID:22759456

Automated concept-level information extraction to reduce the need for custom software and rules development.

PubMed

D'Avolio, Leonard W; Nguyen, Thien M; Goryachev, Sergey; Fiore, Louis D

2011-01-01

Despite at least 40 years of promising empirical performance, very few clinical natural language processing (NLP) or information extraction systems currently contribute to medical science or care. The authors address this gap by reducing the need for custom software and rules development with a graphical user interface-driven, highly generalizable approach to concept-level retrieval. A 'learn by example' approach combines features derived from open-source NLP pipelines with open-source machine learning classifiers to automatically and iteratively evaluate top-performing configurations. The Fourth i2b2/VA Shared Task Challenge's concept extraction task provided the data sets and metrics used to evaluate performance. Top F-measure scores for each of the tasks were medical problems (0.83), treatments (0.82), and tests (0.83). Recall lagged precision in all experiments. Precision was near or above 0.90 in all tasks. Discussion With no customization for the tasks and less than 5 min of end-user time to configure and launch each experiment, the average F-measure was 0.83, one point behind the mean F-measure of the 22 entrants in the competition. Strong precision scores indicate the potential of applying the approach for more specific clinical information extraction tasks. There was not one best configuration, supporting an iterative approach to model creation. Acceptable levels of performance can be achieved using fully automated and generalizable approaches to concept-level information extraction. The described implementation and related documentation is available for download.

Quantitative adaptation analytics for assessing dynamic systems of systems: LDRD Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gauthier, John H.; Miner, Nadine E.; Wilson, Michael L.

2015-01-01

Our society is increasingly reliant on systems and interoperating collections of systems, known as systems of systems (SoS). These SoS are often subject to changing missions (e.g., nation- building, arms-control treaties), threats (e.g., asymmetric warfare, terrorism), natural environments (e.g., climate, weather, natural disasters) and budgets. How well can SoS adapt to these types of dynamic conditions? This report details the results of a three year Laboratory Directed Research and Development (LDRD) project aimed at developing metrics and methodologies for quantifying the adaptability of systems and SoS. Work products include: derivation of a set of adaptability metrics, a method for combiningmore » the metrics into a system of systems adaptability index (SoSAI) used to compare adaptability of SoS designs, development of a prototype dynamic SoS (proto-dSoS) simulation environment which provides the ability to investigate the validity of the adaptability metric set, and two test cases that evaluate the usefulness of a subset of the adaptability metrics and SoSAI for distinguishing good from poor adaptability in a SoS. Intellectual property results include three patents pending: A Method For Quantifying Relative System Adaptability, Method for Evaluating System Performance, and A Method for Determining Systems Re-Tasking.« less

Technical Note: Gray tracking in medical color displays-A report of Task Group 196.

PubMed

Badano, Aldo; Wang, Joel; Boynton, Paul; Le Callet, Patrick; Cheng, Wei-Chung; Deroo, Danny; Flynn, Michael J; Matsui, Takashi; Penczek, John; Revie, Craig; Samei, Ehsan; Steven, Peter M; Swiderski, Stan; Van Hoey, Gert; Yamaguchi, Matsuhiro; Hasegawa, Mikio; Nagy, Balázs Vince

2016-07-01

The authors discuss measurement methods and instrumentation useful for the characterization of the gray tracking performance of medical color monitors for diagnostic applications. The authors define gray tracking as the variability in the chromaticity of the gray levels in a color monitor. The authors present data regarding the capability of color measurement instruments with respect to their abilities to measure a target white point corresponding to the CIE Standard Illuminant D65 at different luminance values within the grayscale palette of a medical display. The authors then discuss evidence of significant differences in performance among color measurement instruments currently available for medical physicists to perform calibrations and image quality checks for the consistent representation of color in medical displays. In addition, the authors introduce two metrics for quantifying grayscale chromaticity consistency of gray tracking. The authors' findings show that there is an order of magnitude difference in the accuracy of field and reference instruments. The gray tracking metrics quantify how close the grayscale chromaticity is to the chromaticity of the full white point (equal amounts of red, green, and blue at maximum level) or to consecutive levels (equal values for red, green, and blue), with a lower value representing an improved grayscale tracking performance. An illustrative example of how to calculate and report the gray tracking performance according to the Task Group definitions is provided. The authors' proposed methodology for characterizing the grayscale degradation in chromaticity for color monitors that can be used to establish standards and procedures aiding in the quality control testing of color displays and color measurement instrumentation.

Relational Agreement Measures for Similarity Searching of Cheminformatic Data Sets.

PubMed

Rivera-Borroto, Oscar Miguel; García-de la Vega, José Manuel; Marrero-Ponce, Yovani; Grau, Ricardo

2016-01-01

Research on similarity searching of cheminformatic data sets has been focused on similarity measures using fingerprints. However, nominal scales are the least informative of all metric scales, increasing the tied similarity scores, and decreasing the effectivity of the retrieval engines. Tanimoto's coefficient has been claimed to be the most prominent measure for this task. Nevertheless, this field is far from being exhausted since the computer science no free lunch theorem predicts that "no similarity measure has overall superiority over the population of data sets". We introduce 12 relational agreement (RA) coefficients for seven metric scales, which are integrated within a group fusion-based similarity searching algorithm. These similarity measures are compared to a reference panel of 21 proximity quantifiers over 17 benchmark data sets (MUV), by using informative descriptors, a feature selection stage, a suitable performance metric, and powerful comparison tests. In this stage, RA coefficients perform favourably with repect to the state-of-the-art proximity measures. Afterward, the RA-based method outperform another four nearest neighbor searching algorithms over the same data domains. In a third validation stage, RA measures are successfully applied to the virtual screening of the NCI data set. Finally, we discuss a possible molecular interpretation for these similarity variants.

Selective attrition and intraindividual variability in response time moderate cognitive change.

PubMed

Yao, Christie; Stawski, Robert S; Hultsch, David F; MacDonald, Stuart W S

2016-01-01

Selection of a developmental time metric is useful for understanding causal processes that underlie aging-related cognitive change and for the identification of potential moderators of cognitive decline. Building on research suggesting that time to attrition is a metric sensitive to non-normative influences of aging (e.g., subclinical health conditions), we examined reason for attrition and intraindividual variability (IIV) in reaction time as predictors of cognitive performance. Three hundred and four community dwelling older adults (64-92 years) completed annual assessments in a longitudinal study. IIV was calculated from baseline performance on reaction time tasks. Multilevel models were fit to examine patterns and predictors of cognitive change. We show that time to attrition was associated with cognitive decline. Greater IIV was associated with declines on executive functioning and episodic memory measures. Attrition due to personal health reasons was also associated with decreased executive functioning compared to that of individuals who remained in the study. These findings suggest that time to attrition is a useful metric for representing cognitive change, and reason for attrition and IIV are predictive of non-normative influences that may underlie instances of cognitive loss in older adults.

Selective Attrition and Intraindividual Variability in Response Time Moderate Cognitive Change

PubMed Central

Yao, Christie; Stawski, Robert S.; Hultsch, David F.; MacDonald, Stuart W.S.

2016-01-01

Objectives Selection of a developmental time metric is useful for understanding causal processes that underlie aging-related cognitive change, and for the identification of potential moderators of cognitive decline. Building on research suggesting that time to attrition is a metric sensitive to non-normative influences of aging (e.g., subclinical health conditions), we examined reason for attrition and intraindividual variability (IIV) in reaction time as predictors of cognitive performance. Method Three-hundred and four community dwelling older adults (64-92 years) completed annual assessments in a longitudinal study. IIV was calculated from baseline performance on reaction time tasks. Multilevel models were fit to examine patterns and predictors of cognitive change. Results We show that time to attrition was associated with cognitive decline. Greater IIV was associated with declines on executive functioning and episodic memory measures. Attrition due to personal health reasons was also associated with decreased executive functioning compared to individuals who remained in study. Discussion These findings suggest that time to attrition is a useful metric for representing cognitive change, and reason for attrition and IIV are predictive of non-normative influences that may underlie instances of cognitive loss in older adults. PMID:26647008

Unsupervised quality estimation model for English to German translation and its application in extensive supervised evaluation.

PubMed

Han, Aaron L-F; Wong, Derek F; Chao, Lidia S; He, Liangye; Lu, Yi

2014-01-01

With the rapid development of machine translation (MT), the MT evaluation becomes very important to timely tell us whether the MT system makes any progress. The conventional MT evaluation methods tend to calculate the similarity between hypothesis translations offered by automatic translation systems and reference translations offered by professional translators. There are several weaknesses in existing evaluation metrics. Firstly, the designed incomprehensive factors result in language-bias problem, which means they perform well on some special language pairs but weak on other language pairs. Secondly, they tend to use no linguistic features or too many linguistic features, of which no usage of linguistic feature draws a lot of criticism from the linguists and too many linguistic features make the model weak in repeatability. Thirdly, the employed reference translations are very expensive and sometimes not available in the practice. In this paper, the authors propose an unsupervised MT evaluation metric using universal part-of-speech tagset without relying on reference translations. The authors also explore the performances of the designed metric on traditional supervised evaluation tasks. Both the supervised and unsupervised experiments show that the designed methods yield higher correlation scores with human judgments.

Sweet-spot training for early esophageal cancer detection

NASA Astrophysics Data System (ADS)

van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Over the past decade, the imaging tools for endoscopists have improved drastically. This has enabled physicians to visually inspect the intestinal tissue for early signs of malignant lesions. Besides this, recent studies show the feasibility of supportive image analysis for endoscopists, but the analysis problem is typically approached as a segmentation task where binary ground truth is employed. In this study, we show that the detection of early cancerous tissue in the gastrointestinal tract cannot be approached as a binary segmentation problem and it is crucial and clinically relevant to involve multiple experts for annotating early lesions. By employing the so-called sweet spot for training purposes as a metric, a much better detection performance can be achieved. Furthermore, a multi-expert-based ground truth, i.e. a golden standard, enables an improved validation of the resulting delineations. For this purpose, besides the sweet spot we also propose another novel metric, the Jaccard Golden Standard (JIGS) that can handle multiple ground-truth annotations. Our experiments involving these new metrics and based on the golden standard show that the performance of a detection algorithm of early neoplastic lesions in Barrett's esophagus can be increased significantly, demonstrating a 10 percent point increase in the resulting F1 detection score.

Cross-sectional evaluation of visuomotor tracking performance following subconcussive head impacts.

PubMed

Brokaw, E B; Fine, M S; Kindschi, K E; Santago Ii, A C; Lum, P S; Higgins, M

2018-01-01

Repeated mild traumatic brain injury (mTBI) has been associated with increased risk of degenerative neurological disorders. While the effects of mTBI and repeated injury are known, studies have only recently started examining repeated subconcussive impacts, impacts that do not result in a clinically diagnosed mTBI. In these studies, repeated subconcussive impacts have been connected to cognitive performance and brain imaging changes. Recent research suggests that performance on a visuomotor tracking (VMT) task may help improve the identification of mTBI. The goal of this study was to investigate if VMT performance is sensitive to the cumulative effect of repeated subconcussive head impacts in collegiate men's lacrosse players. A cross-sectional, prospective study was completed with eleven collegiate men's lacrosse players. Participants wore helmet-mounted sensors and completed VMT and reaction time assessments. The relationship between cumulative impact metrics and VMT metrics were investigated. In this study, VMT performance correlated with repeated subconcussive head impacts; individuals approached clinically diagnosed mTBI-like performance as the cumulative rotational velocity they experienced increased. This suggests that repeated subconcussive impacts can result in measurable impairments and indicates that visuomotor tracking performance may be a useful tool for monitoring the effects of repeated subconcussive impacts.

PDS: A Performance Database Server

DOE PAGES

Berry, Michael W.; Dongarra, Jack J.; Larose, Brian H.; ...

1994-01-01

The process of gathering, archiving, and distributing computer benchmark data is a cumbersome task usually performed by computer users and vendors with little coordination. Most important, there is no publicly available central depository of performance data for all ranges of machines from personal computers to supercomputers. We present an Internet-accessible performance database server (PDS) that can be used to extract current benchmark data and literature. As an extension to the X-Windows-based user interface (Xnetlib) to the Netlib archival system, PDS provides an on-line catalog of public domain computer benchmarks such as the LINPACK benchmark, Perfect benchmarks, and the NAS parallelmore » benchmarks. PDS does not reformat or present the benchmark data in any way that conflicts with the original methodology of any particular benchmark; it is thereby devoid of any subjective interpretations of machine performance. We believe that all branches (research laboratories, academia, and industry) of the general computing community can use this facility to archive performance metrics and make them readily available to the public. PDS can provide a more manageable approach to the development and support of a large dynamic database of published performance metrics.« less

Two forms of touch perception in the human brain.

PubMed

Spitoni, Grazia Fernanda; Galati, Gaspare; Antonucci, Gabriella; Haggard, Patrick; Pizzamiglio, Luigi

2010-12-01

We compared the judgment of distance between two simultaneous tactile stimuli applied to different body parts, with judgment of intensity of skin contact of the very same stimulation. Results on normal subjects showed that both tasks bilaterally activate parietal and frontal areas. However, the evaluation of distances on the body surface selectively activated the angular gyrus and the temporo-parieto-occipital junction in the right hemisphere. The different involvement of the brain areas in the two tactile tasks is interpreted as the need for using a Mental Body Representation (MBR) in the distance task, while the judgment of the intensity of skin deflection can be performed without the mediation of the MBR. The present study suggests that the cognitive processes underlying the two tasks are supported by partially different brain networks. In particular, our results show that metric spatial evaluation is lateralized to the right hemisphere.

An Overview and Empirical Comparison of Distance Metric Learning Methods.

PubMed

Moutafis, Panagiotis; Leng, Mengjun; Kakadiaris, Ioannis A

2016-02-16

In this paper, we first offer an overview of advances in the field of distance metric learning. Then, we empirically compare selected methods using a common experimental protocol. The number of distance metric learning algorithms proposed keeps growing due to their effectiveness and wide application. However, existing surveys are either outdated or they focus only on a few methods. As a result, there is an increasing need to summarize the obtained knowledge in a concise, yet informative manner. Moreover, existing surveys do not conduct comprehensive experimental comparisons. On the other hand, individual distance metric learning papers compare the performance of the proposed approach with only a few related methods and under different settings. This highlights the need for an experimental evaluation using a common and challenging protocol. To this end, we conduct face verification experiments, as this task poses significant challenges due to varying conditions during data acquisition. In addition, face verification is a natural application for distance metric learning because the encountered challenge is to define a distance function that: 1) accurately expresses the notion of similarity for verification; 2) is robust to noisy data; 3) generalizes well to unseen subjects; and 4) scales well with the dimensionality and number of training samples. In particular, we utilize well-tested features to assess the performance of selected methods following the experimental protocol of the state-of-the-art database labeled faces in the wild. A summary of the results is presented along with a discussion of the insights obtained and lessons learned by employing the corresponding algorithms.

Quantitative assessment based on kinematic measures of functional impairments during upper extremity movements: A review.

PubMed

de los Reyes-Guzmán, Ana; Dimbwadyo-Terrer, Iris; Trincado-Alonso, Fernando; Monasterio-Huelin, Félix; Torricelli, Diego; Gil-Agudo, Angel

2014-08-01

Quantitative measures of human movement quality are important for discriminating healthy and pathological conditions and for expressing the outcomes and clinically important changes in subjects' functional state. However the most frequently used instruments for the upper extremity functional assessment are clinical scales, that previously have been standardized and validated, but have a high subjective component depending on the observer who scores the test. But they are not enough to assess motor strategies used during movements, and their use in combination with other more objective measures is necessary. The objective of the present review is to provide an overview on objective metrics found in literature with the aim of quantifying the upper extremity performance during functional tasks, regardless of the equipment or system used for registering kinematic data. A search in Medline, Google Scholar and IEEE Xplore databases was performed following a combination of a series of keywords. The full scientific papers that fulfilled the inclusion criteria were included in the review. A set of kinematic metrics was found in literature in relation to joint displacements, analysis of hand trajectories and velocity profiles. These metrics were classified into different categories according to the movement characteristic that was being measured. These kinematic metrics provide the starting point for a proposed objective metrics for the functional assessment of the upper extremity in people with movement disorders as a consequence of neurological injuries. Potential areas of future and further research are presented in the Discussion section. Copyright © 2014 Elsevier Ltd. All rights reserved.

An investigation of automatic exposure control calibration for chest imaging with a computed radiography system.

PubMed

Moore, C S; Wood, T J; Avery, G; Balcam, S; Needler, L; Beavis, A W; Saunderson, J R

2014-05-07

The purpose of this study was to examine the use of three physical image quality metrics in the calibration of an automatic exposure control (AEC) device for chest radiography with a computed radiography (CR) imaging system. The metrics assessed were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQm), all measured using a uniform chest phantom. Subsequent calibration curves were derived to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated chest images with correct detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated chest images contained clinically realistic projected anatomy and anatomical noise and were scored by experienced image evaluators. Constant DDI and CNR curves do not appear to provide optimized performance across the diagnostic energy range. Conversely, constant eNEQm and SNR do appear to provide optimized performance, with the latter being the preferred calibration metric given as it is easier to measure in practice. Medical physicists may use the SNR image quality metric described here when setting up and optimizing AEC devices for chest radiography CR systems with a degree of confidence that resulting clinical image quality will be adequate for the required clinical task. However, this must be done with close cooperation of expert image evaluators, to ensure appropriate levels of detector air kerma.

An investigation of automatic exposure control calibration for chest imaging with a computed radiography system

NASA Astrophysics Data System (ADS)

Moore, C. S.; Wood, T. J.; Avery, G.; Balcam, S.; Needler, L.; Beavis, A. W.; Saunderson, J. R.

2014-05-01

The purpose of this study was to examine the use of three physical image quality metrics in the calibration of an automatic exposure control (AEC) device for chest radiography with a computed radiography (CR) imaging system. The metrics assessed were signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and mean effective noise equivalent quanta (eNEQm), all measured using a uniform chest phantom. Subsequent calibration curves were derived to ensure each metric was held constant across the tube voltage range. Each curve was assessed for its clinical appropriateness by generating computer simulated chest images with correct detector air kermas for each tube voltage, and grading these against reference images which were reconstructed at detector air kermas correct for the constant detector dose indicator (DDI) curve currently programmed into the AEC device. All simulated chest images contained clinically realistic projected anatomy and anatomical noise and were scored by experienced image evaluators. Constant DDI and CNR curves do not appear to provide optimized performance across the diagnostic energy range. Conversely, constant eNEQm and SNR do appear to provide optimized performance, with the latter being the preferred calibration metric given as it is easier to measure in practice. Medical physicists may use the SNR image quality metric described here when setting up and optimizing AEC devices for chest radiography CR systems with a degree of confidence that resulting clinical image quality will be adequate for the required clinical task. However, this must be done with close cooperation of expert image evaluators, to ensure appropriate levels of detector air kerma.

Quantification and visualization of coordination during non-cyclic upper extremity motion.

PubMed

Fineman, Richard A; Stirling, Leia A

2017-10-03

There are many design challenges in creating at-home tele-monitoring systems that enable quantification and visualization of complex biomechanical behavior. One such challenge is robustly quantifying joint coordination in a way that is intuitive and supports clinical decision-making. This work defines a new measure of coordination called the relative coordination metric (RCM) and its accompanying normalization schemes. RCM enables quantification of coordination during non-constrained discrete motions. Here RCM is applied to a grasping task. Fifteen healthy participants performed a reach, grasp, transport, and release task with a cup and a pen. The measured joint angles were then time-normalized and the RCM time-series were calculated between the shoulder-elbow, shoulder-wrist, and elbow-wrist. RCM was normalized using four differing criteria: the selected joint degree of freedom, angular velocity, angular magnitude, and range of motion. Percent time spent in specified RCM ranges was used asa composite metric and was evaluated for each trial. RCM was found to vary based on: (1) chosen normalization scheme, (2) the stage within the task, (3) the object grasped, and (4) the trajectory of the motion. The RCM addresses some of the limitations of current measures of coordination because it is applicable to discrete motions, does not rely on cyclic repetition, and uses velocity-based measures. Future work will explore clinically relevant differences in the RCM as it is expanded to evaluate different tasks and patient populations. Copyright © 2017. Published by Elsevier Ltd.

Correlated individual differences suggest a common mechanism underlying metacognition in visual perception and visual short-term memory.

PubMed

Samaha, Jason; Postle, Bradley R

2017-11-29

Adaptive behaviour depends on the ability to introspect accurately about one's own performance. Whether this metacognitive ability is supported by the same mechanisms across different tasks is unclear. We investigated the relationship between metacognition of visual perception and metacognition of visual short-term memory (VSTM). Experiments 1 and 2 required subjects to estimate the perceived or remembered orientation of a grating stimulus and rate their confidence. We observed strong positive correlations between individual differences in metacognitive accuracy between the two tasks. This relationship was not accounted for by individual differences in task performance or average confidence, and was present across two different metrics of metacognition and in both experiments. A model-based analysis of data from a third experiment showed that a cross-domain correlation only emerged when both tasks shared the same task-relevant stimulus feature. That is, metacognition for perception and VSTM were correlated when both tasks required orientation judgements, but not when the perceptual task was switched to require contrast judgements. In contrast with previous results comparing perception and long-term memory, which have largely provided evidence for domain-specific metacognitive processes, the current findings suggest that metacognition of visual perception and VSTM is supported by a domain-general metacognitive architecture, but only when both domains share the same task-relevant stimulus feature. © 2017 The Author(s).

Evaluating motion processing algorithms for use with functional near-infrared spectroscopy data from young children.

PubMed

Delgado Reyes, Lourdes M; Bohache, Kevin; Wijeakumar, Sobanawartiny; Spencer, John P

2018-04-01

Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal components analysis (PCA), correlation-based signal improvement (CBSI), wavelet filtering, and spline interpolation. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Brigadoi et al. compared motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Given that fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. This study addresses that problem by evaluating motion correction algorithms implemented in HomER2. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response. Results showed that targeted PCA (tPCA), spline, and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using quantitative metrics. The CBSI method corrected many of the artifacts present in our data; however, this approach produced sometimes unstable HRFs. The targeted PCA and spline methods proved to be the most robust, performing well across all comparison metrics. When compared head to head, tPCA consistently outperformed spline. We conclude, therefore, that tPCA is an effective technique for correcting motion artifacts in fNIRS data from young children.

Multilevel image recognition using discriminative patches and kernel covariance descriptor

NASA Astrophysics Data System (ADS)

Lu, Le; Yao, Jianhua; Turkbey, Evrim; Summers, Ronald M.

2014-03-01

Computer-aided diagnosis of medical images has emerged as an important tool to objectively improve the performance, accuracy and consistency for clinical workflow. To computerize the medical image diagnostic recognition problem, there are three fundamental problems: where to look (i.e., where is the region of interest from the whole image/volume), image feature description/encoding, and similarity metrics for classification or matching. In this paper, we exploit the motivation, implementation and performance evaluation of task-driven iterative, discriminative image patch mining; covariance matrix based descriptor via intensity, gradient and spatial layout; and log-Euclidean distance kernel for support vector machine, to address these three aspects respectively. To cope with often visually ambiguous image patterns for the region of interest in medical diagnosis, discovery of multilabel selective discriminative patches is desired. Covariance of several image statistics summarizes their second order interactions within an image patch and is proved as an effective image descriptor, with low dimensionality compared with joint statistics and fast computation regardless of the patch size. We extensively evaluate two extended Gaussian kernels using affine-invariant Riemannian metric or log-Euclidean metric with support vector machines (SVM), on two medical image classification problems of degenerative disc disease (DDD) detection on cortical shell unwrapped CT maps and colitis detection on CT key images. The proposed approach is validated with promising quantitative results on these challenging tasks. Our experimental findings and discussion also unveil some interesting insights on the covariance feature composition with or without spatial layout for classification and retrieval, and different kernel constructions for SVM. This will also shed some light on future work using covariance feature and kernel classification for medical image analysis.

fMRI characterisation of widespread brain networks relevant for behavioural variability in fine hand motor control with and without visual feedback.

PubMed

Mayhew, Stephen D; Porcaro, Camillo; Tecchio, Franca; Bagshaw, Andrew P

2017-03-01

A bilateral visuo-parietal-motor network is responsible for fine control of hand movements. However, the sub-regions which are devoted to maintenance of contraction stability and how these processes fluctuate with trial-quality of task execution and in the presence/absence of visual feedback remains unclear. We addressed this by integrating behavioural and fMRI measurements during right-hand isometric compression of a compliant rubber bulb, at 10% and 30% of maximum voluntary contraction, both with and without visual feedback of the applied force. We quantified single-trial behavioural performance during 1) the whole task period and 2) stable contraction maintenance, and regressed these metrics against the fMRI data to identify the brain activity most relevant to trial-by-trial fluctuations in performance during specific task phases. fMRI-behaviour correlations in a bilateral network of visual, premotor, primary motor, parietal and inferior frontal cortical regions emerged during performance of the entire feedback task, but only in premotor, parietal cortex and thalamus during the stable contraction period. The trials with the best task performance showed increased bilaterality and amplitude of fMRI responses. With feedback, stronger BOLD-behaviour coupling was found during 10% compared to 30% contractions. Only a small subset of regions in this network were weakly correlated with behaviour without feedback, despite wider network activated during this task than in the presence of feedback. These findings reflect a more focused network strongly coupled to behavioural fluctuations when providing visual feedback, whereas without it the task recruited widespread brain activity almost uncoupled from behavioural performance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluation techniques and metrics for assessment of pan+MSI fusion (pansharpening)

NASA Astrophysics Data System (ADS)

Mercovich, Ryan A.

2015-05-01

Fusion of broadband panchromatic data with narrow band multispectral data - pansharpening - is a common and often studied problem in remote sensing. Many methods exist to produce data fusion results with the best possible spatial and spectral characteristics, and a number have been commercially implemented. This study examines the output products of 4 commercial implementations with regard to their relative strengths and weaknesses for a set of defined image characteristics and analyst use-cases. Image characteristics used are spatial detail, spatial quality, spectral integrity, and composite color quality (hue and saturation), and analyst use-cases included a variety of object detection and identification tasks. The imagery comes courtesy of the RIT SHARE 2012 collect. Two approaches are used to evaluate the pansharpening methods, analyst evaluation or qualitative measure and image quality metrics or quantitative measures. Visual analyst evaluation results are compared with metric results to determine which metrics best measure the defined image characteristics and product use-cases and to support future rigorous characterization the metrics' correlation with the analyst results. Because pansharpening represents a trade between adding spatial information from the panchromatic image, and retaining spectral information from the MSI channels, the metrics examined are grouped into spatial improvement metrics and spectral preservation metrics. A single metric to quantify the quality of a pansharpening method would necessarily be a combination of weighted spatial and spectral metrics based on the importance of various spatial and spectral characteristics for the primary task of interest. Appropriate metrics and weights for such a combined metric are proposed here, based on the conducted analyst evaluation. Additionally, during this work, a metric was developed specifically focused on assessment of spatial structure improvement relative to a reference image and independent of scene content. Using analysis of Fourier transform images, a measure of high-frequency content is computed in small sub-segments of the image. The average increase in high-frequency content across the image is used as the metric, where averaging across sub-segments combats the scene dependent nature of typical image sharpness techniques. This metric had an improved range of scores, better representing difference in the test set than other common spatial structure metrics.

Effects of metric change on safety in the workplace for selected occupations

NASA Astrophysics Data System (ADS)

Lefande, J. M.; Pokorney, J. L.

1982-04-01

The study assesses the potential safety issues of metric conversion in the workplace. A purposive sample of 35 occupations based on injury and illnesses indexes were assessed. After an analysis of workforce population, hazard analysis and measurement sensitivity of the occupations, jobs were analyzed to identify potential safety hazards by industrial hygienists, safety engineers and academia. The study's major findings were as follows: No metric hazard experience was identified. An increased exposure might occur when particular jobs and their job tasks are going the transition from customary measurement to metric measurement. Well planned metric change programs reduce hazard potential. Metric safety issues are unresolved in the aviation industry.

Individual differences in multitasking ability and adaptability.

PubMed

Morgan, Brent; D'Mello, Sidney; Abbott, Robert; Radvansky, Gabriel; Haass, Michael; Tamplin, Andrea

2013-08-01

The aim of this study was to identify the cognitive factors that predictability and adaptability during multitasking with a flight simulator. Multitasking has become increasingly prevalent as most professions require individuals to perform multiple tasks simultaneously. Considerable research has been undertaken to identify the characteristics of people (i.e., individual differences) that predict multitasking ability. Although working memory is a reliable predictor of general multitasking ability (i.e., performance in normal conditions), there is the question of whether different cognitive faculties are needed to rapidly respond to changing task demands (adaptability). Participants first completed a battery of cognitive individual differences tests followed by multitasking sessions with a flight simulator. After a baseline condition, difficulty of the flight simulator was incrementally increased via four experimental manipulations, and performance metrics were collected to assess multitasking ability and adaptability. Scholastic aptitude and working memory predicted general multitasking ability (i.e., performance at baseline difficulty), but spatial manipulation (in conjunction with working memory) was a major predictor of adaptability (performance in difficult conditions after accounting for baseline performance). Multitasking ability and adaptability may be overlapping but separate constructs that draw on overlapping (but not identical) sets of cognitive abilities. The results of this study are applicable to practitioners and researchers in human factors to assess multitasking performance in real-world contexts and with realistic task constraints. We also present a framework for conceptualizing multitasking adaptability on the basis of five adaptability profiles derived from performance on tasks with consistent versus increased difficulty.

Cues to viewing distance for stereoscopic depth constancy.

PubMed

Glennerster, A; Rogers, B J; Bradshaw, M F

1998-01-01

A veridical estimate of viewing distance is required in order to determine the metric structure of objects from binocular stereopsis. One example of a judgment of metric structure, which we used in our experiment, is the apparently circular cylinder task (E B Johnston, 1991 Vision Research 31 1351-1360). Most studies report underconstancy in this task when the stimulus is defined purely by binocular disparities. We examined the effect of two factors on performance: (i) the richness of the cues to viewing distance (using either a naturalistic setting with many cues to viewing distance or a condition in which the room and the monitors were obscured from view), and (ii) the range of stimulus disparities (cylinder depths) presented during an experimental run. We tested both experienced subjects (who had performed the task many times before under full-cue conditions) and naïve subjects. Depth constancy was reduced for the naïve subjects (from 62% to 46%) when the position of the monitors was obscured. Under similar conditions, the experienced subjects showed no reduction in constancy. In a second experiment, using a forced-choice method of constant stimuli, we found that depth constancy was reduced from 64% to 23% in naïve subjects and from 77% to 55% in experienced subjects when the same set of images was presented at all viewing distances rather than using a set of stimulus disparities proportional to the correct setting. One possible explanation of these results is that, under reduced-cue conditions, the range of disparities presented is used by the visual system as a cue to viewing distance.

The data quality analyzer: A quality control program for seismic data

NASA Astrophysics Data System (ADS)

Ringler, A. T.; Hagerty, M. T.; Holland, J.; Gonzales, A.; Gee, L. S.; Edwards, J. D.; Wilson, D.; Baker, A. M.

2015-03-01

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner. The DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station. The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a "grade" for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.

A Low-Cost, Passive Navigation Training System for Image-Guided Spinal Intervention.

PubMed

Lorias-Espinoza, Daniel; Carranza, Vicente González; de León, Fernando Chico-Ponce; Escamirosa, Fernando Pérez; Martinez, Arturo Minor

2016-11-01

Navigation technology is used for training in various medical specialties, not least image-guided spinal interventions. Navigation practice is an important educational component that allows residents to understand how surgical instruments interact with complex anatomy and to learn basic surgical skills such as the tridimensional mental interpretation of bidimensional data. Inexpensive surgical simulators for spinal surgery, however, are lacking. We therefore designed a low-cost spinal surgery simulator (Spine MovDigSys 01) to allow 3-dimensional navigation via 2-dimensional images without altering or limiting the surgeon's natural movement. A training system was developed with an anatomical lumbar model and 2 webcams to passively digitize surgical instruments under MATLAB software control. A proof-of-concept recognition task (vertebral body cannulation) and a pilot test of the system with 12 neuro- and orthopedic surgeons were performed to obtain feedback on the system. Position, orientation, and kinematic variables were determined and the lateral, posteroanterior, and anteroposterior views obtained. The system was tested with a proof-of-concept experimental task. Operator metrics including time of execution (t), intracorporeal length (d), insertion angle (α), average speed (v¯), and acceleration (a) were obtained accurately. These metrics were converted into assessment metrics such as smoothness of operation and linearity of insertion. Results from initial testing are shown and the system advantages and disadvantages described. This low-cost spinal surgery training system digitized the position and orientation of the instruments and allowed image-guided navigation, the generation of metrics, and graphic recording of the instrumental route. Spine MovDigSys 01 is useful for development of basic, noninnate skills and allows the novice apprentice to quickly and economically move beyond the basics. Copyright © 2016 Elsevier Inc. All rights reserved.

Characterization of medical students recall of factual knowledge using learning objects and repeated testing in a novel e-learning system.

PubMed

Taveira-Gomes, Tiago; Prado-Costa, Rui; Severo, Milton; Ferreira, Maria Amélia

2015-01-24

Spaced-repetition and test-enhanced learning are two methodologies that boost knowledge retention. ALERT STUDENT is a platform that allows creation and distribution of Learning Objects named flashcards, and provides insight into student judgments-of-learning through a metric called 'recall accuracy'. This study aims to understand how the spaced-repetition and test-enhanced learning features provided by the platform affect recall accuracy, and to characterize the effect that students, flashcards and repetitions exert on this measurement. Three spaced laboratory sessions (s0, s1 and s2), were conducted with n=96 medical students. The intervention employed a study task, and a quiz task that consisted in mentally answering open-ended questions about each flashcard and grading recall accuracy. Students were randomized into study-quiz and quiz groups. On s0 both groups performed the quiz task. On s1 and s2, the study-quiz group performed the study task followed by the quiz task, whereas the quiz group only performed the quiz task. We measured differences in recall accuracy between groups/sessions, its variance components, and the G-coefficients for the flashcard component. At s0 there were no differences in recall accuracy between groups. The experiment group achieved a significant increase in recall accuracy that was superior to the quiz group in s1 and s2. In the study-quiz group, increases in recall accuracy were mainly due to the session, followed by flashcard factors and student factors. In the quiz group, increases in recall accuracy were mainly accounted by flashcard factors, followed by student and session factors. The flashcard G-coefficient indicated an agreement on recall accuracy of 91% in the quiz group, and of 47% in the study-quiz group. Recall accuracy is an easily collectible measurement that increases the educational value of Learning Objects and open-ended questions. This metric seems to vary in a way consistent with knowledge retention, but further investigation is necessary to ascertain the nature of such relationship. Recall accuracy has educational implications to students and educators, and may contribute to deliver tailored learning experiences, assess the effectiveness of instruction, and facilitate research comparing blended-learning interventions.

Orion Flight Performance Design Trades

NASA Technical Reports Server (NTRS)

Jackson, Mark C.; Straube, Timothy

2010-01-01

A significant portion of the Orion pre-PDR design effort has focused on balancing mass with performance. High level performance metrics include abort success rates, lunar surface coverage, landing accuracy and touchdown loads. These metrics may be converted to parameters that affect mass, such as ballast for stabilizing the abort vehicle, propellant to achieve increased lunar coverage or extended missions, or ballast to increase the lift-to-drag ratio to improve entry and landing performance. The Orion Flight Dynamics team was tasked to perform analyses to evaluate many of these trades. These analyses not only provide insight into the physics of each particular trade but, in aggregate, they illustrate the processes used by Orion to balance performance and mass margins, and thereby make design decisions. Lessons learned can be gleaned from a review of these studies which will be useful to other spacecraft system designers. These lessons fall into several categories, including: appropriate application of Monte Carlo analysis in design trades, managing margin in a highly mass-constrained environment, and the use of requirements to balance margin between subsystems and components. This paper provides a review of some of the trades and analyses conducted by the Flight Dynamics team, as well as systems engineering lessons learned.

The fractured landscape of RNA-seq alignment: the default in our STARs.

PubMed

Ballouz, Sara; Dobin, Alexander; Gingeras, Thomas R; Gillis, Jesse

2018-06-01

Many tools are available for RNA-seq alignment and expression quantification, with comparative value being hard to establish. Benchmarking assessments often highlight methods' good performance, but are focused on either model data or fail to explain variation in performance. This leaves us to ask, what is the most meaningful way to assess different alignment choices? And importantly, where is there room for progress? In this work, we explore the answers to these two questions by performing an exhaustive assessment of the STAR aligner. We assess STAR's performance across a range of alignment parameters using common metrics, and then on biologically focused tasks. We find technical metrics such as fraction mapping or expression profile correlation to be uninformative, capturing properties unlikely to have any role in biological discovery. Surprisingly, we find that changes in alignment parameters within a wide range have little impact on both technical and biological performance. Yet, when performance finally does break, it happens in difficult regions, such as X-Y paralogs and MHC genes. We believe improved reporting by developers will help establish where results are likely to be robust or fragile, providing a better baseline to establish where methodological progress can still occur.

Coalition Formation under Uncertainty

DTIC Science & Technology

2010-03-01

world robotics and demonstrate the algorithm’s scalability. This provides a framework well suited to decentralized task allocation in general collectives...impatience and acquiescence to define a robot allocation to a task in a decentralized manner. The tasks are assigned to the entire collective, and one...20] allocates tasks to robots with a first-price auction method [31]. It announces a task with defined metrics, then the robots issue bids. The task

WISE: Automated support for software project management and measurement. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ramakrishnan, Sudhakar

1995-01-01

One important aspect of software development and IV&V is measurement. Unless a software development effort is measured in some way, it is difficult to judge the effectiveness of current efforts and predict future performances. Collection of metrics and adherence to a process are difficult tasks in a software project. Change activity is a powerful indicator of project status. Automated systems that can handle change requests, issues, and other process documents provide an excellent platform for tracking the status of the project. A World Wide Web based architecture is developed for (a) making metrics collection an implicit part of the software process, (b) providing metric analysis dynamically, (c) supporting automated tools that can complement current practices of in-process improvement, and (d) overcoming geographical barrier. An operational system (WISE) instantiates this architecture allowing for the improvement of software process in a realistic environment. The tool tracks issues in software development process, provides informal communication between the users with different roles, supports to-do lists (TDL), and helps in software process improvement. WISE minimizes the time devoted to metrics collection, analysis, and captures software change data. Automated tools like WISE focus on understanding and managing the software process. The goal is improvement through measurement.

Task-based exposure assessment of nanoparticles in the workplace

NASA Astrophysics Data System (ADS)

Ham, Seunghon; Yoon, Chungsik; Lee, Euiseung; Lee, Kiyoung; Park, Donguk; Chung, Eunkyo; Kim, Pilje; Lee, Byoungcheun

2012-09-01

Although task-based sampling is, theoretically, a plausible approach to the assessment of nanoparticle exposure, few studies using this type of sampling have been published. This study characterized and compared task-based nanoparticle exposure profiles for engineered nanoparticle manufacturing workplaces (ENMW) and workplaces that generated welding fumes containing incidental nanoparticles. Two ENMW and two welding workplaces were selected for exposure assessments. Real-time devices were utilized to characterize the concentration profiles and size distributions of airborne nanoparticles. Filter-based sampling was performed to measure time-weighted average (TWA) concentrations, and off-line analysis was performed using an electron microscope. Workplace tasks were recorded by researchers to determine the concentration profiles associated with particular tasks/events. This study demonstrated that exposure profiles differ greatly in terms of concentrations and size distributions according to the task performed. The size distributions recorded during tasks were different from both those recorded during periods with no activity and from the background. The airborne concentration profiles of the nanoparticles varied according to not only the type of workplace but also the concentration metrics. The concentrations measured by surface area and the number concentrations measured by condensation particle counter, particulate matter 1.0, and TWA mass concentrations all showed a similar pattern, whereas the number concentrations measured by scanning mobility particle sizer indicated that the welding fume concentrations at one of the welding workplaces were unexpectedly higher than were those at workplaces that were engineering nanoparticles. This study suggests that a task-based exposure assessment can provide useful information regarding the exposure profiles of nanoparticles and can therefore be used as an exposure assessment tool.

Distance Metric Learning Using Privileged Information for Face Verification and Person Re-Identification.

PubMed

Xu, Xinxing; Li, Wen; Xu, Dong

2015-12-01

In this paper, we propose a new approach to improve face verification and person re-identification in the RGB images by leveraging a set of RGB-D data, in which we have additional depth images in the training data captured using depth cameras such as Kinect. In particular, we extract visual features and depth features from the RGB images and depth images, respectively. As the depth features are available only in the training data, we treat the depth features as privileged information, and we formulate this task as a distance metric learning with privileged information problem. Unlike the traditional face verification and person re-identification tasks that only use visual features, we further employ the extra depth features in the training data to improve the learning of distance metric in the training process. Based on the information-theoretic metric learning (ITML) method, we propose a new formulation called ITML with privileged information (ITML+) for this task. We also present an efficient algorithm based on the cyclic projection method for solving the proposed ITML+ formulation. Extensive experiments on the challenging faces data sets EUROCOM and CurtinFaces for face verification as well as the BIWI RGBD-ID data set for person re-identification demonstrate the effectiveness of our proposed approach.

Impact of communicative head movements on the quality of functional near-infrared spectroscopy signals: negligible effects for affirmative and negative gestures and consistent artifacts related to raising eyebrows

NASA Astrophysics Data System (ADS)

Balardin, Joana Bisol; Morais, Guilherme Augusto Zimeo; Furucho, Rogério Akira; Trambaiolli, Lucas Romualdo; Sato, João Ricardo

2017-04-01

Functional near-infrared spectroscopy (fNIRS) is currently one of the most promising tools in the neuroscientific research to study brain hemodynamics during naturalistic social communication. The application of fNIRS by studies in this field of knowledge has been widely justified by its strong resilience to motion artifacts, including those that might be generated by communicative head and facial movements. Previous studies have focused on the identification and correction of these artifacts, but a quantification of the differential contribution of common communicative movements on the quality of fNIRS signals is still missing. We assessed the impact of four movements (nodding head up and down, reading aloud, nodding head sideways, and raising eyebrows) performed during rest and task conditions on two metrics of signal quality control: an estimative of signal-to-noise performance and the negative correlation between oxygenated and deoxygenated hemoglobin (oxy-Hb and deoxy-Hb). Channel-wise group analysis confirmed the robustness of the fNIRS technique to head nodding movements but showed a large effect of raising eyebrows in both signal quality control metrics, both during task and rest conditions. Reading aloud did not disrupt the expected anticorrelation between oxy-Hb and deoxy-Hb but had a relatively large effect on signal-to-noise performance. These findings may have implications to the interpretation of fNIRS studies examining communicative processes.

A sensitive period for musical training: contributions of age of onset and cognitive abilities.

PubMed

Bailey, Jennifer; Penhune, Virginia B

2012-04-01

The experiences we engage in during childhood can stay with us well into our adult years. The idea of a sensitive period--a window during maturation when our brains are most influenced by behavior--has been proposed. Work from our laboratory has shown that early-trained musicians (ET) performed better on visual-motor and auditory-motor synchronization tasks than late-trained musicians (LT), even when matched for total musical experience. Although the groups of musicians showed no cognitive differences, working memory scores correlated with task performance. In this study, we have replicated these findings in a larger sample of musicians and included a group of highly educated nonmusicians (NM). Participants performed six woodblock rhythms of varying levels of metrical complexity and completed cognitive subtests measuring verbal abilities, working memory, and pattern recognition. Working memory scores correlated with task performance across all three groups. Interestingly, verbal abilities were stronger among the NM, while nonverbal abilities were stronger among musicians. These findings are discussed in context of the sensitive period hypothesis as well as the debate surrounding cognitive differences between musicians and NM. © 2012 New York Academy of Sciences.

Global Rating Scales and Motion Analysis Are Valid Proficiency Metrics in Virtual and Benchtop Knee Arthroscopy Simulators.

PubMed

Chang, Justues; Banaszek, Daniel C; Gambrel, Jason; Bardana, Davide

2016-04-01

Work-hour restrictions and fatigue management strategies in surgical training programs continue to evolve in an effort to improve the learning environment and promote safer patient care. In response, training programs must reevaluate how various teaching modalities such as simulation can augment the development of surgical competence in trainees. For surgical simulators to be most useful, it is important to determine whether surgical proficiency can be reliably differentiated using them. To our knowledge, performance on both virtual and benchtop arthroscopy simulators has not been concurrently assessed in the same subjects. (1) Do global rating scales and procedure time differentiate arthroscopic expertise in virtual and benchtop knee models? (2) Can commercially available built-in motion analysis metrics differentiate arthroscopic expertise? (3) How well are performance measures on virtual and benchtop simulators correlated? (4) Are these metrics sensitive enough to differentiate by year of training? A cross-sectional study of 19 subjects (four medical students, 12 residents, and three staff) were recruited and divided into 11 novice arthroscopists (student to Postgraduate Year [PGY] 3) and eight proficient arthroscopists (PGY 4 to staff) who completed a diagnostic arthroscopy and loose-body retrieval in both virtual and benchtop knee models. Global rating scales (GRS), procedure times, and motion analysis metrics were used to evaluate performance. The proficient group scored higher on virtual (14 ± 6 [95% confidence interval {CI}, 10-18] versus 36 ± 5 [95% CI, 32-40], p < 0.001) and benchtop (16 ± 8 [95% CI, 11-21] versus 36 ± 5 [95% CI, 31-40], p < 0.001) GRS scales. The proficient subjects completed nearly all tasks faster than novice subjects, including the virtual scope (579 ±169 [95% CI, 466-692] versus 358 ± 178 [95% CI, 210-507] seconds, p = 0.02) and benchtop knee scope + probe (480 ± 160 [95% CI, 373-588] versus 277 ± 64 [95% CI, 224-330] seconds, p = 0.002). The built-in motion analysis metrics also distinguished novices from proficient arthroscopists using the self-generated virtual loose body retrieval task scores (4 ± 1 [95% CI, 3-5] versus 6 ± 1 [95% CI, 5-7], p = 0.001). GRS scores between virtual and benchtop models were very strongly correlated (ρ = 0.93, p < 0.001). There was strong correlation between year of training and virtual GRS (ρ = 0.8, p < 0.001) and benchtop GRS (ρ = 0.87, p < 0.001) scores. To our knowledge, this is the first study to evaluate performance on both virtual and benchtop knee simulators. We have shown that subjective GRS scores and objective motion analysis metrics and procedure time are valid measures to distinguish arthroscopic skill on both virtual and benchtop modalities. Performance on both modalities is well correlated. We believe that training on artificial models allows acquisition of skills in a safe environment. Future work should compare different modalities in the efficiency of skill acquisition, retention, and transferability to the operating room.

Complexity Management Using Metrics for Trajectory Flexibility Preservation and Constraint Minimization

NASA Technical Reports Server (NTRS)

Idris, Husni; Shen, Ni; Wing, David J.

2011-01-01

The growing demand for air travel is increasing the need for mitigating air traffic congestion and complexity problems, which are already at high levels. At the same time new surveillance, navigation, and communication technologies are enabling major transformations in the air traffic management system, including net-based information sharing and collaboration, performance-based access to airspace resources, and trajectory-based rather than clearance-based operations. The new system will feature different schemes for allocating tasks and responsibilities between the ground and airborne agents and between the human and automation, with potential capacity and cost benefits. Therefore, complexity management requires new metrics and methods that can support these new schemes. This paper presents metrics and methods for preserving trajectory flexibility that have been proposed to support a trajectory-based approach for complexity management by airborne or ground-based systems. It presents extensions to these metrics as well as to the initial research conducted to investigate the hypothesis that using these metrics to guide user and service provider actions will naturally mitigate traffic complexity. The analysis showed promising results in that: (1) Trajectory flexibility preservation mitigated traffic complexity as indicated by inducing self-organization in the traffic patterns and lowering traffic complexity indicators such as dynamic density and traffic entropy. (2)Trajectory flexibility preservation reduced the potential for secondary conflicts in separation assurance. (3) Trajectory flexibility metrics showed potential application to support user and service provider negotiations for minimizing the constraints imposed on trajectories without jeopardizing their objectives.

Virtual reality as a metric for the assessment of laparoscopic psychomotor skills. Learning curves and reliability measures.

PubMed

Gallagher, A G; Satava, R M

2002-12-01

The objective assessment of the psychomotor skills of surgeons is now a priority; however, this is a difficult task because of measurement difficulties associated with the assessment of surgery in vivo. In this study, virtual reality (VR) was used to overcome these problems. Twelve experienced (>50 minimal-access procedures), 12 inexperienced laparoscopic surgeons (<10 minimal-access procedures), and 12 laparoscopic novices participated in the study. Each subject completed 10 trials on the Minimally Invasive Surgical Trainer; Virtual Reality (MIST VR). Experienced laparoscopic surgeons performed the tasks significantly (p < 0.01) faster, with less error, more economy in the movement of instruments and the use of diathermy, and with greater consistency in performance. The standardized coefficient alpha for performance measures ranged from a = 0.89 to 0.98, showing high internal measurement consistency. Test-retest reliability ranged from r = 0.96 to r = 0.5. VR is a useful tool for evaluating the psychomotor skills needed to perform laparoscopic surgery.

The Albuquerque Seismological Laboratory Data Quality Analyzer

NASA Astrophysics Data System (ADS)

Ringler, A. T.; Hagerty, M.; Holland, J.; Gee, L. S.; Wilson, D.

2013-12-01

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several efforts underway to improve data quality at its stations. The Data Quality Analyzer (DQA) is one such development. The DQA is designed to characterize station data quality in a quantitative and automated manner. Station quality is based on the evaluation of various metrics, such as timing quality, noise levels, sensor coherence, and so on. These metrics are aggregated into a measurable grade for each station. The DQA consists of a website, a metric calculator (Seedscan), and a PostgreSQL database. The website allows the user to make requests for various time periods, review specific networks and stations, adjust weighting of the station's grade, and plot metrics as a function of time. The website dynamically loads all station data from a PostgreSQL database. The database is central to the application; it acts as a hub where metric values and limited station descriptions are stored. Data is stored at the level of one sensor's channel per day. The database is populated by Seedscan. Seedscan reads and processes miniSEED data, to generate metric values. Seedscan, written in Java, compares hashes of metadata and data to detect changes and perform subsequent recalculations. This ensures that the metric values are up to date and accurate. Seedscan can be run in a scheduled task or on demand by way of a config file. It will compute metrics specified in its configuration file. While many metrics are currently in development, some are completed and being actively used. These include: availability, timing quality, gap count, deviation from the New Low Noise Model, deviation from a station's noise baseline, inter-sensor coherence, and data-synthetic fits. In all, 20 metrics are planned, but any number could be added. ASL is actively using the DQA on a daily basis for station diagnostics and evaluation. As Seedscan is scheduled to run every night, data quality analysts are able to then use the website to diagnose changes in noise levels or other anomalous data. This allows for errors to be corrected quickly and efficiently. The code is designed to be flexible for adding metrics and portable for use in other networks. We anticipate further development of the DQA by improving the existing web-interface, adding more metrics, adding an interface to facilitate the verification of historic station metadata and performance, and an interface to allow better monitoring of data quality goals.

Predictive value of background experiences and visual spatial ability testing on laparoscopic baseline performance among residents entering postgraduate surgical training.

PubMed

Louridas, Marisa; Quinn, Lauren E; Grantcharov, Teodor P

2016-03-01

Emerging evidence suggests that despite dedicated practice, not all surgical trainees have the ability to reach technical competency in minimally invasive techniques. While selecting residents that have the ability to reach technical competence is important, evidence to guide the incorporation of technical ability into selection processes is limited. Therefore, the purpose of the present study was to evaluate whether background experiences and 2D-3D visual spatial test results are predictive of baseline laparoscopic skill for the novice surgical trainee. First-year residents were studied. Demographic data and background surgical and non-surgical experiences were obtained using a questionnaire. Visual spatial ability was evaluated using the PicSOr, cube comparison (CC) and card rotation (CR) tests. Technical skill was assessed using the camera navigation (LCN) task and laparoscopic circle cut (LCC) task. Resident performance on these technical tasks was compared and correlated with the questionnaire and visual spatial findings. Previous experience in observing laparoscopic procedures was associated with significantly better LCN performance, and experience in navigating the laparoscopic camera was associated with significantly better LCC task results. Residents who scored higher on the CC test demonstrated a more accurate LCN path length score (r s(PL) = -0.36, p = 0.03) and angle path (r s(AP) = -0.426, p = 0.01) score when completing the LCN task. No other significant correlations were found between the visual spatial tests (PicSOr, CC or CR) and LCC performance. While identifying selection tests for incoming surgical trainees that predict technical skill performance is appealing, the surrogate markers evaluated correlate with specific metrics of surgical performance related to a single task but do not appear to reliably predict technical performance of different laparoscopic tasks. Predicting the acquisition of technical skills will require the development of a series of evidence-based tests that measure a number of innate abilities as well as their inherent interactions.

Evaluation of cortical plasticity in children with cerebral palsy undergoing constraint-induced movement therapy based on functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Cao, Jianwei; Khan, Bilal; Hervey, Nathan; Tian, Fenghua; Delgado, Mauricio R.; Clegg, Nancy J.; Smith, Linsley; Roberts, Heather; Tulchin-Francis, Kirsten; Shierk, Angela; Shagman, Laura; MacFarlane, Duncan; Liu, Hanli; Alexandrakis, George

2015-04-01

Sensorimotor cortex plasticity induced by constraint-induced movement therapy (CIMT) in six children (10.2±2.1 years old) with hemiplegic cerebral palsy was assessed by functional near-infrared spectroscopy (fNIRS). The activation laterality index and time-to-peak/duration during a finger-tapping task and the resting-state functional connectivity were quantified before, immediately after, and 6 months after CIMT. These fNIRS-based metrics were used to help explain changes in clinical scores of manual performance obtained concurrently with imaging time points. Five age-matched healthy children (9.8±1.3 years old) were also imaged to provide comparative activation metrics for normal controls. Interestingly, the activation time-to-peak/duration for all sensorimotor centers displayed significant normalization immediately after CIMT that persisted 6 months later. In contrast to this improved localized activation response, the laterality index and resting-state connectivity metrics that depended on communication between sensorimotor centers improved immediately after CIMT, but relapsed 6 months later. In addition, for the subjects measured in this work, there was either a trade-off between improving unimanual versus bimanual performance when sensorimotor activation patterns normalized after CIMT, or an improvement occurred in both unimanual and bimanual performance but at the cost of very abnormal plastic changes in sensorimotor activity.

Selling points: What cognitive abilities are tapped by casual video games?

PubMed Central

Baniqued, Pauline L.; Lee, Hyunkyu; Voss, Michelle W.; Basak, Chandramallika; Cosman, Joshua D.; DeSouza, Shanna; Severson, Joan; Salthouse, Timothy A.; Kramer, Arthur F.

2013-01-01

The idea that video games or computer-based applications can improve cognitive function has led to a proliferation of programs claiming to “train the brain.” However, there is often little scientific basis in the development of commercial training programs, and many research-based programs yield inconsistent or weak results. In this study, we sought to better understand the nature of cognitive abilities tapped by casual video games and thus reflect on their potential as a training tool. A moderately large sample of participants (n=209) played 20 web-based casual games and performed a battery of cognitive tasks. We used cognitive task analysis and multivariate statistical techniques to characterize the relationships between performance metrics. We validated the cognitive abilities measured in the task battery, examined a task analysis-based categorization of the casual games, and then characterized the relationship between game and task performance. We found that games categorized to tap working memory and reasoning were robustly related to performance on working memory and fluid intelligence tasks, with fluid intelligence best predicting scores on working memory and reasoning games. We discuss these results in the context of overlap in cognitive processes engaged by the cognitive tasks and casual games, and within the context of assessing near and far transfer. While this is not a training study, these findings provide a methodology to assess the validity of using certain games as training and assessment devices for specific cognitive abilities, and shed light on the mixed transfer results in the computer-based training literature. Moreover, the results can inform design of a more theoretically-driven and methodologically-sound cognitive training program. PMID:23246789

Selling points: What cognitive abilities are tapped by casual video games?

PubMed

Baniqued, Pauline L; Lee, Hyunkyu; Voss, Michelle W; Basak, Chandramallika; Cosman, Joshua D; Desouza, Shanna; Severson, Joan; Salthouse, Timothy A; Kramer, Arthur F

2013-01-01

The idea that video games or computer-based applications can improve cognitive function has led to a proliferation of programs claiming to "train the brain." However, there is often little scientific basis in the development of commercial training programs, and many research-based programs yield inconsistent or weak results. In this study, we sought to better understand the nature of cognitive abilities tapped by casual video games and thus reflect on their potential as a training tool. A moderately large sample of participants (n=209) played 20 web-based casual games and performed a battery of cognitive tasks. We used cognitive task analysis and multivariate statistical techniques to characterize the relationships between performance metrics. We validated the cognitive abilities measured in the task battery, examined a task analysis-based categorization of the casual games, and then characterized the relationship between game and task performance. We found that games categorized to tap working memory and reasoning were robustly related to performance on working memory and fluid intelligence tasks, with fluid intelligence best predicting scores on working memory and reasoning games. We discuss these results in the context of overlap in cognitive processes engaged by the cognitive tasks and casual games, and within the context of assessing near and far transfer. While this is not a training study, these findings provide a methodology to assess the validity of using certain games as training and assessment devices for specific cognitive abilities, and shed light on the mixed transfer results in the computer-based training literature. Moreover, the results can inform design of a more theoretically-driven and methodologically-sound cognitive training program. Copyright © 2012 Elsevier B.V. All rights reserved.

Bilateral assessment of functional tasks for robot-assisted therapy applications

PubMed Central

Wang, Sarah; Bai, Ping; Strachota, Elaine; Tchekanov, Guennady; Melbye, Jeff; McGuire, John

2011-01-01

This article presents a novel evaluation system along with methods to evaluate bilateral coordination of arm function on activities of daily living tasks before and after robot-assisted therapy. An affordable bilateral assessment system (BiAS) consisting of two mini-passive measuring units modeled as three degree of freedom robots is described. The process for evaluating functional tasks using the BiAS is presented and we demonstrate its ability to measure wrist kinematic trajectories. Three metrics, phase difference, movement overlap, and task completion time, are used to evaluate the BiAS system on a bilateral symmetric (bi-drink) and a bilateral asymmetric (bi-pour) functional task. Wrist position and velocity trajectories are evaluated using these metrics to provide insight into temporal and spatial bilateral deficits after stroke. The BiAS system quantified movements of the wrists during functional tasks and detected differences in impaired and unimpaired arm movements. Case studies showed that stroke patients compared to healthy subjects move slower and are less likely to use their arm simultaneously even when the functional task requires simultaneous movement. After robot-assisted therapy, interlimb coordination spatial deficits moved toward normal coordination on functional tasks. PMID:21881901

Improving Separation Assurance Stability Through Trajectory Flexibility Preservation

NASA Technical Reports Server (NTRS)

Idris, Husni; Shen, Ni; Wing, David J.

2010-01-01

New information and automation technologies are enabling the distribution of tasks and decisions from the service providers to the users of the air traffic system, with potential capacity and cost benefits. This distribution of tasks and decisions raises the concern that independent user actions will decrease the predictability and increase the complexity of the traffic system, hence inhibiting and possibly reversing any potential benefits. One such concern is the adverse impact of uncoordinated actions by individual aircraft on the stability of separation assurance. For example, individual aircraft performing self-separation may resolve predicted losses of separation or conflicts with some traffic, only to result in secondary conflicts with other traffic or with the same traffic later in time. In answer to this concern, this paper proposes metrics for preserving user trajectory flexibility to be used in self-separation along with other objectives. The hypothesis is that preserving trajectory flexibility will naturally reduce the creation of secondary conflicts by bringing about implicit coordination between aircraft. The impact of using these metrics on improving self-separation stability is investigated by measuring the impact on secondary conflicts. The scenarios analyzed include aircraft in en route airspace with each aircraft meeting a required time of arrival in a twenty minute time horizon while maintaining separation from the surrounding traffic and using trajectory flexibility metrics to mitigate the risk of secondary conflicts. Preliminary experiments showed promising results in that the trajectory flexibility preservation reduced the potential for secondary conflicts.

Design of a virtual reality based adaptive response technology for children with autism.

PubMed

Lahiri, Uttama; Bekele, Esubalew; Dohrmann, Elizabeth; Warren, Zachary; Sarkar, Nilanjan

2013-01-01

Children with autism spectrum disorder (ASD) demonstrate potent impairments in social communication skills including atypical viewing patterns during social interactions. Recently, several assistive technologies, particularly virtual reality (VR), have been investigated to address specific social deficits in this population. Some studies have coupled eye-gaze monitoring mechanisms to design intervention strategies. However, presently available systems are designed to primarily chain learning via aspects of one's performance only which affords restricted range of individualization. The presented work seeks to bridge this gap by developing a novel VR-based interactive system with Gaze-sensitive adaptive response technology that can seamlessly integrate VR-based tasks with eye-tracking techniques to intelligently facilitate engagement in tasks relevant to advancing social communication skills. Specifically, such a system is capable of objectively identifying and quantifying one's engagement level by measuring real-time viewing patterns, subtle changes in eye physiological responses, as well as performance metrics in order to adaptively respond in an individualized manner to foster improved social communication skills among the participants. The developed system was tested through a usability study with eight adolescents with ASD. The results indicate the potential of the system to promote improved social task performance along with socially-appropriate mechanisms during VR-based social conversation tasks.

Design of a Virtual Reality Based Adaptive Response Technology for Children With Autism

PubMed Central

Lahiri, Uttama; Bekele, Esubalew; Dohrmann, Elizabeth; Warren, Zachary; Sarkar, Nilanjan

2013-01-01

Children with autism spectrum disorder (ASD) demonstrate potent impairments in social communication skills including atypical viewing patterns during social interactions. Recently, several assistive technologies, particularly virtual reality (VR), have been investigated to address specific social deficits in this population. Some studies have coupled eye-gaze monitoring mechanisms to design intervention strategies. However, presently available systems are designed to primarily chain learning via aspects of one’s performance only which affords restricted range of individualization. The presented work seeks to bridge this gap by developing a novel VR-based interactive system with Gaze-sensitive adaptive response technology that can seamlessly integrate VR-based tasks with eye-tracking techniques to intelligently facilitate engagement in tasks relevant to advancing social communication skills. Specifically, such a system is capable of objectively identifying and quantifying one’s engagement level by measuring real-time viewing patterns, subtle changes in eye physiological responses, as well as performance metrics in order to adaptively respond in an individualized manner to foster improved social communication skills among the participants. The developed system was tested through a usability study with eight adolescents with ASD. The results indicate the potential of the system to promote improved social task performance along with socially-appropriate mechanisms during VR-based social conversation tasks. PMID:23033333

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology.

PubMed

Koch, Julian; Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics.

Understanding neuromotor strategy during functional upper extremity tasks using symbolic dynamics.

PubMed

Nathan, Dominic E; Guastello, Stephen J; Prost, Robert W; Jeutter, Dean C

2012-01-01

The ability to model and quantify brain activation patterns that pertain to natural neuromotor strategy of the upper extremities during functional task performance is critical to the development of therapeutic interventions such as neuroprosthetic devices. The mechanisms of information flow, activation sequence and patterns, and the interaction between anatomical regions of the brain that are specific to movement planning, intention and execution of voluntary upper extremity motor tasks were investigated here. This paper presents a novel method using symbolic dynamics (orbital decomposition) and nonlinear dynamic tools of entropy, self-organization and chaos to describe the underlying structure of activation shifts in regions of the brain that are involved with the cognitive aspects of functional upper extremity task performance. Several questions were addressed: (a) How is it possible to distinguish deterministic or causal patterns of activity in brain fMRI from those that are really random or non-contributory to the neuromotor control process? (b) Can the complexity of activation patterns over time be quantified? (c) What are the optimal ways of organizing fMRI data to preserve patterns of activation, activation levels, and extract meaningful temporal patterns as they evolve over time? Analysis was performed using data from a custom developed time resolved fMRI paradigm involving human subjects (N=18) who performed functional upper extremity motor tasks with varying time delays between the onset of intention and onset of actual movements. The results indicate that there is structure in the data that can be quantified through entropy and dimensional complexity metrics and statistical inference, and furthermore, orbital decomposition is sensitive in capturing the transition of states that correlate with the cognitive aspects of functional task performance.

Improving Attachments of Non-Invasive (Type III) Electronic Data Loggers to Cetaceans

DTIC Science & Technology

2015-09-30

animals in human care will be performed to test and validate this approach. The cadaver trials will enable controlled testing to failure or with both...quantitative metrics and analysis tools to assess the impact of a tag on the animal . Here we will present: 1) the characterization of the mechanical...fine scale motion analysis for swimming animals . 2 APPROACH Our approach is divided into four subtasks: Task 1: Forces and failure modes

Take-over performance in evasive manoeuvres.

PubMed

Happee, Riender; Gold, Christian; Radlmayr, Jonas; Hergeth, Sebastian; Bengler, Klaus

2017-09-01

We investigated after effects of automation in take-over scenarios in a high-end moving-base driving simulator. Drivers performed evasive manoeuvres encountering a blocked lane in highway driving. We compared the performance of drivers 1) during manual driving, 2) after automated driving with eyes on the road while performing the cognitively demanding n-back task, and 3) after automated driving with eyes off the road performing the visually demanding SuRT task. Both minimum time to collision (TTC) and minimum clearance towards the obstacle disclosed a substantial number of near miss events and are regarded as valuable surrogate safety metrics in evasive manoeuvres. TTC proved highly sensitive to the applied definition of colliding paths, and we prefer robust solutions using lane position while disregarding heading. The extended time to collision (ETTC) which takes into account acceleration was close to the more robust conventional TTC. In line with other publications, the initial steering or braking intervention was delayed after using automation compared to manual driving. This resulted in lower TTC values and stronger steering and braking actions. Using automation, effects of cognitive distraction were similar to visual distraction for the intervention time with effects on the surrogate safety metric TTC being larger with visual distraction. However the precision of the evasive manoeuvres was hardly affected with a similar clearance towards the obstacle, similar overshoots and similar excursions to the hard shoulder. Further research is needed to validate and complement the current simulator based results with human behaviour in real world driving conditions. Experiments with real vehicles can disclose possible systematic differences in behaviour, and naturalistic data can serve to validate surrogate safety measures like TTC and obstacle clearance in evasive manoeuvres. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Sparse Contextual Activation for Efficient Visual Re-Ranking.

PubMed

Bai, Song; Bai, Xiang

2016-03-01

In this paper, we propose an extremely efficient algorithm for visual re-ranking. By considering the original pairwise distance in the contextual space, we develop a feature vector called sparse contextual activation (SCA) that encodes the local distribution of an image. Hence, re-ranking task can be simply accomplished by vector comparison under the generalized Jaccard metric, which has its theoretical meaning in the fuzzy set theory. In order to improve the time efficiency of re-ranking procedure, inverted index is successfully introduced to speed up the computation of generalized Jaccard metric. As a result, the average time cost of re-ranking for a certain query can be controlled within 1 ms. Furthermore, inspired by query expansion, we also develop an additional method called local consistency enhancement on the proposed SCA to improve the retrieval performance in an unsupervised manner. On the other hand, the retrieval performance using a single feature may not be satisfactory enough, which inspires us to fuse multiple complementary features for accurate retrieval. Based on SCA, a robust feature fusion algorithm is exploited that also preserves the characteristic of high time efficiency. We assess our proposed method in various visual re-ranking tasks. Experimental results on Princeton shape benchmark (3D object), WM-SRHEC07 (3D competition), YAEL data set B (face), MPEG-7 data set (shape), and Ukbench data set (image) manifest the effectiveness and efficiency of SCA.

Virtual reality robotic surgery warm-up improves task performance in a dry laboratory environment: a prospective randomized controlled study.

PubMed

Lendvay, Thomas S; Brand, Timothy C; White, Lee; Kowalewski, Timothy; Jonnadula, Saikiran; Mercer, Laina D; Khorsand, Derek; Andros, Justin; Hannaford, Blake; Satava, Richard M

2013-06-01

Preoperative simulation warm-up has been shown to improve performance and reduce errors in novice and experienced surgeons, yet existing studies have only investigated conventional laparoscopy. We hypothesized that a brief virtual reality (VR) robotic warm-up would enhance robotic task performance and reduce errors. In a 2-center randomized trial, 51 residents and experienced minimally invasive surgery faculty in General Surgery, Urology, and Gynecology underwent a validated robotic surgery proficiency curriculum on a VR robotic simulator and on the da Vinci surgical robot (Intuitive Surgical Inc). Once they successfully achieved performance benchmarks, surgeons were randomized to either receive a 3- to 5-minute VR simulator warm-up or read a leisure book for 10 minutes before performing similar and dissimilar (intracorporeal suturing) robotic surgery tasks. The primary outcomes compared were task time, tool path length, economy of motion, technical, and cognitive errors. Task time (-29.29 seconds, p = 0.001; 95% CI, -47.03 to -11.56), path length (-79.87 mm; p = 0.014; 95% CI, -144.48 to -15.25), and cognitive errors were reduced in the warm-up group compared with the control group for similar tasks. Global technical errors in intracorporeal suturing (0.32; p = 0.020; 95% CI, 0.06-0.59) were reduced after the dissimilar VR task. When surgeons were stratified by earlier robotic and laparoscopic clinical experience, the more experienced surgeons (n = 17) demonstrated significant improvements from warm-up in task time (-53.5 seconds; p = 0.001; 95% CI, -83.9 to -23.0) and economy of motion (0.63 mm/s; p = 0.007; 95% CI, 0.18-1.09), and improvement in these metrics was not statistically significantly appreciated in the less-experienced cohort (n = 34). We observed significant performance improvement and error reduction rates among surgeons of varying experience after VR warm-up for basic robotic surgery tasks. In addition, the VR warm-up reduced errors on a more complex task (robotic suturing), suggesting the generalizability of the warm-up. Copyright © 2013 American College of Surgeons. All rights reserved.

Virtual Reality Robotic Surgery Warm-Up Improves Task Performance in a Dry Lab Environment: A Prospective Randomized Controlled Study

PubMed Central

Lendvay, Thomas S.; Brand, Timothy C.; White, Lee; Kowalewski, Timothy; Jonnadula, Saikiran; Mercer, Laina; Khorsand, Derek; Andros, Justin; Hannaford, Blake; Satava, Richard M.

2014-01-01

Background Pre-operative simulation “warm-up” has been shown to improve performance and reduce errors in novice and experienced surgeons, yet existing studies have only investigated conventional laparoscopy. We hypothesized a brief virtual reality (VR) robotic warm-up would enhance robotic task performance and reduce errors. Study Design In a two-center randomized trial, fifty-one residents and experienced minimally invasive surgery faculty in General Surgery, Urology, and Gynecology underwent a validated robotic surgery proficiency curriculum on a VR robotic simulator and on the da Vinci surgical robot. Once successfully achieving performance benchmarks, surgeons were randomized to either receive a 3-5 minute VR simulator warm-up or read a leisure book for 10 minutes prior to performing similar and dissimilar (intracorporeal suturing) robotic surgery tasks. The primary outcomes compared were task time, tool path length, economy of motion, technical and cognitive errors. Results Task time (-29.29sec, p=0.001, 95%CI-47.03,-11.56), path length (-79.87mm, p=0.014, 95%CI -144.48,-15.25), and cognitive errors were reduced in the warm-up group compared to the control group for similar tasks. Global technical errors in intracorporeal suturing (0.32, p=0.020, 95%CI 0.06,0.59) were reduced after the dissimilar VR task. When surgeons were stratified by prior robotic and laparoscopic clinical experience, the more experienced surgeons(n=17) demonstrated significant improvements from warm-up in task time (-53.5sec, p=0.001, 95%CI -83.9,-23.0) and economy of motion (0.63mm/sec, p=0.007, 95%CI 0.18,1.09), whereas improvement in these metrics was not statistically significantly appreciated in the less experienced cohort(n=34). Conclusions We observed a significant performance improvement and error reduction rate among surgeons of varying experience after VR warm-up for basic robotic surgery tasks. In addition, the VR warm-up reduced errors on a more complex task (robotic suturing) suggesting the generalizability of the warm-up. PMID:23583618

Metrics for Operator Situation Awareness, Workload, and Performance in Automated Separation Assurance Systems

NASA Technical Reports Server (NTRS)

Strybel, Thomas Z.; Vu, Kim-Phuong L.; Battiste, Vernol; Dao, Arik-Quang; Dwyer, John P.; Landry, Steven; Johnson, Walter; Ho, Nhut

2011-01-01

A research consortium of scientists and engineers from California State University Long Beach (CSULB), San Jose State University Foundation (SJSUF), California State University Northridge (CSUN), Purdue University, and The Boeing Company was assembled to evaluate the impact of changes in roles and responsibilities and new automated technologies, being introduced in the Next Generation Air Transportation System (NextGen), on operator situation awareness (SA) and workload. To meet these goals, consortium members performed systems analyses of NextGen concepts and airspace scenarios, and concurrently evaluated SA, workload, and performance measures to assess their appropriateness for evaluations of NextGen concepts and tools. The following activities and accomplishments were supported by the NRA: a distributed simulation, metric development, systems analysis, part-task simulations, and large-scale simulations. As a result of this NRA, we have gained a greater understanding of situation awareness and its measurement, and have shared our knowledge with the scientific community. This network provides a mechanism for consortium members, colleagues, and students to pursue research on other topics in air traffic management and aviation, thus enabling them to make greater contributions to the field

Millimeter wave sensor requirements for maritime small craft identification

NASA Astrophysics Data System (ADS)

Krapels, Keith; Driggers, Ronald G.; Garcia, Jose; Boettcher, Evelyn; Prather, Dennis; Schuetz, Chrisopher; Samluk, Jesse; Stein, Lee; Kiser, William; Visnansky, Andrew; Grata, Jeremy; Wikner, David; Harris, Russ

2009-09-01

Passive millimeter wave (mmW) imagers have improved in terms of resolution sensitivity and frame rate. Currently, the Office of Naval Research (ONR), along with the US Army Research, Development and Engineering Command, Communications Electronics Research Development and Engineering Center (RDECOM CERDEC) Night Vision and Electronic Sensor Directorate (NVESD), are investigating the current state-of-the-art of mmW imaging systems. The focus of this study was the performance of mmW imaging systems for the task of small watercraft / boat identification field performance. First mmW signatures were collected. This consisted of a set of eight small watercrafts; at 5 different aspects, during the daylight hours over a 48 hour period in the spring of 2008. Target characteristics were measured and characteristic dimension, signatures, and Root Sum Squared of Target's Temperature (RRSΔT) tabulated. Then an eight-alternative, forced choice (8AFC) human perception experiment was developed and conducted at NVESD. The ability of observers to discriminate between small watercraft was quantified. Next, the task difficulty criterion, V50, was quantified by applying this data to NVESD's target acquisition models using the Targeting Task Performance (TTP) metric. These parameters can be used to evaluate sensor field performance for Anti-Terrorism / Force Protection (AT/FP) and navigation tasks for the U.S. Navy, as well as for design and evaluation of imaging passive mmW sensors for both the U.S. Navy and U.S. Coast Guard.

Using machine learning and real-time workload assessment in a high-fidelity UAV simulation environment

NASA Astrophysics Data System (ADS)

Monfort, Samuel S.; Sibley, Ciara M.; Coyne, Joseph T.

2016-05-01

Future unmanned vehicle operations will see more responsibilities distributed among fewer pilots. Current systems typically involve a small team of operators maintaining control over a single aerial platform, but this arrangement results in a suboptimal configuration of operator resources to system demands. Rather than devoting the full-time attention of several operators to a single UAV, the goal should be to distribute the attention of several operators across several UAVs as needed. Under a distributed-responsibility system, operator task load would be continuously monitored, with new tasks assigned based on system needs and operator capabilities. The current paper sought to identify a set of metrics that could be used to assess workload unobtrusively and in near real-time to inform a dynamic tasking algorithm. To this end, we put 20 participants through a variable-difficulty multiple UAV management simulation. We identified a subset of candidate metrics from a larger pool of pupillary and behavioral measures. We then used these metrics as features in a machine learning algorithm to predict workload condition every 60 seconds. This procedure produced an overall classification accuracy of 78%. An automated tasker sensitive to fluctuations in operator workload could be used to efficiently delegate tasks for teams of UAV operators.

The Effects of Sensor Performance as Modeled by Signal Detection Theory on the Performance of Reinforcement Learning in a Target Acquisition Task

NASA Astrophysics Data System (ADS)

Quirion, Nate

Unmanned Aerial Systems (UASs) today are fulfilling more roles than ever before. There is a general push to have these systems feature more advanced autonomous capabilities in the near future. To achieve autonomous behavior requires some unique approaches to control and decision making. More advanced versions of these approaches are able to adapt their own behavior and examine their past experiences to increase their future mission performance. To achieve adaptive behavior and decision making capabilities this study used Reinforcement Learning algorithms. In this research the effects of sensor performance, as modeled through Signal Detection Theory (SDT), on the ability of RL algorithms to accomplish a target localization task are examined. Three levels of sensor sensitivity are simulated and compared to the results of the same system using a perfect sensor. To accomplish the target localization task, a hierarchical architecture used two distinct agents. A simulated human operator is assumed to be a perfect decision maker, and is used in the system feedback. An evaluation of the system is performed using multiple metrics, including episodic reward curves and the time taken to locate all targets. Statistical analyses are employed to detect significant differences in the comparison of steady-state behavior of different systems.

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Schmidt, D. K.; Anderson, M. R.

1985-01-01

Optimal-control-theoretic modeling and frequency-domain analysis is the methodology proposed to evaluate analytically the handling qualities of higher-order manually controlled dynamic systems. Fundamental to the methodology is evaluating the interplay between pilot workload and closed-loop pilot/vehicle performance and stability robustness. The model-based metric for pilot workload is the required pilot phase compensation. Pilot/vehicle performance and loop stability is then evaluated using frequency-domain techniques. When these techniques were applied to the flight-test data for thirty-two highly-augmented fighter configurations, strong correlation was obtained between the analytical and experimental results.

SU-D-204-05: Quantitative Comparison of a High Resolution Micro-Angiographic Fluoroscopic (MAF) Detector with a Standard Flat Panel Detector (FPD) Using the New Metric of Generalized Measured Relative Object Detectability (GM-ROD)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russ, M; Ionita, C; Bednarek, D

Purpose: In endovascular image-guided neuro-interventions, visualization of fine detail is paramount. For example, the ability of the interventionist to visualize the stent struts depends heavily on the x-ray imaging detector performance. Methods: A study to examine the relative performance of the high resolution MAF-CMOS (pixel size 75µm, Nyquist frequency 6.6 cycles/mm) and a standard Flat Panel Detector (pixel size 194µm, Nyquist frequency 2.5 cycles/mm) detectors in imaging a neuro stent was done using the Generalized Measured Relative Object Detectability (GM-ROD) metric. Low quantum noise images of a deployed stent were obtained by averaging 95 frames obtained by both detectors withoutmore » changing other exposure or geometric parameters. The square of the Fourier transform of each image is taken and divided by the generalized normalized noise power spectrum to give an effective measured task-specific signal-to-noise ratio. This expression is then integrated from 0 to each of the detector’s Nyquist frequencies, and the GM-ROD value is determined by taking a ratio of the integrals for the MAF-CMOS to that of the FPD. The lower bound of integration can be varied to emphasize high frequencies in the detector comparisons. Results: The MAF-CMOS detector exhibits vastly superior performance over the FPD when integrating over all frequencies, yielding a GM-ROD value of 63.1. The lower bound of integration was stepped up in increments of 0.5 cycles/mm for higher frequency comparisons. As the lower bound increased, the GM-ROD value was augmented, reflecting the superior performance of the MAF-CMOS in the high frequency regime. Conclusion: GM-ROD is a versatile metric that can provide quantitative detector and task dependent comparisons that can be used as a basis for detector selection. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.« less

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems.

PubMed

Favazza, Christopher P; Fetterly, Kenneth A; Hangiandreou, Nicholas J; Leng, Shuai; Schueler, Beth A

2015-01-01

Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks.

Task-based optimization of image reconstruction in breast CT

NASA Astrophysics Data System (ADS)

Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

2014-03-01

We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

Modeling temporal sequences of cognitive state changes based on a combination of EEG-engagement, EEG-workload, and heart rate metrics

PubMed Central

Stikic, Maja; Berka, Chris; Levendowski, Daniel J.; Rubio, Roberto F.; Tan, Veasna; Korszen, Stephanie; Barba, Douglas; Wurzer, David

2014-01-01

The objective of this study was to investigate the feasibility of physiological metrics such as ECG-derived heart rate and EEG-derived cognitive workload and engagement as potential predictors of performance on different training tasks. An unsupervised approach based on self-organizing neural network (NN) was utilized to model cognitive state changes over time. The feature vector comprised EEG-engagement, EEG-workload, and heart rate metrics, all self-normalized to account for individual differences. During the competitive training process, a linear topology was developed where the feature vectors similar to each other activated the same NN nodes. The NN model was trained and auto-validated on combat marksmanship training data from 51 participants that were required to make “deadly force decisions” in challenging combat scenarios. The trained NN model was cross validated using 10-fold cross-validation. It was also validated on a golf study in which additional 22 participants were asked to complete 10 sessions of 10 putts each. Temporal sequences of the activated nodes for both studies followed the same pattern of changes, demonstrating the generalization capabilities of the approach. Most node transition changes were local, but important events typically caused significant changes in the physiological metrics, as evidenced by larger state changes. This was investigated by calculating a transition score as the sum of subsequent state transitions between the activated NN nodes. Correlation analysis demonstrated statistically significant correlations between the transition scores and subjects' performances in both studies. This paper explored the hypothesis that temporal sequences of physiological changes comprise the discriminative patterns for performance prediction. These physiological markers could be utilized in future training improvement systems (e.g., through neurofeedback), and applied across a variety of training environments. PMID:25414629

Degraded visual environment image/video quality metrics

NASA Astrophysics Data System (ADS)

Baumgartner, Dustin D.; Brown, Jeremy B.; Jacobs, Eddie L.; Schachter, Bruce J.

2014-06-01

A number of image quality metrics (IQMs) and video quality metrics (VQMs) have been proposed in the literature for evaluating techniques and systems for mitigating degraded visual environments. Some require both pristine and corrupted imagery. Others require patterned target boards in the scene. None of these metrics relates well to the task of landing a helicopter in conditions such as a brownout dust cloud. We have developed and used a variety of IQMs and VQMs related to the pilot's ability to detect hazards in the scene and to maintain situational awareness. Some of these metrics can be made agnostic to sensor type. Not only are the metrics suitable for evaluating algorithm and sensor variation, they are also suitable for choosing the most cost effective solution to improve operating conditions in degraded visual environments.

Oriented regions grouping based candidate proposal for infrared pedestrian detection

NASA Astrophysics Data System (ADS)

Wang, Jiangtao; Zhang, Jingai; Li, Huaijiang

2018-04-01

Effectively and accurately locating the positions of pedestrian candidates in image is a key task for the infrared pedestrian detection system. In this work, a novel similarity measuring metric is designed. Based on the selective search scheme, the developed similarity measuring metric is utilized to yield the possible locations for pedestrian candidate. Besides this, corresponding diversification strategies are also provided according to the characteristics of the infrared thermal imaging system. Experimental results indicate that the presented scheme can achieve more efficient outputs than the traditional selective search methodology for the infrared pedestrian detection task.

Development and Application of a Clinical Microsystem Simulation Methodology for Human Factors-Based Research of Alarm Fatigue.

PubMed

Kobayashi, Leo; Gosbee, John W; Merck, Derek L

2017-07-01

(1) To develop a clinical microsystem simulation methodology for alarm fatigue research with a human factors engineering (HFE) assessment framework and (2) to explore its application to the comparative examination of different approaches to patient monitoring and provider notification. Problems with the design, implementation, and real-world use of patient monitoring systems result in alarm fatigue. A multidisciplinary team is developing an open-source tool kit to promote bedside informatics research and mitigate alarm fatigue. Simulation, HFE, and computer science experts created a novel simulation methodology to study alarm fatigue. Featuring multiple interconnected simulated patient scenarios with scripted timeline, "distractor" patient care tasks, and triggered true and false alarms, the methodology incorporated objective metrics to assess provider and system performance. Developed materials were implemented during institutional review board-approved study sessions that assessed and compared an experimental multiparametric alerting system with a standard monitor telemetry system for subject response, use characteristics, and end-user feedback. A four-patient simulation setup featuring objective metrics for participant task-related performance and response to alarms was developed along with accompanying structured HFE assessment (questionnaire and interview) for monitor systems use testing. Two pilot and four study sessions with individual nurse subjects elicited true alarm and false alarm responses (including diversion from assigned tasks) as well as nonresponses to true alarms. In-simulation observation and subject questionnaires were used to test the experimental system's approach to suppressing false alarms and alerting providers. A novel investigative methodology applied simulation and HFE techniques to replicate and study alarm fatigue in controlled settings for systems assessment and experimental research purposes.

Neurophysiologic monitoring of mental workload and fatigue during operation of a flight simulator

NASA Astrophysics Data System (ADS)

Smith, Michael E.; Gevins, Alan

2005-05-01

In one experiment, EEG recordings were made during a daytime session while 16 well-rested participants performed versions of a PC flight simulator task that were either low, moderate, or high in difficulty. In another experiment, the same subjects repeatedly performed high difficulty versions of the same task during an all night session with total sleep deprivation. Multivariate EEG metrics of cortical activation were derived for frontal brain regions essential for working memory and executive control processes that are presumably important for maintaining situational awareness, central brain regions essential for sensorimotor control, and posterior parietal and occipital regions essential for visuoperceptual processing. During the daytime session each of these regional measures displayed greater activation during the high difficulty task than during the low difficulty task, and degree of cortical activation was positively correlated with subjective workload ratings in these well-rested subjects. During the overnight session, cortical activation declined with time-on-task, and the degree of this decline over frontal regions was negatively correlated with subjective workload ratings. Since participants were already highly skilled in the task, such changes likely reflect fatigue-related diminishment of frontal executive capability rather than practice effects. These findings suggest that the success of efforts to gauge mental workload via proxy cortical activation measures in the context of adaptive automation systems will likely depend on use of user models that take both task demands and the operator"s state of alertness into account. Further methodological development of the measurement approach outlined here would be required to achieve a practical, effective objective means for monitoring transient changes in cognitive brain function during performance of complex real-world tasks.

Detecting switching and intermittent causalities in time series

NASA Astrophysics Data System (ADS)

Zanin, Massimiliano; Papo, David

2017-04-01

During the last decade, complex network representations have emerged as a powerful instrument for describing the cross-talk between different brain regions both at rest and as subjects are carrying out cognitive tasks, in healthy brains and neurological pathologies. The transient nature of such cross-talk has nevertheless by and large been neglected, mainly due to the inherent limitations of some metrics, e.g., causality ones, which require a long time series in order to yield statistically significant results. Here, we present a methodology to account for intermittent causal coupling in neural activity, based on the identification of non-overlapping windows within the original time series in which the causality is strongest. The result is a less coarse-grained assessment of the time-varying properties of brain interactions, which can be used to create a high temporal resolution time-varying network. We apply the proposed methodology to the analysis of the brain activity of control subjects and alcoholic patients performing an image recognition task. Our results show that short-lived, intermittent, local-scale causality is better at discriminating both groups than global network metrics. These results highlight the importance of the transient nature of brain activity, at least under some pathological conditions.

Touch Interaction with 3D Geographical Visualization on Web: Selected Technological and User Issues

NASA Astrophysics Data System (ADS)

Herman, L.; Stachoň, Z.; Stuchlík, R.; Hladík, J.; Kubíček, P.

2016-10-01

The use of both 3D visualization and devices with touch displays is increasing. In this paper, we focused on the Web technologies for 3D visualization of spatial data and its interaction via touch screen gestures. At the first stage, we compared the support of touch interaction in selected JavaScript libraries on different hardware (desktop PCs with touch screens, tablets, and smartphones) and software platforms. Afterward, we realized simple empiric test (within-subject design, 6 participants, 2 simple tasks, LCD touch monitor Acer and digital terrain models as stimuli) focusing on the ability of users to solve simple spatial tasks via touch screens. An in-house testing web tool was developed and used based on JavaScript, PHP, and X3DOM languages and Hammer.js libraries. The correctness of answers, speed of users' performances, used gestures, and a simple gesture metric was recorded and analysed. Preliminary results revealed that the pan gesture is most frequently used by test participants and it is also supported by the majority of 3D libraries. Possible gesture metrics and future developments including the interpersonal differences are discussed in the conclusion.

Smartphone App-Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability.

PubMed

Manor, Brad; Yu, Wanting; Zhu, Hao; Harrison, Rachel; Lo, On-Yee; Lipsitz, Lewis; Travison, Thomas; Pascual-Leone, Alvaro; Zhou, Junhong

2018-01-30

Walking is a complex cognitive motor task that is commonly completed while performing another task such as talking or making decisions. Gait assessments performed under normal and "dual-task" walking conditions thus provide important insights into health. Such assessments, however, are limited primarily to laboratory-based settings. The objective of our study was to create and test a smartphone-based assessment of normal and dual-task walking for use in nonlaboratory settings. We created an iPhone app that used the phone's motion sensors to record movements during walking under normal conditions and while performing a serial-subtraction dual task, with the phone placed in the user's pants pocket. The app provided the user with multimedia instructions before and during the assessment. Acquired data were automatically uploaded to a cloud-based server for offline analyses. A total of 14 healthy adults completed 2 laboratory visits separated by 1 week. On each visit, they used the app to complete three 45-second trials each of normal and dual-task walking. Kinematic data were collected with the app and a gold-standard-instrumented GAITRite mat. Participants also used the app to complete normal and dual-task walking trials within their homes on 3 separate days. Within laboratory-based trials, GAITRite-derived heel strikes and toe-offs of the phone-side leg aligned with smartphone acceleration extrema, following filtering and rotation to the earth coordinate system. We derived stride times-a clinically meaningful metric of locomotor control-from GAITRite and app data, for all strides occurring over the GAITRite mat. We calculated stride times and the dual-task cost to the average stride time (ie, percentage change from normal to dual-task conditions) from both measurement devices. We calculated similar metrics from home-based app data. For these trials, periods of potential turning were identified via custom-developed algorithms and omitted from stride-time analyses. Across all detected strides in the laboratory, stride times derived from the app and GAITRite mat were highly correlated (P<.001, r 2 =.98). These correlations were independent of walking condition and pocket tightness. App- and GAITRite-derived stride-time dual-task costs were also highly correlated (P<.001, r 2 =.95). The error of app-derived stride times (mean 16.9, SD 9.0 ms) was unaffected by the magnitude of stride time, walking condition, or pocket tightness. For both normal and dual-task trials, average stride times derived from app walking trials demonstrated excellent test-retest reliability within and between both laboratory and home-based assessments (intraclass correlation coefficient range .82-.94). The iPhone app we created enabled valid and reliable assessment of stride timing-with the smartphone in the pocket-during both normal and dual-task walking and within both laboratory and nonlaboratory environments. Additional work is warranted to expand the functionality of this tool to older adults and other patient populations. ©Brad Manor, Wanting Yu, Hao Zhu, Rachel Harrison, On-Yee Lo, Lewis Lipsitz, Thomas Travison, Alvaro Pascual-Leone, Junhong Zhou. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 30.01.2018.

The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty.

PubMed

Churchill, Nathan W; Spring, Robyn; Grady, Cheryl; Cimprich, Bernadine; Askren, Mary K; Reuter-Lorenz, Patricia A; Jung, Mi Sook; Peltier, Scott; Strother, Stephen C; Berman, Marc G

2016-08-08

There is growing evidence that fluctuations in brain activity may exhibit scale-free ("fractal") dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f(-β), where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement.

The suppression of scale-free fMRI brain dynamics across three different sources of effort: aging, task novelty and task difficulty

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Grady, Cheryl; Cimprich, Bernadine; Askren, Mary K.; Reuter-Lorenz, Patricia A.; Jung, Mi Sook; Peltier, Scott; Strother, Stephen C.; Berman, Marc G.

2016-01-01

There is growing evidence that fluctuations in brain activity may exhibit scale-free (“fractal”) dynamics. Scale-free signals follow a spectral-power curve of the form P(f ) ∝ f−β, where spectral power decreases in a power-law fashion with increasing frequency. In this study, we demonstrated that fractal scaling of BOLD fMRI signal is consistently suppressed for different sources of cognitive effort. Decreases in the Hurst exponent (H), which quantifies scale-free signal, was related to three different sources of cognitive effort/task engagement: 1) task difficulty, 2) task novelty, and 3) aging effects. These results were consistently observed across multiple datasets and task paradigms. We also demonstrated that estimates of H are robust across a range of time-window sizes. H was also compared to alternative metrics of BOLD variability (SDBOLD) and global connectivity (Gconn), with effort-related decreases in H producing similar decreases in SDBOLD and Gconn. These results indicate a potential global brain phenomenon that unites research from different fields and indicates that fractal scaling may be a highly sensitive metric for indexing cognitive effort/task engagement. PMID:27498696

Modeling Alzheimer's disease cognitive scores using multi-task sparse group lasso.

PubMed

Liu, Xiaoli; Goncalves, André R; Cao, Peng; Zhao, Dazhe; Banerjee, Arindam

2018-06-01

Alzheimer's disease (AD) is a severe neurodegenerative disorder characterized by loss of memory and reduction in cognitive functions due to progressive degeneration of neurons and their connections, eventually leading to death. In this paper, we consider the problem of simultaneously predicting several different cognitive scores associated with categorizing subjects as normal, mild cognitive impairment (MCI), or Alzheimer's disease (AD) in a multi-task learning framework using features extracted from brain images obtained from ADNI (Alzheimer's Disease Neuroimaging Initiative). To solve the problem, we present a multi-task sparse group lasso (MT-SGL) framework, which estimates sparse features coupled across tasks, and can work with loss functions associated with any Generalized Linear Models. Through comparisons with a variety of baseline models using multiple evaluation metrics, we illustrate the promising predictive performance of MT-SGL on ADNI along with its ability to identify brain regions more likely to help the characterization Alzheimer's disease progression. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cognitive Styles, Demographic Attributes, Task Performance and Affective Experiences: An Empirical Investigation into Astrophysics Data System (ADS) Core Users

NASA Astrophysics Data System (ADS)

Tong, Rong

As a primary digital library portal for astrophysics researchers, SAO/NASA ADS (Astrophysics Data System) 2.0 interface features several visualization tools such as Author Network and Metrics. This research study involves 20 ADS long term users who participated in a usability and eye tracking research session. Participants first completed a cognitive test, and then performed five tasks in ADS 2.0 where they explored its multiple visualization tools. Results show that over half of the participants were Imagers and half of the participants were Analytic. Cognitive styles were found to have significant impacts on several efficiency-based measures. Analytic-oriented participants were observed to spent shorter time on web pages and apps, made fewer web page changes than less-Analytic-driving participants in performing common tasks, whereas AI (Analytic-Imagery) participants also completed their five tasks faster than non-AI participants. Meanwhile, self-identified Imagery participants were found to be more efficient in their task completion through multiple measures including total time on task, number of mouse clicks, and number of query revisions made. Imagery scores were negatively associated with frequency of confusion and the observed counts of being surprised. Compared to those who did not claimed to be a visual person, self-identified Imagery participants were observed to have significantly less frequency in frustration and hesitation during their task performance. Both demographic variables and past user experiences were found to correlate with task performance; query revision also correlated with multiple time-based measurements. Considered as an indicator of efficiency, query revisions were found to correlate negatively with the rate of complete with ease, and positively with several time-based efficiency measures, rate of complete with some difficulty, and the frequency of frustration. These results provide rich insights into the cognitive styles of ADS' core users, the impact of such styles and demographic attributes on their task performance their affective and cognitive experiences, and their interaction behaviors while using the visualization component of ADS 2.0, and would subsequently contribute to the design of bibliographic retrieval systems for scientists.

The Metrics of Spatial Distance Traversed During Mental Imagery

ERIC Educational Resources Information Center

Rinck, Mike; Denis, Michel

2004-01-01

The authors conducted 2 experiments to study the metrics of spatial distance in a mental imagery task. In both experiments, participants first memorized the layout of a building containing 10 rooms with 24 objects. Participants then received mental imagery instructions and imagined how they walked through the building from one room to another. The…

Lexical and Metrical Stress in Word Recognition: Lexical or Pre-Lexical Influences?

ERIC Educational Resources Information Center

Slowiaczek, Louisa M.; Soltano, Emily G.; Bernstein, Hilary L.

2006-01-01

The influence of lexical stress and/or metrical stress on spoken word recognition was examined. Two experiments were designed to determine whether response times in lexical decision or shadowing tasks are influenced when primes and targets share lexical stress patterns (JUVenile-BIBlical [Syllables printed in capital letters indicate those…

Metrical Encoding in Adults Who Do and Do Not Stutter

ERIC Educational Resources Information Center

Coalson, Geoffrey A.; Byrd, Courtney T.

2015-01-01

Purpose: The purpose of this study was to explore metrical aspects of phonological encoding (i.e., stress and syllable boundary assignment) in adults who do and do not stutter (AWS and AWNS, respectively). Method: Participants monitored nonwords for target sounds during silent phoneme monitoring tasks across two distinct experiments. For…

Time takes space: selective effects of multitasking on concurrent spatial processing.

PubMed

Mäntylä, Timo; Coni, Valentina; Kubik, Veit; Todorov, Ivo; Del Missier, Fabio

2017-08-01

Many everyday activities require coordination and monitoring of complex relations of future goals and deadlines. Cognitive offloading may provide an efficient strategy for reducing control demands by representing future goals and deadlines as a pattern of spatial relations. We tested the hypothesis that multiple-task monitoring involves time-to-space transformational processes, and that these spatial effects are selective with greater demands on coordinate (metric) than categorical (nonmetric) spatial relation processing. Participants completed a multitasking session in which they monitored four series of deadlines, running on different time scales, while making concurrent coordinate or categorical spatial judgments. We expected and found that multitasking taxes concurrent coordinate, but not categorical, spatial processing. Furthermore, males showed a better multitasking performance than females. These findings provide novel experimental evidence for the hypothesis that efficient multitasking involves metric relational processing.

Quantum Algorithm for K-Nearest Neighbors Classification Based on the Metric of Hamming Distance

NASA Astrophysics Data System (ADS)

Ruan, Yue; Xue, Xiling; Liu, Heng; Tan, Jianing; Li, Xi

2017-11-01

K-nearest neighbors (KNN) algorithm is a common algorithm used for classification, and also a sub-routine in various complicated machine learning tasks. In this paper, we presented a quantum algorithm (QKNN) for implementing this algorithm based on the metric of Hamming distance. We put forward a quantum circuit for computing Hamming distance between testing sample and each feature vector in the training set. Taking advantage of this method, we realized a good analog for classical KNN algorithm by setting a distance threshold value t to select k - n e a r e s t neighbors. As a result, QKNN achieves O( n 3) performance which is only relevant to the dimension of feature vectors and high classification accuracy, outperforms Llyod's algorithm (Lloyd et al. 2013) and Wiebe's algorithm (Wiebe et al. 2014).

Perceived assessment metrics for visible and infrared color fused image quality without reference image

NASA Astrophysics Data System (ADS)

Yu, Xuelian; Chen, Qian; Gu, Guohua; Ren, Jianle; Sui, Xiubao

2015-02-01

Designing objective quality assessment of color-fused image is a very demanding and challenging task. We propose four no-reference metrics based on human visual system characteristics for objectively evaluating the quality of false color fusion image. The perceived edge metric (PEM) is defined based on visual perception model and color image gradient similarity between the fused image and the source images. The perceptual contrast metric (PCM) is established associating multi-scale contrast and varying contrast sensitivity filter (CSF) with color components. The linear combination of the standard deviation and mean value over the fused image construct the image colorfulness metric (ICM). The color comfort metric (CCM) is designed by the average saturation and the ratio of pixels with high and low saturation. The qualitative and quantitative experimental results demonstrate that the proposed metrics have a good agreement with subjective perception.

Ideal AFROC and FROC observers.

PubMed

Khurd, Parmeshwar; Liu, Bin; Gindi, Gene

2010-02-01

Detection of multiple lesions in images is a medically important task and free-response receiver operating characteristic (FROC) analyses and its variants, such as alternative FROC (AFROC) analyses, are commonly used to quantify performance in such tasks. However, ideal observers that optimize FROC or AFROC performance metrics have not yet been formulated in the general case. If available, such ideal observers may turn out to be valuable for imaging system optimization and in the design of computer aided diagnosis techniques for lesion detection in medical images. In this paper, we derive ideal AFROC and FROC observers. They are ideal in that they maximize, amongst all decision strategies, the area, or any partial area, under the associated AFROC or FROC curve. Calculation of observer performance for these ideal observers is computationally quite complex. We can reduce this complexity by considering forms of these observers that use false positive reports derived from signal-absent images only. We also consider a Bayes risk analysis for the multiple-signal detection task with an appropriate definition of costs. A general decision strategy that minimizes Bayes risk is derived. With particular cost constraints, this general decision strategy reduces to the decision strategy associated with the ideal AFROC or FROC observer.

Assessing the learning curve for the acquisition of laparoscopic skills on a virtual reality simulator.

PubMed

Sherman, V; Feldman, L S; Stanbridge, D; Kazmi, R; Fried, G M

2005-05-01

The aim of this study was to develop summary metrics and assess the construct validity for a virtual reality laparoscopic simulator (LapSim) by comparing the learning curves of three groups with different levels of laparoscopic expertise. Three groups of subjects ('expert', 'junior', and 'naïve') underwent repeated trials on three LapSim tasks. Formulas were developed to calculate scores for efficiency ('time-error') and economy of 'motion' ('motion') using metrics generated by the software after each drill. Data (mean +/- SD) were evaluated by analysis of variance (ANOVA). Significance was set at p < 0.05. All three groups improved significantly from baseline to final for both 'time-error' and 'motion' scores. There were significant differences between groups in time error performances at baseline and final, due to higher scores in the 'expert' group. A significant difference in 'motion' scores was seen only at baseline. We have developed summary metrics for the LapSim that differentiate among levels of laparoscopic experience. This study also provides evidence of construct validity for the LapSim.

Thoughts on Earned Value Assessments

NASA Technical Reports Server (NTRS)

Pido, Kelle

2009-01-01

This slide presentation reviews the concepts of Earned Value reporting and Earned Value Metrics (EVM) and the implementation for the Constellation Program. EVM is used to manage both the contract and civil service workforce, and used as a measure of contractor costs and performance. The Program EVM is not as useful for Level of Effort tasking, for either contractor, or civil service employees. Some issues and concerns in reference to EVM and the process for the use of EVM for Mission assurance are reviewed,

Space station definition and preliminary design, WP-01. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Lenda, J. A.

1987-01-01

System activities are summarized and an overview of the system level engineering tasks performed are provided. Areas discussed include requirements, system test and verification, the advanced development plan, customer accommodations, software, growth, productivity, operations, product assurance and metrication. The hardware element study results are summarized. Overviews of recommended configurations are provided for the core module, the USL, the logistics elements, the propulsion subsystems, reboost, vehicle accommodations, and the smart front end. A brief overview is provided for costing activities.

No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control

PubMed Central

Saunders, Blair; He, Frank F. H.; Inzlicht, Michael

2015-01-01

It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude—operationalized by experimental condition or as a continuous predictor—and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes. PMID:26633830

No Evidence That Gratitude Enhances Neural Performance Monitoring or Conflict-Driven Control.

PubMed

Saunders, Blair; He, Frank F H; Inzlicht, Michael

2015-01-01

It has recently been suggested that gratitude can benefit self-regulation by reducing impulsivity during economic decision making. We tested if comparable benefits of gratitude are observed for neural performance monitoring and conflict-driven self-control. In a pre-post design, 61 participants were randomly assigned to either a gratitude or happiness condition, and then performed a pre-induction flanker task. Subsequently, participants recalled an autobiographical event where they had felt grateful or happy, followed by a post-induction flanker task. Despite closely following existing protocols, participants in the gratitude condition did not report elevated gratefulness compared to the happy group. In regard to self-control, we found no association between gratitude--operationalized by experimental condition or as a continuous predictor--and any control metric, including flanker interference, post-error adjustments, or neural monitoring (the error-related negativity, ERN). Thus, while gratitude might increase economic patience, such benefits may not generalize to conflict-driven control processes.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks.

PubMed

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-06-26

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H²RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H²RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller.

The impact of crosstalk on three-dimensional laparoscopic performance and workload.

PubMed

Sakata, Shinichiro; Grove, Philip M; Watson, Marcus O; Stevenson, Andrew R L

2017-10-01

This is the first study to explore the effects of crosstalk from 3D laparoscopic displays on technical performance and workload. We studied crosstalk at magnitudes that may have been tolerated during laparoscopic surgery. Participants were 36 voluntary doctors. To minimize floor effects, participants completed their surgery rotations, and a laparoscopic suturing course for surgical trainees. We used a counterbalanced, within-subjects design in which participants were randomly assigned to complete laparoscopic tasks in one of six unique testing sequences. In a simulation laboratory, participants were randomly assigned to complete laparoscopic 'navigation in space' and suturing tasks in three viewing conditions: 2D, 3D without ghosting and 3D with ghosting. Participants calibrated their exposure to crosstalk as the maximum level of ghosting that they could tolerate without discomfort. The Randot® Stereotest was used to verify stereoacuity. The study performance metric was time to completion. The NASA TLX was used to measure workload. Normal threshold stereoacuity (40-20 second of arc) was verified in all participants. Comparing optimal 3D with 2D viewing conditions, mean performance times were 2.8 and 1.6 times faster in laparoscopic navigation in space and suturing tasks respectively (p< .001). Comparing optimal 3D with suboptimal 3D viewing conditions, mean performance times were 2.9 times faster in both tasks (p< .001). Mean workload in 2D was 1.5 and 1.3 times greater than in optimal 3D viewing, for navigation in space and suturing tasks respectively (p< .001). Mean workload associated with suboptimal 3D was 1.3 times greater than optimal 3D in both laparoscopic tasks (p< .001). There was no significant relationship between the magnitude of ghosting score, laparoscopic performance and workload. Our findings highlight the advantages of 3D displays when used optimally, and their shortcomings when used sub-optimally, on both laparoscopic performance and workload.

International Space Station Increment Operations Services

NASA Astrophysics Data System (ADS)

Michaelis, Horst; Sielaff, Christian

2002-01-01

The Industrial Operator (IO) has defined End-to-End services to perform efficiently all required operations tasks for the Manned Space Program (MSP) as agreed during the Ministerial Council in Edinburgh in November 2001. Those services are the result of a detailed task analysis based on the operations processes as derived from the Space Station Program Implementation Plans (SPIP) and defined in the Operations Processes Documents (OPD). These services are related to ISS Increment Operations and ATV Mission Operations. Each of these End-to-End services is typically characterised by the following properties: It has a clearly defined starting point, where all requirements on the end-product are fixed and associated performance metrics of the customer are well defined. It has a clearly defined ending point, when the product or service is delivered to the customer and accepted by him, according to the performance metrics defined at the start point. The implementation of the process might be restricted by external boundary conditions and constraints mutually agreed with the customer. As far as those are respected the IO has the free choice to select methods and means of implementation. The ISS Increment Operations Service (IOS) activities required for the MSP Exploitation program cover the complete increment specific cycle starting with the support to strategic planning and ending with the post increment evaluation. These activities are divided into sub-services including the following tasks: - ISS Planning Support covering the support to strategic and tactical planning up to the generation - Development &Payload Integration Support - ISS Increment Preparation - ISS Increment Execution These processes are tight together by the Increment Integration Management, which provides the planning and scheduling of all activities as well as the technical management of the overall process . The paper describes the entire End-to-End ISS Increment Operations service and the implementation to support the Columbus Flight 1E related increment and subsequent ISS increments. Special attention is paid to the implications caused by long term operations on hardware, software and operations personnel.

Optimizing spectral CT parameters for material classification tasks

NASA Astrophysics Data System (ADS)

Rigie, D. S.; La Rivière, P. J.

2016-06-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies.

Optimizing Spectral CT Parameters for Material Classification Tasks

PubMed Central

Rigie, D. S.; La Rivière, P. J.

2017-01-01

In this work, we propose a framework for optimizing spectral CT imaging parameters and hardware design with regard to material classification tasks. Compared with conventional CT, many more parameters must be considered when designing spectral CT systems and protocols. These choices will impact material classification performance in a non-obvious, task-dependent way with direct implications for radiation dose reduction. In light of this, we adapt Hotelling Observer formalisms typically applied to signal detection tasks to the spectral CT, material-classification problem. The result is a rapidly computable metric that makes it possible to sweep out many system configurations, generating parameter optimization curves (POC’s) that can be used to select optimal settings. The proposed model avoids restrictive assumptions about the basis-material decomposition (e.g. linearity) and incorporates signal uncertainty with a stochastic object model. This technique is demonstrated on dual-kVp and photon-counting systems for two different, clinically motivated material classification tasks (kidney stone classification and plaque removal). We show that the POC’s predicted with the proposed analytic model agree well with those derived from computationally intensive numerical simulation studies. PMID:27227430

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands

PubMed Central

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M.; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n-back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks. PMID:28553215

EEG Cortical Connectivity Analysis of Working Memory Reveals Topological Reorganization in Theta and Alpha Bands.

PubMed

Dai, Zhongxiang; de Souza, Joshua; Lim, Julian; Ho, Paul M; Chen, Yu; Li, Junhua; Thakor, Nitish; Bezerianos, Anastasios; Sun, Yu

2017-01-01

Numerous studies have revealed various working memory (WM)-related brain activities that originate from various cortical regions and oscillate at different frequencies. However, multi-frequency band analysis of the brain network in WM in the cortical space remains largely unexplored. In this study, we employed a graph theoretical framework to characterize the topological properties of the brain functional network in the theta and alpha frequency bands during WM tasks. Twenty-eight subjects performed visual n -back tasks at two difficulty levels, i.e., 0-back (control task) and 2-back (WM task). After preprocessing, Electroencephalogram (EEG) signals were projected into the source space and 80 cortical brain regions were selected for further analysis. Subsequently, the theta- and alpha-band networks were constructed by calculating the Pearson correlation coefficients between the power series (obtained by concatenating the power values of all epochs in each session) of all pairs of brain regions. Graph theoretical approaches were then employed to estimate the topological properties of the brain networks at different WM tasks. We found higher functional integration in the theta band and lower functional segregation in the alpha band in the WM task compared with the control task. Moreover, compared to the 0-back task, altered regional centrality was revealed in the 2-back task in various brain regions that mainly resided in the frontal, temporal and occipital lobes, with distinct presentations in the theta and alpha bands. In addition, significant negative correlations were found between the reaction time with the average path length of the theta-band network and the local clustering of the alpha-band network, which demonstrates the potential for using the brain network metrics as biomarkers for predicting the task performance during WM tasks.

Enhanced Data Representation by Kernel Metric Learning for Dementia Diagnosis

PubMed Central

Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German

2017-01-01

Alzheimer's disease (AD) is the kind of dementia that affects the most people around the world. Therefore, an early identification supporting effective treatments is required to increase the life quality of a wide number of patients. Recently, computer-aided diagnosis tools for dementia using Magnetic Resonance Imaging scans have been successfully proposed to discriminate between patients with AD, mild cognitive impairment, and healthy controls. Most of the attention has been given to the clinical data, provided by initiatives as the ADNI, supporting reliable researches on intervention, prevention, and treatments of AD. Therefore, there is a need for improving the performance of classification machines. In this paper, we propose a kernel framework for learning metrics that enhances conventional machines and supports the diagnosis of dementia. Our framework aims at building discriminative spaces through the maximization of center kernel alignment function, aiming at improving the discrimination of the three considered neurological classes. The proposed metric learning performance is evaluated on the widely-known ADNI database using three supervised classification machines (k-nn, SVM and NNs) for multi-class and bi-class scenarios from structural MRIs. Specifically, from ADNI collection 286 AD patients, 379 MCI patients and 231 healthy controls are used for development and validation of our proposed metric learning framework. For the experimental validation, we split the data into two subsets: 30% of subjects used like a blindfolded assessment and 70% employed for parameter tuning. Then, in the preprocessing stage, each structural MRI scan a total of 310 morphological measurements are automatically extracted from by FreeSurfer software package and concatenated to build an input feature matrix. Obtained test performance results, show that including a supervised metric learning improves the compared baseline classifiers in both scenarios. In the multi-class scenario, we achieve the best performance (accuracy 60.1%) for pretrained 1-layered NN, and we obtain measures over 90% in the average for HC vs. AD task. From the machine learning point of view, our proposal enhances the classifier performance by building spaces with a better class separability. From the clinical application, our enhancement results in a more balanced performance in each class than the compared approaches from the CADDementia challenge by increasing the sensitivity of pathological groups and the specificity of healthy controls. PMID:28798659

Machine learning of network metrics in ATLAS Distributed Data Management

NASA Astrophysics Data System (ADS)

Lassnig, Mario; Toler, Wesley; Vamosi, Ralf; Bogado, Joaquin; ATLAS Collaboration

2017-10-01

The increasing volume of physics data poses a critical challenge to the ATLAS experiment. In anticipation of high luminosity physics, automation of everyday data management tasks has become necessary. Previously many of these tasks required human decision-making and operation. Recent advances in hardware and software have made it possible to entrust more complicated duties to automated systems using models trained by machine learning algorithms. In this contribution we show results from one of our ongoing automation efforts that focuses on network metrics. First, we describe our machine learning framework built atop the ATLAS Analytics Platform. This framework can automatically extract and aggregate data, train models with various machine learning algorithms, and eventually score the resulting models and parameters. Second, we use these models to forecast metrics relevant for networkaware job scheduling and data brokering. We show the characteristics of the data and evaluate the forecasting accuracy of our models.

Monitoring cognitive function and need with the automated neuropsychological assessment metrics in Decompression Sickness (DCS) research

NASA Technical Reports Server (NTRS)

Nesthus, Thomas E.; Schiflett, Sammuel G.

1993-01-01

Hypobaric decompression sickness (DCS) research presents the medical monitor with the difficult task of assessing the onset and progression of DCS largely on the basis of subjective symptoms. Even with the introduction of precordial Doppler ultrasound techniques for the detection of venous gas emboli (VGE), correct prediction of DCS can be made only about 65 percent of the time according to data from the Armstrong Laboratory's (AL's) hypobaric DCS database. An AL research protocol concerned with exercise and its effects on denitrogenation efficiency includes implementation of a performance assessment test battery to evaluate cognitive functioning during a 4-h simulated 30,000 ft (9144 m) exposure. Information gained from such a test battery may assist the medical monitor in identifying early signs of DCS and subtle neurologic dysfunction related to cases of asymptomatic, but advanced, DCS. This presentation concerns the selection and integration of a test battery and the timely graphic display of subject test results for the principal investigator and medical monitor. A subset of the Automated Neuropsychological Assessment Metrics (ANAM) developed through the Office of Military Performance Assessment Technology (OMPAT) was selected. The ANAM software provides a library of simple tests designed for precise measurement of processing efficiency in a variety of cognitive domains. For our application and time constraints, two tests requiring high levels of cognitive processing and memory were chosen along with one test requiring fine psychomotor performance. Accuracy, speed, and processing throughout variables as well as RMS error were collected. An automated mood survey provided 'state' information on six scales including anger, happiness, fear, depression, activity, and fatigue. An integrated and interactive LOTUS 1-2-3 macro was developed to import and display past and present task performance and mood-change information.

Cognitive-motor integration deficits in young adult athletes following concussion.

PubMed

Brown, Jeffrey A; Dalecki, Marc; Hughes, Cindy; Macpherson, Alison K; Sergio, Lauren E

2015-01-01

The ability to perform visually-guided motor tasks requires the transformation of visual information into programmed motor outputs. When the guiding visual information does not align spatially with the motor output, the brain processes rules to integrate the information for an appropriate motor response. Here, we look at how performance on such tasks is affected in young adult athletes with concussion history. Participants displaced a cursor from a central to peripheral targets on a vertical display by sliding their finger along a touch sensitive screen in one of two spatial planes. The addition of a memory component, along with variations in cursor feedback increased task complexity across conditions. Significant main effects between participants with concussion history and healthy controls without concussion history were observed in timing and accuracy measures. Importantly, the deficits were distinctly more pronounced for participants with concussion history compared to healthy controls, especially when the brain had to control movements having two levels of decoupling between vision and action. A discriminant analysis correctly classified athletes with a history of concussion based on task performance with an accuracy of 94 %, despite the majority of these athletes being rated asymptomatic by current standards. These findings correspond to our previous work with adults at risk of developing dementia, and support the use of cognitive motor integration as an enhanced assessment tool for those who may have mild brain dysfunction. Such a task may provide a more sensitive metric of performance relevant to daily function than what is currently in use, to assist in return to play/work/learn decisions.

Smartphone App–Based Assessment of Gait During Normal and Dual-Task Walking: Demonstration of Validity and Reliability

PubMed Central

Yu, Wanting; Zhu, Hao; Harrison, Rachel; Lo, On-Yee; Lipsitz, Lewis; Travison, Thomas; Pascual-Leone, Alvaro; Zhou, Junhong

2018-01-01

Background Walking is a complex cognitive motor task that is commonly completed while performing another task such as talking or making decisions. Gait assessments performed under normal and “dual-task” walking conditions thus provide important insights into health. Such assessments, however, are limited primarily to laboratory-based settings. Objective The objective of our study was to create and test a smartphone-based assessment of normal and dual-task walking for use in nonlaboratory settings. Methods We created an iPhone app that used the phone’s motion sensors to record movements during walking under normal conditions and while performing a serial-subtraction dual task, with the phone placed in the user’s pants pocket. The app provided the user with multimedia instructions before and during the assessment. Acquired data were automatically uploaded to a cloud-based server for offline analyses. A total of 14 healthy adults completed 2 laboratory visits separated by 1 week. On each visit, they used the app to complete three 45-second trials each of normal and dual-task walking. Kinematic data were collected with the app and a gold-standard–instrumented GAITRite mat. Participants also used the app to complete normal and dual-task walking trials within their homes on 3 separate days. Within laboratory-based trials, GAITRite-derived heel strikes and toe-offs of the phone-side leg aligned with smartphone acceleration extrema, following filtering and rotation to the earth coordinate system. We derived stride times—a clinically meaningful metric of locomotor control—from GAITRite and app data, for all strides occurring over the GAITRite mat. We calculated stride times and the dual-task cost to the average stride time (ie, percentage change from normal to dual-task conditions) from both measurement devices. We calculated similar metrics from home-based app data. For these trials, periods of potential turning were identified via custom-developed algorithms and omitted from stride-time analyses. Results Across all detected strides in the laboratory, stride times derived from the app and GAITRite mat were highly correlated (P<.001, r2=.98). These correlations were independent of walking condition and pocket tightness. App- and GAITRite-derived stride-time dual-task costs were also highly correlated (P<.001, r2=.95). The error of app-derived stride times (mean 16.9, SD 9.0 ms) was unaffected by the magnitude of stride time, walking condition, or pocket tightness. For both normal and dual-task trials, average stride times derived from app walking trials demonstrated excellent test-retest reliability within and between both laboratory and home-based assessments (intraclass correlation coefficient range .82-.94). Conclusions The iPhone app we created enabled valid and reliable assessment of stride timing—with the smartphone in the pocket—during both normal and dual-task walking and within both laboratory and nonlaboratory environments. Additional work is warranted to expand the functionality of this tool to older adults and other patient populations. PMID:29382625

Functional MRI of Handwriting Tasks: A Study of Healthy Young Adults Interacting with a Novel Touch-Sensitive Tablet

PubMed Central

Karimpoor, Mahta; Churchill, Nathan W.; Tam, Fred; Fischer, Corinne E.; Schweizer, Tom A.; Graham, Simon J.

2018-01-01

Handwriting is a complex human activity that engages a blend of cognitive and visual motor skills. Current understanding of the neural correlates of handwriting has largely come from lesion studies of patients with impaired handwriting. Task-based fMRI studies would be useful to supplement this work. To address concerns over ecological validity, previously we developed a fMRI-compatible, computerized tablet system for writing and drawing including visual feedback of hand position and an augmented reality display. The purpose of the present work is to use the tablet system in proof-of-concept to characterize brain activity associated with clinically relevant handwriting tasks, originally developed to characterize handwriting impairments in Alzheimer’s disease patients. As a prelude to undertaking fMRI studies of patients, imaging was performed of twelve young healthy subjects who copied sentences, phone numbers, and grocery lists using the fMRI-compatible tablet. Activation maps for all handwriting tasks consisted of a distributed network of regions in reasonable agreement with previous studies of handwriting performance. In addition, differences in brain activity were observed between the test subcomponents consistent with different demands of neural processing for successful task performance, as identified by investigating three quantitative behavioral metrics (writing speed, stylus contact force and stylus in air time). This study provides baseline behavioral and brain activity results for fMRI studies that adopt this handwriting test to characterize patients with brain impairments. PMID:29487511

Functional MRI of Handwriting Tasks: A Study of Healthy Young Adults Interacting with a Novel Touch-Sensitive Tablet.

PubMed

Karimpoor, Mahta; Churchill, Nathan W; Tam, Fred; Fischer, Corinne E; Schweizer, Tom A; Graham, Simon J

2018-01-01

Handwriting is a complex human activity that engages a blend of cognitive and visual motor skills. Current understanding of the neural correlates of handwriting has largely come from lesion studies of patients with impaired handwriting. Task-based fMRI studies would be useful to supplement this work. To address concerns over ecological validity, previously we developed a fMRI-compatible, computerized tablet system for writing and drawing including visual feedback of hand position and an augmented reality display. The purpose of the present work is to use the tablet system in proof-of-concept to characterize brain activity associated with clinically relevant handwriting tasks, originally developed to characterize handwriting impairments in Alzheimer's disease patients. As a prelude to undertaking fMRI studies of patients, imaging was performed of twelve young healthy subjects who copied sentences, phone numbers, and grocery lists using the fMRI-compatible tablet. Activation maps for all handwriting tasks consisted of a distributed network of regions in reasonable agreement with previous studies of handwriting performance. In addition, differences in brain activity were observed between the test subcomponents consistent with different demands of neural processing for successful task performance, as identified by investigating three quantitative behavioral metrics (writing speed, stylus contact force and stylus in air time). This study provides baseline behavioral and brain activity results for fMRI studies that adopt this handwriting test to characterize patients with brain impairments.

Numerical aerodynamic simulation facility. Preliminary study extension

NASA Technical Reports Server (NTRS)

1978-01-01

The production of an optimized design of key elements of the candidate facility was the primary objective of this report. This was accomplished by effort in the following tasks: (1) to further develop, optimize and describe the function description of the custom hardware; (2) to delineate trade off areas between performance, reliability, availability, serviceability, and programmability; (3) to develop metrics and models for validation of the candidate systems performance; (4) to conduct a functional simulation of the system design; (5) to perform a reliability analysis of the system design; and (6) to develop the software specifications to include a user level high level programming language, a correspondence between the programming language and instruction set and outline the operation system requirements.

On using multiple routing metrics with destination sequenced distance vector protocol for MultiHop wireless ad hoc networks

NASA Astrophysics Data System (ADS)

Mehic, M.; Fazio, P.; Voznak, M.; Partila, P.; Komosny, D.; Tovarek, J.; Chmelikova, Z.

2016-05-01

A mobile ad hoc network is a collection of mobile nodes which communicate without a fixed backbone or centralized infrastructure. Due to the frequent mobility of nodes, routes connecting two distant nodes may change. Therefore, it is not possible to establish a priori fixed paths for message delivery through the network. Because of its importance, routing is the most studied problem in mobile ad hoc networks. In addition, if the Quality of Service (QoS) is demanded, one must guarantee the QoS not only over a single hop but over an entire wireless multi-hop path which may not be a trivial task. In turns, this requires the propagation of QoS information within the network. The key to the support of QoS reporting is QoS routing, which provides path QoS information at each source. To support QoS for real-time traffic one needs to know not only minimum delay on the path to the destination but also the bandwidth available on it. Therefore, throughput, end-to-end delay, and routing overhead are traditional performance metrics used to evaluate the performance of routing protocol. To obtain additional information about the link, most of quality-link metrics are based on calculation of the lost probabilities of links by broadcasting probe packets. In this paper, we address the problem of including multiple routing metrics in existing routing packets that are broadcasted through the network. We evaluate the efficiency of such approach with modified version of DSDV routing protocols in ns-3 simulator.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

Citizen science: A new perspective to advance spatial pattern evaluation in hydrology

PubMed Central

Stisen, Simon

2017-01-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning often make humans more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which inevitably gives benefits such as speed and the possibility to automatize processes. However, the human vision can be harnessed to evaluate the reliability of algorithms which are tailored to quantify similarity in spatial patterns. We established a citizen science project to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of several scenarios of a hydrological catchment model. In total, the turnout counts more than 2500 volunteers that provided over 43000 classifications of 1095 individual subjects. We investigate the capability of a set of advanced statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric. The obtained dataset can provide an insightful benchmark to the community to test novel spatial metrics. PMID:28558050

Sensorimotor Synchronization with Different Metrical Levels of Point-Light Dance Movements.

PubMed

Su, Yi-Huang

2016-01-01

Rhythm perception and synchronization have been extensively investigated in the auditory domain, as they underlie means of human communication such as music and speech. Although recent studies suggest comparable mechanisms for synchronizing with periodically moving visual objects, the extent to which it applies to ecologically relevant information, such as the rhythm of complex biological motion, remains unknown. The present study addressed this issue by linking rhythm of music and dance in the framework of action-perception coupling. As a previous study showed that observers perceived multiple metrical periodicities in dance movements that embodied this structure, the present study examined whether sensorimotor synchronization (SMS) to dance movements resembles what is known of auditory SMS. Participants watched a point-light figure performing two basic steps of Swing dance cyclically, in which the trunk bounced at every beat and the limbs moved at every second beat, forming two metrical periodicities. Participants tapped synchronously to the bounce of the trunk with or without the limbs moving in the stimuli (Experiment 1), or tapped synchronously to the leg movements with or without the trunk bouncing simultaneously (Experiment 2). Results showed that, while synchronization with the bounce (lower-level pulse) was not influenced by the presence or absence of limb movements (metrical accent), synchronization with the legs (beat) was improved by the presence of the bounce (metrical subdivision) across different movement types. The latter finding parallels the "subdivision benefit" often demonstrated in auditory tasks, suggesting common sensorimotor mechanisms for visual rhythms in dance and auditory rhythms in music.

Objective assessment based on motion-related metrics and technical performance in laparoscopic suturing.

PubMed

Sánchez-Margallo, Juan A; Sánchez-Margallo, Francisco M; Oropesa, Ignacio; Enciso, Silvia; Gómez, Enrique J

2017-02-01

The aim of this study is to present the construct and concurrent validity of a motion-tracking method of laparoscopic instruments based on an optical pose tracker and determine its feasibility as an objective assessment tool of psychomotor skills during laparoscopic suturing. A group of novice ([Formula: see text] laparoscopic procedures), intermediate (11-100 laparoscopic procedures) and experienced ([Formula: see text] laparoscopic procedures) surgeons performed three intracorporeal sutures on an ex vivo porcine stomach. Motion analysis metrics were recorded using the proposed tracking method, which employs an optical pose tracker to determine the laparoscopic instruments' position. Construct validation was measured for all 10 metrics across the three groups and between pairs of groups. Concurrent validation was measured against a previously validated suturing checklist. Checklists were completed by two independent surgeons over blinded video recordings of the task. Eighteen novices, 15 intermediates and 11 experienced surgeons took part in this study. Execution time and path length travelled by the laparoscopic dissector presented construct validity. Experienced surgeons required significantly less time ([Formula: see text]), travelled less distance using both laparoscopic instruments ([Formula: see text]) and made more efficient use of the work space ([Formula: see text]) compared with novice and intermediate surgeons. Concurrent validation showed strong correlation between both the execution time and path length and the checklist score ([Formula: see text] and [Formula: see text], [Formula: see text]). The suturing performance was successfully assessed by the motion analysis method. Construct and concurrent validity of the motion-based assessment method has been demonstrated for the execution time and path length metrics. This study demonstrates the efficacy of the presented method for objective evaluation of psychomotor skills in laparoscopic suturing. However, this method does not take into account the quality of the suture. Thus, future works will focus on developing new methods combining motion analysis and qualitative outcome evaluation to provide a complete performance assessment to trainees.

Neural decoding with kernel-based metric learning.

PubMed

Brockmeier, Austin J; Choi, John S; Kriminger, Evan G; Francis, Joseph T; Principe, Jose C

2014-06-01

In studies of the nervous system, the choice of metric for the neural responses is a pivotal assumption. For instance, a well-suited distance metric enables us to gauge the similarity of neural responses to various stimuli and assess the variability of responses to a repeated stimulus-exploratory steps in understanding how the stimuli are encoded neurally. Here we introduce an approach where the metric is tuned for a particular neural decoding task. Neural spike train metrics have been used to quantify the information content carried by the timing of action potentials. While a number of metrics for individual neurons exist, a method to optimally combine single-neuron metrics into multineuron, or population-based, metrics is lacking. We pose the problem of optimizing multineuron metrics and other metrics using centered alignment, a kernel-based dependence measure. The approach is demonstrated on invasively recorded neural data consisting of both spike trains and local field potentials. The experimental paradigm consists of decoding the location of tactile stimulation on the forepaws of anesthetized rats. We show that the optimized metrics highlight the distinguishing dimensions of the neural response, significantly increase the decoding accuracy, and improve nonlinear dimensionality reduction methods for exploratory neural analysis.

Microgravity Science and Applications. Program Tasks and Bibliography for FY 1993

NASA Technical Reports Server (NTRS)

1994-01-01

An annual report published by the Microgravity Science and Applications Division (MSAD) of NASA is presented. It represents a compilation of the Division's currently-funded ground, flight and Advanced Technology Development tasks. An overview and progress report for these tasks, including progress reports by principal investigators selected from the academic, industry and government communities, are provided. The document includes a listing of new bibliographic data provided by the principal investigators to reflect the dissemination of research data during FY 1993 via publications and presentations. The document also includes division research metrics and an index of the funded investigators. The document contains three sections and three appendices: Section 1 includes an introduction and metrics data, Section 2 is a compilation of the task reports in an order representative of its ground, flight or ATD status and the science discipline it represents, and Section 3 is the bibliography. The three appendices, in the order of presentation, are: Appendix A - a microgravity science acronym list, Appendix B - a list of guest investigators associated with a biotechnology task, and Appendix C - an index of the currently funded principal investigators.

Compensatory Saccades Are Associated With Physical Performance in Older Adults: Data From the Baltimore Longitudinal Study of Aging.

PubMed

Xie, Yanjun; Anson, Eric R; Simonsick, Eleanor M; Studenski, Stephanie A; Agrawal, Yuri

2017-03-01

To determine whether compensatory saccade metrics observed in the video head impulse test, specifically saccade amplitude and latency, predict physical performance. Cross-sectional analysis of the Baltimore Longitudinal Study of Aging, a prospective cohort study. National Institute on Aging Intramural Research Program Clinical Research Unit in Baltimore, Maryland. Community-dwelling older adults. Video head impulse testing was performed, and compensatory saccades and horizontal vestibulo-ocular reflex (VOR) gain were measured. Physical performance was assessed using the Short Physical Performance Battery (SPPB), which included the feet side-by-side, semitandem, tandem, and single-leg stance; repeated chair stands; and usual gait speed measurements. Compensatory saccade amplitude and latency, VOR gain, and SPPB performance. In 183 participants who underwent vestibular and SPPB testing (mean age 71.8 yr; 53% females), both higher mean saccade amplitude (odds ratio [OR] =1.62, p = 0.010) and shorter mean saccade latency (OR = 0.88, p = 0.004) were associated with a higher odds of failing the tandem stand task. In contrast, VOR gain was not associated with any physical performance measure. We observed in a cohort of healthy older adults that compensatory saccade amplitude and latency were associated with tandem stance performance. Compensatory saccade metrics may provide insights into capturing the impact of vestibular loss on physical function in older adults.

Development of Methodologies, Metrics, and Tools for Investigating Human-Robot Interaction in Space Robotics

NASA Technical Reports Server (NTRS)

Ezer, Neta; Zumbado, Jennifer Rochlis; Sandor, Aniko; Boyer, Jennifer

2011-01-01

Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator (SPDM), Robonaut, and Space Exploration Vehicle (SEV), as well as interviews with robotics trainers, robot operators, and developers of gesture interfaces. A survey of methods and metrics used in HRI was completed to identify those most applicable to space robotics. These methods and metrics included techniques and tools associated with task performance, the quantification of human-robot interactions and communication, usability, human workload, and situation awareness. The need for more research in areas such as natural interfaces, compensations for loss of signal and poor video quality, psycho-physiological feedback, and common HRI testbeds were identified. The initial findings from these activities and planned future research are discussed. Human-robot systems are expected to have a central role in future space exploration missions that extend beyond low-earth orbit [1]. As part of a directed research project funded by NASA s Human Research Program (HRP), researchers at the Johnson Space Center have started to use a variety of techniques, including literature reviews, case studies, knowledge capture, field studies, and experiments to understand critical human-robot interaction (HRI) variables for current and future systems. Activities accomplished to date include observations of the International Space Station s Special Purpose Dexterous Manipulator (SPDM), Robonaut, and Space Exploration Vehicle (SEV), as well as interviews with robotics trainers, robot operators, and developers of gesture interfaces. A survey of methods and metrics used in HRI was completed to identify those most applicable to space robotics. These methods and metrics included techniques and tools associated with task performance, the quantification of human-robot interactions and communication, usability, human workload, and situation awareness. The need for more research in areas such as natural interfaces, compensations for loss of signal and poor video quality, psycho-physiological feedback, and common HRI testbeds were identified. The initial findings from these activities and planned future research are discussed.

Selective preservation of the beat in apperceptive music agnosia: a case study.

PubMed

Baird, Amee D; Walker, David G; Biggs, Vivien; Robinson, Gail A

2014-04-01

Music perception involves processing of melodic, temporal and emotional dimensions that have been found to dissociate in healthy individuals and after brain injury. Two components of the temporal dimension have been distinguished, namely rhythm and metre. We describe an 18 year old male musician 'JM' who showed apperceptive music agnosia with selectively preserved metre perception, and impaired recognition of sad and peaceful music relative to age and music experience matched controls after resection of a right temporoparietal tumour. Two months post-surgery JM underwent a comprehensive neuropsychological evaluation including assessment of his music perception abilities using the Montreal Battery for Evaluation of Amusia (MBEA, Peretz, Champod, & Hyde, 2003). He also completed several experimental tasks to explore his ability to recognise famous songs and melodies, emotions portrayed by music and a broader range of environmental sounds. Five age-, gender-, education- and musical experienced-matched controls were administered the same experimental tasks. JM showed selective preservation of metre perception, with impaired performances compared to controls and scoring below the 5% cut-off on all MBEA subtests, except for the metric condition. He could identify his favourite songs and environmental sounds. He showed impaired recognition of sad and peaceful emotions portrayed in music relative to controls but intact ability to identify happy and scary music. This case study contributes to the scarce literature documenting a dissociation between rhythmic and metric processing, and the rare observation of selectively preserved metric interpretation in the context of apperceptive music agnosia. It supports the notion that the anterior portion of the superior temporal gyrus (STG) plays a role in metric processing and provides the novel observation that selectively preserved metre is sufficient to identify happy and scary, but not sad or peaceful emotions portrayed in music. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

A novel augmented reality simulator for skills assessment in minimal invasive surgery.

PubMed

Lahanas, Vasileios; Loukas, Constantinos; Smailis, Nikolaos; Georgiou, Evangelos

2015-08-01

Over the past decade, simulation-based training has come to the foreground as an efficient method for training and assessment of surgical skills in minimal invasive surgery. Box-trainers and virtual reality (VR) simulators have been introduced in the teaching curricula and have substituted to some extent the traditional model of training based on animals or cadavers. Augmented reality (AR) is a new technology that allows blending of VR elements and real objects within a real-world scene. In this paper, we present a novel AR simulator for assessment of basic laparoscopic skills. The components of the proposed system include: a box-trainer, a camera and a set of laparoscopic tools equipped with custom-made sensors that allow interaction with VR training elements. Three AR tasks were developed, focusing on basic skills such as perception of depth of field, hand-eye coordination and bimanual operation. The construct validity of the system was evaluated via a comparison between two experience groups: novices with no experience in laparoscopic surgery and experienced surgeons. The observed metrics included task execution time, tool pathlength and two task-specific errors. The study also included a feedback questionnaire requiring participants to evaluate the face-validity of the system. Between-group comparison demonstrated highly significant differences (<0.01) in all performance metrics and tasks denoting the simulator's construct validity. Qualitative analysis on the instruments' trajectories highlighted differences between novices and experts regarding smoothness and economy of motion. Subjects' ratings on the feedback questionnaire highlighted the face-validity of the training system. The results highlight the potential of the proposed simulator to discriminate groups with different expertise providing a proof of concept for the potential use of AR as a core technology for laparoscopic simulation training.

Multivariate analyses of individual variation in soccer skill as a tool for talent identification and development: utilising evolutionary theory in sports science.

PubMed

Wilson, Robbie S; James, Rob S; David, Gwendolyn; Hermann, Ecki; Morgan, Oliver J; Niehaus, Amanda C; Hunter, Andrew; Thake, Doug; Smith, Michelle D

2016-11-01

The development of a comprehensive protocol for quantifying soccer-specific skill could markedly improve both talent identification and development. Surprisingly, most protocols for talent identification in soccer still focus on the more generic athletic attributes of team sports, such as speed, strength, agility and endurance, rather than on a player's technical skills. We used a multivariate methodology borrowed from evolutionary analyses of adaptation to develop our quantitative assessment of individual soccer-specific skill. We tested the performance of 40 individual academy-level players in eight different soccer-specific tasks across an age range of 13-18 years old. We first quantified the repeatability of each skill performance then explored the effects of age on soccer-specific skill, correlations between each of the pairs of skill tasks independent of age, and finally developed an individual metric of overall skill performance that could be easily used by coaches. All of our measured traits were highly repeatable when assessed over a short period and we found that an individual's overall skill - as well as their performance in their best task - was strongly positively correlated with age. Most importantly, our study established a simple but comprehensive methodology for assessing skill performance in soccer players, thus allowing coaches to rapidly assess the relative abilities of their players, identify promising youths and work on eliminating skill deficits in players.

Speech-perception training for older adults with hearing loss impacts word recognition and effort.

PubMed

Kuchinsky, Stefanie E; Ahlstrom, Jayne B; Cute, Stephanie L; Humes, Larry E; Dubno, Judy R; Eckert, Mark A

2014-10-01

The current pupillometry study examined the impact of speech-perception training on word recognition and cognitive effort in older adults with hearing loss. Trainees identified more words at the follow-up than at the baseline session. Training also resulted in an overall larger and faster peaking pupillary response, even when controlling for performance and reaction time. Perceptual and cognitive capacities affected the peak amplitude of the pupil response across participants but did not diminish the impact of training on the other pupil metrics. Thus, we demonstrated that pupillometry can be used to characterize training-related and individual differences in effort during a challenging listening task. Importantly, the results indicate that speech-perception training not only affects overall word recognition, but also a physiological metric of cognitive effort, which has the potential to be a biomarker of hearing loss intervention outcome. Copyright © 2014 Society for Psychophysiological Research.

Implementation of a channelized Hotelling observer model to assess image quality of x-ray angiography systems

PubMed Central

Favazza, Christopher P.; Fetterly, Kenneth A.; Hangiandreou, Nicholas J.; Leng, Shuai; Schueler, Beth A.

2015-01-01

Abstract. Evaluation of flat-panel angiography equipment through conventional image quality metrics is limited by the scope of standard spatial-domain image quality metric(s), such as contrast-to-noise ratio and spatial resolution, or by restricted access to appropriate data to calculate Fourier domain measurements, such as modulation transfer function, noise power spectrum, and detective quantum efficiency. Observer models have been shown capable of overcoming these limitations and are able to comprehensively evaluate medical-imaging systems. We present a spatial domain-based channelized Hotelling observer model to calculate the detectability index (DI) of our different sized disks and compare the performance of different imaging conditions and angiography systems. When appropriate, changes in DIs were compared to expectations based on the classical Rose model of signal detection to assess linearity of the model with quantum signal-to-noise ratio (SNR) theory. For these experiments, the estimated uncertainty of the DIs was less than 3%, allowing for precise comparison of imaging systems or conditions. For most experimental variables, DI changes were linear with expectations based on quantum SNR theory. DIs calculated for the smallest objects demonstrated nonlinearity with quantum SNR theory due to system blur. Two angiography systems with different detector element sizes were shown to perform similarly across the majority of the detection tasks. PMID:26158086

EVA: laparoscopic instrument tracking based on Endoscopic Video Analysis for psychomotor skills assessment.

PubMed

Oropesa, Ignacio; Sánchez-González, Patricia; Chmarra, Magdalena K; Lamata, Pablo; Fernández, Alvaro; Sánchez-Margallo, Juan A; Jansen, Frank Willem; Dankelman, Jenny; Sánchez-Margallo, Francisco M; Gómez, Enrique J

2013-03-01

The EVA (Endoscopic Video Analysis) tracking system is a new system for extracting motions of laparoscopic instruments based on nonobtrusive video tracking. The feasibility of using EVA in laparoscopic settings has been tested in a box trainer setup. EVA makes use of an algorithm that employs information of the laparoscopic instrument's shaft edges in the image, the instrument's insertion point, and the camera's optical center to track the three-dimensional position of the instrument tip. A validation study of EVA comprised a comparison of the measurements achieved with EVA and the TrEndo tracking system. To this end, 42 participants (16 novices, 22 residents, and 4 experts) were asked to perform a peg transfer task in a box trainer. Ten motion-based metrics were used to assess their performance. Construct validation of the EVA has been obtained for seven motion-based metrics. Concurrent validation revealed that there is a strong correlation between the results obtained by EVA and the TrEndo for metrics, such as path length (ρ = 0.97), average speed (ρ = 0.94), or economy of volume (ρ = 0.85), proving the viability of EVA. EVA has been successfully validated in a box trainer setup, showing the potential of endoscopic video analysis to assess laparoscopic psychomotor skills. The results encourage further implementation of video tracking in training setups and image-guided surgery.

Fully Automatic Speech-Based Analysis of the Semantic Verbal Fluency Task.

PubMed

König, Alexandra; Linz, Nicklas; Tröger, Johannes; Wolters, Maria; Alexandersson, Jan; Robert, Phillipe

2018-06-08

Semantic verbal fluency (SVF) tests are routinely used in screening for mild cognitive impairment (MCI). In this task, participants name as many items as possible of a semantic category under a time constraint. Clinicians measure task performance manually by summing the number of correct words and errors. More fine-grained variables add valuable information to clinical assessment, but are time-consuming. Therefore, the aim of this study is to investigate whether automatic analysis of the SVF could provide these as accurate as manual and thus, support qualitative screening of neurocognitive impairment. SVF data were collected from 95 older people with MCI (n = 47), Alzheimer's or related dementias (ADRD; n = 24), and healthy controls (HC; n = 24). All data were annotated manually and automatically with clusters and switches. The obtained metrics were validated using a classifier to distinguish HC, MCI, and ADRD. Automatically extracted clusters and switches were highly correlated (r = 0.9) with manually established values, and performed as well on the classification task separating HC from persons with ADRD (area under curve [AUC] = 0.939) and MCI (AUC = 0.758). The results show that it is possible to automate fine-grained analyses of SVF data for the assessment of cognitive decline. © 2018 S. Karger AG, Basel.

Analysis of Trajectory Flexibility Preservation Impact on Traffic Complexity

NASA Technical Reports Server (NTRS)

Idris, Husni; El-Wakil, Tarek; Wing, David J.

2009-01-01

The growing demand for air travel is increasing the need for mitigation of air traffic congestion and complexity problems, which are already at high levels. At the same time new information and automation technologies are enabling the distribution of tasks and decisions from the service providers to the users of the air traffic system, with potential capacity and cost benefits. This distribution of tasks and decisions raises the concern that independent user actions will decrease the predictability and increase the complexity of the traffic system, hence inhibiting and possibly reversing any potential benefits. In answer to this concern, the authors proposed the introduction of decision-making metrics for preserving user trajectory flexibility. The hypothesis is that such metrics will make user actions naturally mitigate traffic complexity. In this paper, the impact of using these metrics on traffic complexity is investigated. The scenarios analyzed include aircraft in en route airspace with each aircraft meeting a required time of arrival in a one-hour time horizon while mitigating the risk of loss of separation with the other aircraft, thus preserving its trajectory flexibility. The experiments showed promising results in that the individual trajectory flexibility preservation induced self-separation and self-organization effects in the overall traffic situation. The effects were quantified using traffic complexity metrics, namely dynamic density indicators, which indicated that using the flexibility metrics reduced aircraft density and the potential of loss of separation.

The role of uncertainty and reward on eye movements in a virtual driving task

PubMed Central

Sullivan, Brian T.; Johnson, Leif; Rothkopf, Constantin A.; Ballard, Dana; Hayhoe, Mary

2012-01-01

Eye movements during natural tasks are well coordinated with ongoing task demands and many variables could influence gaze strategies. Sprague and Ballard (2003) proposed a gaze-scheduling model that uses a utility-weighted uncertainty metric to prioritize fixations on task-relevant objects and predicted that human gaze should be influenced by both reward structure and task-relevant uncertainties. To test this conjecture, we tracked the eye movements of participants in a simulated driving task where uncertainty and implicit reward (via task priority) were varied. Participants were instructed to simultaneously perform a Follow Task where they followed a lead car at a specific distance and a Speed Task where they drove at an exact speed. We varied implicit reward by instructing the participants to emphasize one task over the other and varied uncertainty in the Speed Task with the presence or absence of uniform noise added to the car's velocity. Subjects' gaze data were classified for the image content near fixation and segmented into looks. Gaze measures, including look proportion, duration and interlook interval, showed that drivers more closely monitor the speedometer if it had a high level of uncertainty, but only if it was also associated with high task priority or implicit reward. The interaction observed appears to be an example of a simple mechanism whereby the reduction of visual uncertainty is gated by behavioral relevance. This lends qualitative support for the primary variables controlling gaze allocation proposed in the Sprague and Ballard model. PMID:23262151

Building an Evaluation Scale using Item Response Theory.

PubMed

Lalor, John P; Wu, Hao; Yu, Hong

2016-11-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.

Building an Evaluation Scale using Item Response Theory

PubMed Central

Lalor, John P.; Wu, Hao; Yu, Hong

2016-01-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.1 PMID:28004039

Laparoscopic and robotic skills are transferable in a simulation setting: a randomized controlled trial.

PubMed

Thomaier, Lauren; Orlando, Megan; Abernethy, Melinda; Paka, Chandhana; Chen, Chi Chiung Grace

2017-08-01

Although surgical simulation provides an effective supplement to traditional training, it is not known whether skills are transferable between minimally invasive surgical modalities. The purpose of this study was to assess the transferability of skills between minimally invasive surgical simulation platforms among simulation-naïve participants. Forty simulation-naïve medical students were enrolled in this randomized single-blinded controlled trial. Participants completed a baseline evaluation on laparoscopic (Fundamentals of Laparoscopic Surgery Program, Los Angeles, CA) and robotic (dV-Trainer, Mimic, Seattle, WA) simulation peg transfer tasks. Participants were then randomized to perform a practice session on either the robotic (N = 20) or laparoscopic (N = 20) simulator. Two blinded, expert minimally invasive surgeons evaluated participants before and after training using a modified previously validated subjective global rating scale. Objective measures including time to task completion and Mimic dV-Trainer motion metrics were also recorded. At baseline, there were no significant differences between the training groups as measured by objective and subjective measures for either simulation task. After training, participants randomized to the laparoscopic practice group completed the laparoscopic task faster (p < 0.003) and with higher global rating scale scores (p < 0.001) than the robotic group. Robotic-trained participants performed the robotic task faster (p < 0.001), with improved economy of motion (p < 0.001), and with higher global rating scale scores (p = 0.006) than the laparoscopic group. The robotic practice group also demonstrated significantly improved performance on the laparoscopic task (p = 0.02). Laparoscopic-trained participants also improved their robotic performance (p = 0.02), though the robotic group had a higher percent improvement on the robotic task (p = 0.037). Skills acquired through practice on either laparoscopic or robotic simulation platforms appear to be transferable between modalities. However, participants demonstrate superior skill in the modality in which they specifically train.

Validation of a short-term memory test for the recognition of people and faces.

PubMed

Leyk, D; Sievert, A; Heiss, A; Gorges, W; Ridder, D; Alexander, T; Wunderlich, M; Ruther, T

2008-08-01

Memorising and processing faces is a short-term memory dependent task of utmost importance in the security domain, in which constant and high performance is a must. Especially in access or passport control-related tasks, the timely identification of performance decrements is essential, margins of error are narrow and inadequate performance may have grave consequences. However, conventional short-term memory tests frequently use abstract settings with little relevance to working situations. They may thus be unable to capture task-specific decrements. The aim of the study was to devise and validate a new test, better reflecting job specifics and employing appropriate stimuli. After 1.5 s (short) or 4.5 s (long) presentation, a set of seven portraits of faces had to be memorised for comparison with two control stimuli. Stimulus appearance followed 2 s (first item) and 8 s (second item) after set presentation. Twenty eight subjects (12 male, 16 female) were tested at seven different times of day, 3 h apart. Recognition rates were above 60% even for the least favourable condition. Recognition was significantly better in the 'long' condition (+10%) and for the first item (+18%). Recognition time showed significant differences (10%) between items. Minor effects of learning were found for response latencies only. Based on occupationally relevant metrics, the test displayed internal and external validity, consistency and suitability for further use in test/retest scenarios. In public security, especially where access to restricted areas is monitored, margins of error are narrow and operator performance must remain high and level. Appropriate schedules for personnel, based on valid test results, are required. However, task-specific data and performance tests, permitting the description of task specific decrements, are not available. Commonly used tests may be unsuitable due to undue abstraction and insufficient reference to real-world conditions. Thus, tests are required that account for task-specific conditions and neurophysiological characteristics.

Area of Concern: a new paradigm in life cycle assessment for ...

EPA Pesticide Factsheets

Purpose: As a class of environmental metrics, footprints have been poorly defined, have shared an unclear relationship to life cycle assessment (LCA), and the variety of approaches to quantification have sometimes resulted in confusing and contradictory messages in the marketplace. In response, a task force operating under the auspices of the UNEP/SETAC Life Cycle Initiative project on environmental life cycle impact assessment (LCIA) has been working to develop generic guidance for developers of footprint metrics. The purpose of this paper is to introduce a universal footprint definition and related terminology as well as to discuss modelling implications.MethodsThe task force has worked from the perspective that footprints should be based on LCA methodology, underpinned by the same data systems and models as used in LCA. However, there are important differences in purpose and orientation relative to LCA impact category indicators. Footprints have a primary orientation toward society and nontechnical stakeholders. They are also typically of narrow scope, having the purpose of reporting only in relation to specific topics. In comparison, LCA has a primary orientation toward stakeholders interested in comprehensive evaluation of overall environmental performance and trade-offs among impact categories. These differences create tension between footprints, the existing LCIA framework based on the area of protection paradigm and the core LCA standards ISO14040/44.Res

Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

NASA Astrophysics Data System (ADS)

Blasch, Erik

2015-06-01

Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

Bimanual Motor Coordination in Older Adults Is Associated with Increased Functional Brain Connectivity – A Graph-Theoretical Analysis

PubMed Central

Heitger, Marcus H.; Goble, Daniel J.; Dhollander, Thijs; Dupont, Patrick; Caeyenberghs, Karen; Leemans, Alexander; Sunaert, Stefan; Swinnen, Stephan P.

2013-01-01

In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA) to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had “small world” character. The present findings indicate (a) that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b) that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions. PMID:23637982

Categorical encoding of color in the brain.

PubMed

Bird, Chris M; Berens, Samuel C; Horner, Aidan J; Franklin, Anna

2014-03-25

The areas of the brain that encode color categorically have not yet been reliably identified. Here, we used functional MRI adaptation to identify neuronal populations that represent color categories irrespective of metric differences in color. Two colors were successively presented within a block of trials. The two colors were either from the same or different categories (e.g., "blue 1 and blue 2" or "blue 1 and green 1"), and the size of the hue difference was varied. Participants performed a target detection task unrelated to the difference in color. In the middle frontal gyrus of both hemispheres and to a lesser extent, the cerebellum, blood-oxygen level-dependent response was greater for colors from different categories relative to colors from the same category. Importantly, activation in these regions was not modulated by the size of the hue difference, suggesting that neurons in these regions represent color categorically, regardless of metric color difference. Representational similarity analyses, which investigated the similarity of the pattern of activity across local groups of voxels, identified other regions of the brain (including the visual cortex), which responded to metric but not categorical color differences. Therefore, categorical and metric hue differences appear to be coded in qualitatively different ways and in different brain regions. These findings have implications for the long-standing debate on the origin and nature of color categories, and also further our understanding of how color is processed by the brain.

Do laparoscopic skills transfer to robotic surgery?

PubMed

Panait, Lucian; Shetty, Shohan; Shewokis, Patricia A; Sanchez, Juan A

2014-03-01

Identifying the set of skills that can transfer from laparoscopic to robotic surgery is an important consideration in designing optimal training curricula. We tested the degree to which laparoscopic skills transfer to a robotic platform. Fourteen medical students and 14 surgery residents with no previous robotic but varying degrees of laparoscopic experience were studied. Three fundamentals of laparoscopic surgery tasks were used on the laparoscopic box trainer and then the da Vinci robot: peg transfer (PT), circle cutting (CC), and intracorporeal suturing (IS). A questionnaire was administered for assessing subjects' comfort level with each task. Standard fundamentals of laparoscopic surgery scoring metric were used and higher scores indicate a superior performance. For the group, PT and CC scores were similar between robotic and laparoscopic modalities (90 versus 90 and 52 versus 47; P > 0.05). However, for the advanced IS task, robotic-IS scores were significantly higher than laparoscopic-IS (80 versus 53; P < 0.001). Subgroup analysis of senior residents revealed a lower robotic-PT score when compared with laparoscopic-PT (92 versus 105; P < 0.05). Scores for CC and IS were similar in this subgroup (64 ± 9 versus 69 ± 15 and 95 ± 3 versus 92 ± 10; P > 0.05). The robot was favored over laparoscopy for all drills (PT, 66.7%; CC, 88.9%; IS, 94.4%). For simple tasks, participants with preexisting skills perform worse with the robot. However, with increasing task difficulty, robotic performance is equal or better than laparoscopy. Laparoscopic skills appear to readily transfer to a robotic platform, and difficult tasks such as IS are actually enhanced, even in subjects naive to the technology. Copyright © 2014 Elsevier Inc. All rights reserved.

Using Multi-Core Systems for Rover Autonomy

NASA Technical Reports Server (NTRS)

Clement, Brad; Estlin, Tara; Bornstein, Benjamin; Springer, Paul; Anderson, Robert C.

2010-01-01

Task Objectives are: (1) Develop and demonstrate key capabilities for rover long-range science operations using multi-core computing, (a) Adapt three rover technologies to execute on SOA multi-core processor (b) Illustrate performance improvements achieved (c) Demonstrate adapted capabilities with rover hardware, (2) Targeting three high-level autonomy technologies (a) Two for onboard data analysis (b) One for onboard command sequencing/planning, (3) Technologies identified as enabling for future missions, (4)Benefits will be measured along several metrics: (a) Execution time / Power requirements (b) Number of data products processed per unit time (c) Solution quality

Eyetracking metrics reveal impaired spatial anticipation in behavioural variant frontotemporal dementia.

PubMed

Primativo, Silvia; Clark, Camilla; Yong, Keir X X; Firth, Nicholas C; Nicholas, Jennifer; Alexander, Daniel; Warren, Jason D; Rohrer, Jonathan D; Crutch, Sebastian J

2017-11-01

Eyetracking technology has had limited application in the dementia field to date, with most studies attempting to discriminate syndrome subgroups on the basis of basic oculomotor functions rather than higher-order cognitive abilities. Eyetracking-based tasks may also offer opportunities to reduce or ameliorate problems associated with standard paper-and-pencil cognitive tests such as the complexity and linguistic demands of verbal test instructions, and the problems of tiredness and attention associated with lengthy tasks that generate few data points at a slow rate. In the present paper we adapted the Brixton spatial anticipation test to a computerized instruction-less version where oculomotor metrics, rather than overt verbal responses, were taken into account as indicators of high level cognitive functions. Twelve bvFTD (in whom spatial anticipation deficits were expected), six SD patients (in whom deficits were predicted to be less frequent) and 38 healthy controls were presented with a 10 × 7 matrix of white circles. During each trial (N = 24) a black dot moved across seven positions on the screen, following 12 different patterns. Participants' eye movements were recorded. Frequentist statistical analysis of standard eye movement metrics were complemented by a Bayesian machine learning (ML) approach in which raw eyetracking time series datasets were examined to explore the ability to discriminate diagnostic group performance not only on the overall performance but also on individual trials. The original pen and paper Brixton test identified a spatial anticipation deficit in 7/12 (58%) of bvFTD and in 2/6 (33%) of SD patients. The eyetracking frequentist approach reported the deficit in 11/12 (92%) of bvFTD and in none (0%) of the SD patients. The machine learning approach had the main advantage of identifying significant differences from controls in 24/24 individual trials for bvFTD patients and in only 12/24 for SD patients. Results indicate that the fine grained rich datasets obtained from eyetracking metrics can inform us about high level cognitive functions in dementia, such as spatial anticipation. The ML approach can help identify conditions where subtle deficits are present and, potentially, contribute to test optimisation and the reduction of testing times. The absence of instructions also favoured a better distinction between different clinical groups of patients and can help provide valuable disease-specific markers. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

SU-F-BRB-07: A Plan Comparison Tool to Ensure Robustness and Deliverability in Online-Adaptive Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, P; Labby, Z; Bayliss, R A

Purpose: To develop a plan comparison tool that will ensure robustness and deliverability through analysis of baseline and online-adaptive radiotherapy plans using similarity metrics. Methods: The ViewRay MRIdian treatment planning system allows export of a plan file that contains plan and delivery information. A software tool was developed to read and compare two plans, providing information and metrics to assess their similarity. In addition to performing direct comparisons (e.g. demographics, ROI volumes, number of segments, total beam-on time), the tool computes and presents histograms of derived metrics (e.g. step-and-shoot segment field sizes, segment average leaf gaps). Such metrics were investigatedmore » for their ability to predict that an online-adapted plan reasonably similar to a baseline plan where deliverability has already been established. Results: In the realm of online-adaptive planning, comparing ROI volumes offers a sanity check to verify observations found during contouring. Beyond ROI analysis, it has been found that simply editing contours and re-optimizing to adapt treatment can produce a delivery that is substantially different than the baseline plan (e.g. number of segments increased by 31%), with no changes in optimization parameters and only minor changes in anatomy. Currently the tool can quickly identify large omissions or deviations from baseline expectations. As our online-adaptive patient population increases, we will continue to develop and refine quantitative acceptance criteria for adapted plans and relate them historical delivery QA measurements. Conclusion: The plan comparison tool is in clinical use and reports a wide range of comparison metrics, illustrating key differences between two plans. This independent check is accomplished in seconds and can be performed in parallel to other tasks in the online-adaptive workflow. Current use prevents large planning or delivery errors from occurring, and ongoing refinements will lead to increased assurance of plan quality.« less

Serial binary interval ratios improve rhythm reproduction.

PubMed

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception.

Serial binary interval ratios improve rhythm reproduction

PubMed Central

Wu, Xiang; Westanmo, Anders; Zhou, Liang; Pan, Junhao

2013-01-01

Musical rhythm perception is a natural human ability that involves complex cognitive processes. Rhythm refers to the organization of events in time, and musical rhythms have an underlying hierarchical metrical structure. The metrical structure induces the feeling of a beat and the extent to which a rhythm induces the feeling of a beat is referred to as its metrical strength. Binary ratios are the most frequent interval ratio in musical rhythms. Rhythms with hierarchical binary ratios are better discriminated and reproduced than rhythms with hierarchical non-binary ratios. However, it remains unclear whether a superiority of serial binary over non-binary ratios in rhythm perception and reproduction exists. In addition, how different types of serial ratios influence the metrical strength of rhythms remains to be elucidated. The present study investigated serial binary vs. non-binary ratios in a reproduction task. Rhythms formed with exclusively binary (1:2:4:8), non-binary integer (1:3:5:6), and non-integer (1:2.3:5.3:6.4) ratios were examined within a constant meter. The results showed that the 1:2:4:8 rhythm type was more accurately reproduced than the 1:3:5:6 and 1:2.3:5.3:6.4 rhythm types, and the 1:2.3:5.3:6.4 rhythm type was more accurately reproduced than the 1:3:5:6 rhythm type. Further analyses showed that reproduction performance was better predicted by the distribution pattern of event occurrences within an inter-beat interval, than by the coincidence of events with beats, or the magnitude and complexity of interval ratios. Whereas rhythm theories and empirical data emphasize the role of the coincidence of events with beats in determining metrical strength and predicting rhythm performance, the present results suggest that rhythm processing may be better understood when the distribution pattern of event occurrences is taken into account. These results provide new insights into the mechanisms underlining musical rhythm perception. PMID:23964258

Performance of a normalized energy metric without jammer state information for an FH/MFSK system in worst case partial band jamming

NASA Technical Reports Server (NTRS)

Lee, P. J.

1985-01-01

For a frequency-hopped noncoherent MFSK communication system without jammer state information (JSI) in a worst case partial band jamming environment, it is well known that the use of a conventional unquantized metric results in very poor performance. In this paper, a 'normalized' unquantized energy metric is suggested for such a system. It is shown that with this metric, one can save 2-3 dB in required signal energy over the system with hard decision metric without JSI for the same desired performance. When this very robust metric is compared to the conventional unquantized energy metric with JSI, the loss in required signal energy is shown to be small. Thus, the use of this normalized metric provides performance comparable to systems for which JSI is known. Cutoff rate and bit error rate with dual-k coding are used for the performance measures.

Methods for Assessment of Memory Reactivation.

PubMed

Liu, Shizhao; Grosmark, Andres D; Chen, Zhe

2018-04-13

It has been suggested that reactivation of previously acquired experiences or stored information in declarative memories in the hippocampus and neocortex contributes to memory consolidation and learning. Understanding memory consolidation depends crucially on the development of robust statistical methods for assessing memory reactivation. To date, several statistical methods have seen established for assessing memory reactivation based on bursts of ensemble neural spike activity during offline states. Using population-decoding methods, we propose a new statistical metric, the weighted distance correlation, to assess hippocampal memory reactivation (i.e., spatial memory replay) during quiet wakefulness and slow-wave sleep. The new metric can be combined with an unsupervised population decoding analysis, which is invariant to latent state labeling and allows us to detect statistical dependency beyond linearity in memory traces. We validate the new metric using two rat hippocampal recordings in spatial navigation tasks. Our proposed analysis framework may have a broader impact on assessing memory reactivations in other brain regions under different behavioral tasks.

A New Distance Metric for Unsupervised Learning of Categorical Data.

PubMed

Jia, Hong; Cheung, Yiu-Ming; Liu, Jiming

2016-05-01

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.

Field Test: Results of Tandem Walk Performance Following Long-Duration Spaceflight

NASA Technical Reports Server (NTRS)

Rosenberg, M. J. F.; Reschke, M. F.; Cerisano, J. M.; Kofman, I. S.; Fisher, E. A.; Gadd, N. E.; May-Phillips, T. R.; Lee, S. M. C.; Laurie, S. S.; Stenger, M. B.;

A Quantitative Relationship between Signal Detection in Attention and Approach/Avoidance Behavior

PubMed Central

Viswanathan, Vijay; Sheppard, John P.; Kim, Byoung W.; Plantz, Christopher L.; Ying, Hao; Lee, Myung J.; Raman, Kalyan; Mulhern, Frank J.; Block, Martin P.; Calder, Bobby; Lee, Sang; Mortensen, Dale T.; Blood, Anne J.; Breiter, Hans C.

2017-01-01

This study examines how the domains of reward and attention, which are often studied as independent processes, in fact interact at a systems level. We operationalize divided attention with a continuous performance task and variables from signal detection theory (SDT), and reward/aversion with a keypress task measuring approach/avoidance in the framework of relative preference theory (RPT). Independent experiments with the same subjects showed a significant association between one SDT and two RPT variables, visualized as a three-dimensional structure. Holding one of these three variables constant, further showed a significant relationship between a loss aversion-like metric from the approach/avoidance task, and the response bias observed during the divided attention task. These results indicate that a more liberal response bias under signal detection (i.e., a higher tolerance for noise, resulting in a greater proportion of false alarms) is associated with higher “loss aversion.” Furthermore, our functional model suggests a mechanism for processing constraints with divided attention and reward/aversion. Together, our results argue for a systematic relationship between divided attention and reward/aversion processing in humans. PMID:28270776

A Quantitative Relationship between Signal Detection in Attention and Approach/Avoidance Behavior.

PubMed

Viswanathan, Vijay; Sheppard, John P; Kim, Byoung W; Plantz, Christopher L; Ying, Hao; Lee, Myung J; Raman, Kalyan; Mulhern, Frank J; Block, Martin P; Calder, Bobby; Lee, Sang; Mortensen, Dale T; Blood, Anne J; Breiter, Hans C

2017-01-01

This study examines how the domains of reward and attention, which are often studied as independent processes, in fact interact at a systems level. We operationalize divided attention with a continuous performance task and variables from signal detection theory (SDT), and reward/aversion with a keypress task measuring approach/avoidance in the framework of relative preference theory (RPT). Independent experiments with the same subjects showed a significant association between one SDT and two RPT variables, visualized as a three-dimensional structure. Holding one of these three variables constant, further showed a significant relationship between a loss aversion-like metric from the approach/avoidance task, and the response bias observed during the divided attention task. These results indicate that a more liberal response bias under signal detection (i.e., a higher tolerance for noise, resulting in a greater proportion of false alarms) is associated with higher "loss aversion." Furthermore, our functional model suggests a mechanism for processing constraints with divided attention and reward/aversion. Together, our results argue for a systematic relationship between divided attention and reward/aversion processing in humans.

Metrics for Performance Evaluation of Patient Exercises during Physical Therapy.

PubMed

Vakanski, Aleksandar; Ferguson, Jake M; Lee, Stephen

2017-06-01

The article proposes a set of metrics for evaluation of patient performance in physical therapy exercises. Taxonomy is employed that classifies the metrics into quantitative and qualitative categories, based on the level of abstraction of the captured motion sequences. Further, the quantitative metrics are classified into model-less and model-based metrics, in reference to whether the evaluation employs the raw measurements of patient performed motions, or whether the evaluation is based on a mathematical model of the motions. The reviewed metrics include root-mean square distance, Kullback Leibler divergence, log-likelihood, heuristic consistency, Fugl-Meyer Assessment, and similar. The metrics are evaluated for a set of five human motions captured with a Kinect sensor. The metrics can potentially be integrated into a system that employs machine learning for modelling and assessment of the consistency of patient performance in home-based therapy setting. Automated performance evaluation can overcome the inherent subjectivity in human performed therapy assessment, and it can increase the adherence to prescribed therapy plans, and reduce healthcare costs.

Symmetry-based detection and diagnosis of DCIS in breast MRI

NASA Astrophysics Data System (ADS)

Srikantha, Abhilash; Harz, Markus T.; Newstead, Gillian; Wang, Lei; Platel, Bram; Hegenscheid, Katrin; Mann, Ritse M.; Hahn, Horst K.; Peitgen, Heinz-Otto

2013-02-01

The delineation and diagnosis of non-mass-like lesions, most notably DCIS (ductal carcinoma in situ), is among the most challenging tasks in breast MRI reading. Even for human observers, DCIS is not always easy to diferentiate from patterns of active parenchymal enhancement or from benign alterations of breast tissue. In this light, it is no surprise that CADe/CADx approaches often completely fail to classify DCIS. Of the several approaches that have tried to devise such computer aid, none achieve performances similar to mass detection and classification in terms of sensitivity and specificity. In our contribution, we show a novel approach to combine a newly proposed metric of anatomical breast symmetry calculated on subtraction images of dynamic contrast-enhanced (DCE) breast MRI, descriptive kinetic parameters, and lesion candidate morphology to achieve performances comparable to computer-aided methods used for masses. We have based the development of the method on DCE MRI data of 18 DCIS cases with hand-annotated lesions, complemented by DCE-MRI data of nine normal cases. We propose a novel metric to quantify the symmetry of contralateral breasts and derive a strong indicator for potentially malignant changes from this metric. Also, we propose a novel metric for the orientation of a finding towards a fix point (the nipple). Our combined scheme then achieves a sensitivity of 89% with a specificity of 78%, matching CAD results for breast MRI on masses. The processing pipeline is intended to run on a CAD server, hence we designed all processing to be automated and free of per-case parameters. We expect that the detection results of our proposed non-mass aimed algorithm will complement other CAD algorithms, or ideally be joined with them in a voting scheme.

Association Between Brain Activation and Functional Connectivity.

PubMed

Tomasi, Dardo; Volkow, Nora D

2018-04-13

The origin of the "resting-state" brain activity recorded with functional magnetic resonance imaging (fMRI) is still uncertain. Here we provide evidence for the neurovascular origins of the amplitude of the low-frequency fluctuations (ALFF) and the local functional connectivity density (lFCD) by comparing them with task-induced blood-oxygen level dependent (BOLD) responses, which are considered a proxy for neuronal activation. Using fMRI data for 2 different tasks (Relational and Social) collected by the Human Connectome Project in 426 healthy adults, we show that ALFF and lFCD have linear associations with the BOLD response. This association was significantly attenuated by a novel task signal regression (TSR) procedure, indicating that task performance enhances lFCD and ALFF in activated regions. We also show that lFCD predicts BOLD activation patterns, as was recently shown for other functional connectivity metrics, which corroborates that resting functional connectivity architecture impacts brain activation responses. Thus, our findings indicate a common source for BOLD responses, ALFF and lFCD, which is consistent with the neurovascular origin of local hemodynamic synchrony presumably reflecting coordinated fluctuations in neuronal activity. This study also supports the development of task-evoked functional connectivity density mapping.

Impaired spatial processing in a mouse model of fragile X syndrome.

PubMed

Ghilan, Mohamed; Bettio, Luis E B; Noonan, Athena; Brocardo, Patricia S; Gil-Mohapel, Joana; Christie, Brian R

2018-05-17

Fragile X syndrome (FXS) is the most common form of inherited intellectual impairment. The Fmr1 -/y mouse model has been previously shown to have deficits in context discrimination tasks but not in the elevated plus-maze. To further characterize this FXS mouse model and determine whether hippocampal-mediated behaviours are affected in these mice, dentate gyrus (DG)-dependent spatial processing and Cornu ammonis 1 (CA1)-dependent temporal order discrimination tasks were evaluated. In agreement with previous findings of long-term potentiation deficits in the DG of this transgenic model of FXS, the results reported here demonstrate that Fmr1 -/y mice perform poorly in the DG-dependent metric change spatial processing task. However, Fmr1 -/y mice did not present deficits in the CA1-dependent temporal order discrimination task, and were able to remember the order in which objects were presented to them to the same extent as their wild-type littermate controls. These data suggest that the previously reported subregional-specific differences in hippocampal synaptic plasticity observed in the Fmr1 -/y mouse model may manifest as selective behavioural deficits in hippocampal-dependent tasks. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

The Nature and Nurture of Melody: A Twin Study of Musical Pitch and Rhythm Perception.

PubMed

Seesjärvi, Erik; Särkämö, Teppo; Vuoksimaa, Eero; Tervaniemi, Mari; Peretz, Isabelle; Kaprio, Jaakko

2016-07-01

Both genetic and environmental factors are known to play a role in our ability to perceive music, but the degree to which they influence different aspects of music cognition is still unclear. We investigated the relative contribution of genetic and environmental effects on melody perception in 384 young adult twins [69 full monozygotic (MZ) twin pairs, 44 full dizygotic (DZ) twin pairs, 70 MZ twins without a co-twin, and 88 DZ twins without a co-twin]. The participants performed three online music tests requiring the detection of pitch changes in a two-melody comparison task (Scale) and key and rhythm incongruities in single-melody perception tasks (Out-of-key, Off-beat). The results showed predominantly additive genetic effects in the Scale task (58 %, 95 % CI 42-70 %), shared environmental effects in the Out-of-key task (61 %, 49-70 %), and non-shared environmental effects in the Off-beat task (82 %, 61-100 %). This highly different pattern of effects suggests that the contribution of genetic and environmental factors on music perception depends on the degree to which it calls for acquired knowledge of musical tonal and metric structures.

Sensorimotor Synchronization with Different Metrical Levels of Point-Light Dance Movements

PubMed Central

Su, Yi-Huang

2016-01-01

Rhythm perception and synchronization have been extensively investigated in the auditory domain, as they underlie means of human communication such as music and speech. Although recent studies suggest comparable mechanisms for synchronizing with periodically moving visual objects, the extent to which it applies to ecologically relevant information, such as the rhythm of complex biological motion, remains unknown. The present study addressed this issue by linking rhythm of music and dance in the framework of action-perception coupling. As a previous study showed that observers perceived multiple metrical periodicities in dance movements that embodied this structure, the present study examined whether sensorimotor synchronization (SMS) to dance movements resembles what is known of auditory SMS. Participants watched a point-light figure performing two basic steps of Swing dance cyclically, in which the trunk bounced at every beat and the limbs moved at every second beat, forming two metrical periodicities. Participants tapped synchronously to the bounce of the trunk with or without the limbs moving in the stimuli (Experiment 1), or tapped synchronously to the leg movements with or without the trunk bouncing simultaneously (Experiment 2). Results showed that, while synchronization with the bounce (lower-level pulse) was not influenced by the presence or absence of limb movements (metrical accent), synchronization with the legs (beat) was improved by the presence of the bounce (metrical subdivision) across different movement types. The latter finding parallels the “subdivision benefit” often demonstrated in auditory tasks, suggesting common sensorimotor mechanisms for visual rhythms in dance and auditory rhythms in music. PMID:27199709

Toward an optimisation technique for dynamically monitored environment

NASA Astrophysics Data System (ADS)

Shurrab, Orabi M.

2016-10-01

The data fusion community has introduced multiple procedures of situational assessments; this is to facilitate timely responses to emerging situations. More directly, the process refinement of the Joint Directors of Laboratories (JDL) is a meta-process to assess and improve the data fusion task during real-time operation. In other wording, it is an optimisation technique to verify the overall data fusion performance, and enhance it toward the top goals of the decision-making resources. This paper discusses the theoretical concept of prioritisation. Where the analysts team is required to keep an up to date with the dynamically changing environment, concerning different domains such as air, sea, land, space and cyberspace. Furthermore, it demonstrates an illustration example of how various tracking activities are ranked, simultaneously into a predetermined order. Specifically, it presents a modelling scheme for a case study based scenario, where the real-time system is reporting different classes of prioritised events. Followed by a performance metrics for evaluating the prioritisation process of situational awareness (SWA) domain. The proposed performance metrics has been designed and evaluated using an analytical approach. The modelling scheme represents the situational awareness system outputs mathematically, in the form of a list of activities. Such methods allowed the evaluation process to conduct a rigorous analysis of the prioritisation process, despite any constrained related to a domain-specific configuration. After conducted three levels of assessments over three separates scenario, The Prioritisation Capability Score (PCS) has provided an appropriate scoring scheme for different ranking instances, Indeed, from the data fusion perspectives, the proposed metric has assessed real-time system performance adequately, and it is capable of conducting a verification process, to direct the operator's attention to any issue, concerning the prioritisation capability of situational awareness domain.

How task demands influence scanpath similarity in a sequential number-search task.

PubMed

Dewhurst, Richard; Foulsham, Tom; Jarodzka, Halszka; Johansson, Roger; Holmqvist, Kenneth; Nyström, Marcus

2018-06-07

More and more researchers are considering the omnibus eye movement sequence-the scanpath-in their studies of visual and cognitive processing (e.g. Hayes, Petrov, & Sederberg, 2011; Madsen, Larson, Loschky, & Rebello, 2012; Ni et al., 2011; von der Malsburg & Vasishth, 2011). However, it remains unclear how recent methods for comparing scanpaths perform in experiments producing variable scanpaths, and whether these methods supplement more traditional analyses of individual oculomotor statistics. We address this problem for MultiMatch (Jarodzka et al., 2010; Dewhurst et al., 2012), evaluating its performance with a visual search-like task in which participants must fixate a series of target numbers in a prescribed order. This task should produce predictable sequences of fixations and thus provide a testing ground for scanpath measures. Task difficulty was manipulated by making the targets more or less visible through changes in font and the presence of distractors or visual noise. These changes in task demands led to slower search and more fixations. Importantly, they also resulted in a reduction in the between-subjects scanpath similarity, demonstrating that participants' gaze patterns became more heterogenous in terms of saccade length and angle, and fixation position. This implies a divergent strategy or random component to eye-movement behaviour which increases as the task becomes more difficult. Interestingly, the duration of fixations along aligned vectors showed the opposite pattern, becoming more similar between observers in 2 of the 3 difficulty manipulations. This provides important information for vision scientists who may wish to use scanpath metrics to quantify variations in gaze across a spectrum of perceptual and cognitive tasks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validation of the da Vinci Surgical Skill Simulator across three surgical disciplines: A pilot study

PubMed Central

Alzahrani, Tarek; Haddad, Richard; Alkhayal, Abdullah; Delisle, Josée; Drudi, Laura; Gotlieb, Walter; Fraser, Shannon; Bergman, Simon; Bladou, Frank; Andonian, Sero; Anidjar, Maurice

2013-01-01

Objective: In this paper, we evaluate face, content and construct validity of the da Vinci Surgical Skills Simulator (dVSSS) across 3 surgical disciplines. Methods: In total, 48 participants from urology, gynecology and general surgery participated in the study as novices (0 robotic cases performed), intermediates (1–74) or experts (≥75). Each participant completed 9 tasks (Peg board level 2, match board level 2, needle targeting, ring and rail level 2, dots and needles level 1, suture sponge level 2, energy dissection level 1, ring walk level 3 and tubes). The Mimic Technologies software scored each task from 0 (worst) to 100 (best) using several predetermined metrics. Face and content validity were evaluated by a questionnaire administered after task completion. Wilcoxon test was used to perform pair wise comparisons. Results: The expert group comprised of 6 attending surgeons. The intermediate group included 4 attending surgeons, 3 fellows and 5 residents. The novices included 1 attending surgeon, 1 fellow, 13 residents, 13 medical students and 2 research assistants. The median number of robotic cases performed by experts and intermediates were 250 and 9, respectively. The median overall realistic score (face validity) was 8/10. Experts rated the usefulness of the simulator as a training tool for residents (content validity) as 8.5/10. For construct validity, experts outperformed novices in all 9 tasks (p < 0.05). Intermediates outperformed novices in 7 of 9 tasks (p < 0.05); there were no significant differences in the energy dissection and ring walk tasks. Finally, experts scored significantly better than intermediates in only 3 of 9 tasks (matchboard, dots and needles and energy dissection) (p < 0.05). Conclusions: This study confirms the face, content and construct validities of the dVSSS across urology, gynecology and general surgery. Larger sample size and more complex tasks are needed to further differentiate intermediates from experts. PMID:23914275

SU-E-I-71: Quality Assessment of Surrogate Metrics in Multi-Atlas-Based Image Segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, T; Ruan, D

Purpose: With the ever-growing data of heterogeneous quality, relevance assessment of atlases becomes increasingly critical for multi-atlas-based image segmentation. However, there is no universally recognized best relevance metric and even a standard to compare amongst candidates remains elusive. This study, for the first time, designs a quantification to assess relevance metrics’ quality, based on a novel perspective of the metric as surrogate for inferring the inaccessible oracle geometric agreement. Methods: We first develop an inference model to relate surrogate metrics in image space to the underlying oracle relevance metric in segmentation label space, with a monotonically non-decreasing function subject tomore » random perturbations. Subsequently, we investigate model parameters to reveal key contributing factors to surrogates’ ability in prognosticating the oracle relevance value, for the specific task of atlas selection. Finally, we design an effective contract-to-noise ratio (eCNR) to quantify surrogates’ quality based on insights from these analyses and empirical observations. Results: The inference model was specialized to a linear function with normally distributed perturbations, with surrogate metric exemplified by several widely-used image similarity metrics, i.e., MSD/NCC/(N)MI. Surrogates’ behaviors in selecting the most relevant atlases were assessed under varying eCNR, showing that surrogates with high eCNR dominated those with low eCNR in retaining the most relevant atlases. In an end-to-end validation, NCC/(N)MI with eCNR of 0.12 compared to MSD with eCNR of 0.10 resulted in statistically better segmentation with mean DSC of about 0.85 and the first and third quartiles of (0.83, 0.89), compared to MSD with mean DSC of 0.84 and the first and third quartiles of (0.81, 0.89). Conclusion: The designed eCNR is capable of characterizing surrogate metrics’ quality in prognosticating the oracle relevance value. It has been demonstrated to be correlated with the performance of relevant atlas selection and ultimate label fusion.« less

Playing to your skills: a randomised controlled trial evaluating a dedicated video game for minimally invasive surgery.

PubMed

Harrington, Cuan M; Chaitanya, Vishwa; Dicker, Patrick; Traynor, Oscar; Kavanagh, Dara O

2018-02-14

Video gaming demands elements of visual attention, hand-eye coordination and depth perception which may be contiguous with laparoscopic skill development. General video gaming has demonstrated altered cortical plasticity and improved baseline/acquisition of minimally invasive skills. The present study aimed to evaluate for skill acquisition associated with a commercially available dedicated laparoscopic video game (Underground) and its unique (laparoscopic-like) controller for the Nintendo®Wii U™ console. This single-blinded randomised controlled study was conducted with laparoscopically naive student volunteers of limited (< 3 h/week) video gaming backgrounds. Baseline laparoscopic skills were assessed using four basic tasks on the Virtual Reality (VR) simulator (LAP Mentor TM , 3D systems, Colorado, USA). Twenty participants were randomised to two groups; Group A was requested to complete 5 h of video gaming (Underground) per week and Group B to avoid gaming beyond their normal frequency. After 4 weeks participants were reassessed using the same VR tasks. Changes in simulator performances were assessed for each group and for intergroup variances using mixed model regression. Significant inter- and intragroup performances were present for the video gaming and controls across four basic tasks. The video gaming group demonstrated significant improvements in thirty-one of the metrics examined including dominant (p ≤ 0.004) and non-dominant (p < 0.050) instrument movements, pathlengths (p ≤ 0.040), time taken (p ≤ 0.021) and end score [p ≤ 0.046, (task-dependent)]. The control group demonstrated improvements in fourteen measures. The video gaming group demonstrated significant (p < 0.05) improvements compared to the control in five metrics. Despite encouraged gameplay and the console in participants' domiciles, voluntary engagement was lower than directed due to factors including: game enjoyment (33.3%), lack of available time (22.2%) and entertainment distractions (11.1%). Our work revealed significant value in training using a dedicated laparoscopic video game for acquisition of virtual laparoscopic skills. This novel serious game may provide foundations for future surgical developments on game consoles in the home environment.

Can teenage novel users perform as well as General Surgery residents upon initial exposure to a robotic surgical system simulator?

PubMed

Mehta, A; Patel, S; Robison, W; Senkowski, T; Allen, J; Shaw, E; Senkowski, C

2018-03-01

New techniques in minimally invasive and robotic surgical platforms require staged curricula to insure proficiency. Scant literature exists as to how much simulation should play a role in training those who have skills in advanced surgical technology. The abilities of novel users may help discriminate if surgically experienced users should start at a higher simulation level or if the tasks are too rudimentary. The study's purpose is to explore the ability of General Surgery residents to gain proficiency on the dVSS as compared to novel users. The hypothesis is that Surgery residents will have increased proficiency in skills acquisition as compared to naive users. Six General Surgery residents at a single institution were compared with six teenagers using metrics measured by the dVSS. Participants were given two 1-h sessions to achieve an MScoreTM in the 90th percentile on each of the five simulations. MScoreTM software compiles a variety of metrics including total time, number of attempts, and high score. Statistical analysis was run using Student's t test. Significance was set at p value <0.05. Total time, attempts, and high score were compared between the two groups. The General Surgery residents took significantly less Total Time to complete Pegboard 1 (PB1) (p = 0.043). No significant difference was evident between the two groups in the other four simulations across the same MScoreTM metrics. A focused look at the energy dissection task revealed that overall score might not be discriminant enough. Our findings indicate that prior medical knowledge or surgical experience does not significantly impact one's ability to acquire new skills on the dVSS. It is recommended that residency-training programs begin to include exposure to robotic technology.

On temporal connectivity of PFC via Gauss-Markov modeling of fNIRS signals.

PubMed

Aydöre, Sergül; Mihçak, M Kivanç; Ciftçi, Koray; Akin, Ata

2010-03-01

Functional near-infrared spectroscopy (fNIRS) is an optical imaging method, which monitors the brain activation by measuring the successive changes in the concentration of oxy- and deoxyhemoglobin in real time. In this study, we present a method to investigate the functional connectivity of prefrontal cortex (PFC) Sby applying a Gauss-Markov model to fNIRS signals. The hemodynamic changes on PFC during the performance of cognitive paradigm are measured by fNIRS for 17 healthy adults. The color-word matching Stroop task is performed to activate 16 different regions of PFC. There are three different types of stimuli in this task, which can be listed as incongruent stimulus (IS), congruent stimulus (CS), and neutral stimulus (NS), respectively. We introduce a new measure, called "information transfer metric" (ITM) for each time sample. The behavior of ITMs during IS are significantly different from the ITMs during CS and NS, which is consistent with the outcome of the previous research, which concentrated on fNIRS signal analysis via color-word matching Stroop task. Our analysis shows that the functional connectivity of PFC is highly relevant with the cognitive load, i.e., functional connectivity increases with the increasing cognitive load.

Load-embedded inertial measurement unit reveals lifting performance.

PubMed

Tammana, Aditya; McKay, Cody; Cain, Stephen M; Davidson, Steven P; Vitali, Rachel V; Ojeda, Lauro; Stirling, Leia; Perkins, Noel C

2018-07-01

Manual lifting of loads arises in many occupations as well as in activities of daily living. Prior studies explore lifting biomechanics and conditions implicated in lifting-induced injuries through laboratory-based experimental methods. This study introduces a new measurement method using load-embedded inertial measurement units (IMUs) to evaluate lifting tasks in varied environments outside of the laboratory. An example vertical load lifting task is considered that is included in an outdoor obstacle course. The IMU data, in the form of the load acceleration and angular velocity, is used to estimate load vertical velocity and three lifting performance metrics: the lifting time (speed), power, and motion smoothness. Large qualitative differences in these parameters distinguish exemplar high and low performance trials. These differences are further supported by subsequent statistical analyses of twenty three trials (including a total of 115 total lift/lower cycles) from fourteen healthy participants. Results reveal that lifting time is strongly correlated with lifting power (as expected) but also correlated with motion smoothness. Thus, participants who lift rapidly do so with significantly greater power using motions that minimize motion jerk. Copyright © 2018 Elsevier Ltd. All rights reserved.

Taking Word Clouds Apart: An Empirical Investigation of the Design Space for Keyword Summaries.

PubMed

Felix, Cristian; Franconeri, Steven; Bertini, Enrico

2018-01-01

In this paper we present a set of four user studies aimed at exploring the visual design space of what we call keyword summaries: lists of words with associated quantitative values used to help people derive an intuition of what information a given document collection (or part of it) may contain. We seek to systematically study how different visual representations may affect people's performance in extracting information out of keyword summaries. To this purpose, we first create a design space of possible visual representations and compare the possible solutions in this design space through a variety of representative tasks and performance metrics. Other researchers have, in the past, studied some aspects of effectiveness with word clouds, however, the existing literature is somewhat scattered and do not seem to address the problem in a sufficiently systematic and holistic manner. The results of our studies showed a strong dependency on the tasks users are performing. In this paper we present details of our methodology, the results, as well as, guidelines on how to design effective keyword summaries based in our discoveries.

Bimanual Psychomotor Performance in Neurosurgical Resident Applicants Assessed Using NeuroTouch, a Virtual Reality Simulator.

PubMed

Winkler-Schwartz, Alexander; Bajunaid, Khalid; Mullah, Muhammad A S; Marwa, Ibrahim; Alotaibi, Fahad E; Fares, Jawad; Baggiani, Marta; Azarnoush, Hamed; Zharni, Gmaan Al; Christie, Sommer; Sabbagh, Abdulrahman J; Werthner, Penny; Del Maestro, Rolando F

Current selection methods for neurosurgical residents fail to include objective measurements of bimanual psychomotor performance. Advancements in computer-based simulation provide opportunities to assess cognitive and psychomotor skills in surgically naive populations during complex simulated neurosurgical tasks in risk-free environments. This pilot study was designed to answer 3 questions: (1) What are the differences in bimanual psychomotor performance among neurosurgical residency applicants using NeuroTouch? (2) Are there exceptionally skilled medical students in the applicant cohort? and (3) Is there an influence of previous surgical exposure on surgical performance? Participants were instructed to remove 3 simulated brain tumors with identical visual appearance, stiffness, and random bleeding points. Validated tier 1, tier 2, and advanced tier 2 metrics were used to assess bimanual psychomotor performance. Demographic data included weeks of neurosurgical elective and prior operative exposure. This pilot study was carried out at the McGill Neurosurgical Simulation Research and Training Center immediately following neurosurgical residency interviews at McGill University, Montreal, Canada. All 17 medical students interviewed were asked to participate, of which 16 agreed. Performances were clustered in definable top, middle, and bottom groups with significant differences for all metrics. Increased time spent playing music, increased applicant self-evaluated technical skills, high self-ratings of confidence, and increased skin closures statistically influenced performance on univariate analysis. A trend for both self-rated increased operating room confidence and increased weeks of neurosurgical exposure to increased blood loss was seen in multivariate analysis. Simulation technology identifies neurosurgical residency applicants with differing levels of technical ability. These results provide information for studies being developed for longitudinal studies on the acquisition, development, and maintenance of psychomotor skills. Technical abilities customized training programs that maximize individual resident bimanual psychomotor training dependant on continuously updated and validated metrics from virtual reality simulation studies should be explored. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Noise properties and task-based evaluation of diffraction-enhanced imaging

PubMed Central

Brankov, Jovan G.; Saiz-Herranz, Alejandro; Wernick, Miles N.

2014-01-01

Abstract. Diffraction-enhanced imaging (DEI) is an emerging x-ray imaging method that simultaneously yields x-ray attenuation and refraction images and holds great promise for soft-tissue imaging. The DEI has been mainly studied using synchrotron sources, but efforts have been made to transition the technology to more practical implementations using conventional x-ray sources. The main technical challenge of this transition lies in the relatively lower x-ray flux obtained from conventional sources, leading to photon-limited data contaminated by Poisson noise. Several issues that must be understood in order to design and optimize DEI imaging systems with respect to noise performance are addressed. Specifically, we: (a) develop equations describing the noise properties of DEI images, (b) derive the conditions under which the DEI algorithm is statistically optimal, (c) characterize the imaging performance that can be obtained as measured by task-based metrics, and (d) consider image-processing steps that may be employed to mitigate noise effects. PMID:26158056

Microgravity effects on fine motor skills: tying surgical knots during parabolic flight.

PubMed

Rafiq, Azhar; Hummel, Russ; Lavrentyev, Vladimir; Derry, William; Williams, David; Merrell, Ronald C

2006-08-01

The health provider on a space exploration mission cannot evacuate a patient to Earth. Contingency plans for medical intervention must be designed for autonomy. This study measured the effect of microgravity on performance of fine motor skills such as basic surgical tasks. Eight subjects, six with medical and two with non-medical backgrounds, were evaluated during parabolic microgravity flights aboard NASA's KC-135. We evaluated their skill in tying surgical knots on simulated skin made of silicone using standard techniques for minimally invasive surgery. LabView software was developed to archive forces applied to the laparoscopic tool handles during knot-tying. Studies were controlled for medication (ScopeDex) and the aircraft environment. All participants completed the tests successfully. The data indicated that increased force was applied to the instruments and knot quality decreased during flight compared with ground control sessions. Specific metrics of surgical task performance are essential in developing education modules for providers of medical care during exploration-class missions.

Second-order relational face processing is applied to faces of different race and photographic contrast.

PubMed

Matheson, H E; Bilsbury, T G; McMullen, P A

2012-03-01

A large body of research suggests that faces are processed by a specialized mechanism within the human visual system. This specialized mechanism is made up of subprocesses (Maurer, LeGrand, & Mondloch, 2002). One subprocess, called second- order relational processing, analyzes the metric distances between face parts. Importantly, it is well established that other-race faces and contrast-reversed faces are associated with impaired performance on numerous face processing tasks. Here, we investigated the specificity of second-order relational processing by testing how this process is applied to faces of different race and photographic contrast. Participants completed a feature displacement discrimination task, directly measuring the sensitivity to second-order relations between face parts. Across three experiments we show that, despite absolute differences in sensitivity in some conditions, inversion impaired performance in all conditions. The presence of robust inversion effects for all faces suggests that second-order relational processing can be applied to faces of different race and photographic contrast.

Digital mammographic tumor classification using transfer learning from deep convolutional neural networks.

PubMed

Huynh, Benjamin Q; Li, Hui; Giger, Maryellen L

2016-07-01

Convolutional neural networks (CNNs) show potential for computer-aided diagnosis (CADx) by learning features directly from the image data instead of using analytically extracted features. However, CNNs are difficult to train from scratch for medical images due to small sample sizes and variations in tumor presentations. Instead, transfer learning can be used to extract tumor information from medical images via CNNs originally pretrained for nonmedical tasks, alleviating the need for large datasets. Our database includes 219 breast lesions (607 full-field digital mammographic images). We compared support vector machine classifiers based on the CNN-extracted image features and our prior computer-extracted tumor features in the task of distinguishing between benign and malignant breast lesions. Five-fold cross validation (by lesion) was conducted with the area under the receiver operating characteristic (ROC) curve as the performance metric. Results show that classifiers based on CNN-extracted features (with transfer learning) perform comparably to those using analytically extracted features [area under the ROC curve [Formula: see text

Body-Machine Interface Enables People With Cervical Spinal Cord Injury to Control Devices With Available Body Movements: Proof of Concept.

PubMed

Abdollahi, Farnaz; Farshchiansadegh, Ali; Pierella, Camilla; Seáñez-González, Ismael; Thorp, Elias; Lee, Mei-Hua; Ranganathan, Rajiv; Pedersen, Jessica; Chen, David; Roth, Elliot; Casadio, Maura; Mussa-Ivaldi, Ferdinando

2017-05-01

This study tested the use of a customized body-machine interface (BoMI) for enhancing functional capabilities in persons with cervical spinal cord injury (cSCI). The interface allows people with cSCI to operate external devices by reorganizing their residual movements. This was a proof-of-concept phase 0 interventional nonrandomized clinical trial. Eight cSCI participants wore a custom-made garment with motion sensors placed on the shoulders. Signals derived from the sensors controlled a computer cursor. A standard algorithm extracted the combinations of sensor signals that best captured each participant's capacity for controlling a computer cursor. Participants practiced with the BoMI for 24 sessions over 12 weeks performing 3 tasks: reaching, typing, and game playing. Learning and performance were evaluated by the evolution of movement time, errors, smoothness, and performance metrics specific to each task. Through practice, participants were able to reduce the movement time and the distance from the target at the 1-second mark in the reaching task. They also made straighter and smoother movements while reaching to different targets. All participants became faster in the typing task and more skilled in game playing, as the pong hit rate increased significantly with practice. The results provide proof-of-concept for the customized BoMI as a means for people with absent or severely impaired hand movements to control assistive devices that otherwise would be manually operated.

Neural control of finger movement via intracortical brain-machine interface

NASA Astrophysics Data System (ADS)

Irwin, Z. T.; Schroeder, K. E.; Vu, P. P.; Bullard, A. J.; Tat, D. M.; Nu, C. S.; Vaskov, A.; Nason, S. R.; Thompson, D. E.; Bentley, J. N.; Patil, P. G.; Chestek, C. A.

2017-12-01

Objective. Intracortical brain-machine interfaces (BMIs) are a promising source of prosthesis control signals for individuals with severe motor disabilities. Previous BMI studies have primarily focused on predicting and controlling whole-arm movements; precise control of hand kinematics, however, has not been fully demonstrated. Here, we investigate the continuous decoding of precise finger movements in rhesus macaques. Approach. In order to elicit precise and repeatable finger movements, we have developed a novel behavioral task paradigm which requires the subject to acquire virtual fingertip position targets. In the physical control condition, four rhesus macaques performed this task by moving all four fingers together in order to acquire a single target. This movement was equivalent to controlling the aperture of a power grasp. During this task performance, we recorded neural spikes from intracortical electrode arrays in primary motor cortex. Main results. Using a standard Kalman filter, we could reconstruct continuous finger movement offline with an average correlation of ρ  =  0.78 between actual and predicted position across four rhesus macaques. For two of the monkeys, this movement prediction was performed in real-time to enable direct brain control of the virtual hand. Compared to physical control, neural control performance was slightly degraded; however, the monkeys were still able to successfully perform the task with an average target acquisition rate of 83.1%. The monkeys’ ability to arbitrarily specify fingertip position was also quantified using an information throughput metric. During brain control task performance, the monkeys achieved an average 1.01 bits s-1 throughput, similar to that achieved in previous studies which decoded upper-arm movements to control computer cursors using a standard Kalman filter. Significance. This is, to our knowledge, the first demonstration of brain control of finger-level fine motor skills. We believe that these results represent an important step towards full and dexterous control of neural prosthetic devices.

Novel Hybrid Scheduling Technique for Sensor Nodes with Mixed Criticality Tasks

PubMed Central

Micea, Mihai-Victor; Stangaciu, Cristina-Sorina; Stangaciu, Valentin; Curiac, Daniel-Ioan

2017-01-01

Sensor networks become increasingly a key technology for complex control applications. Their potential use in safety- and time-critical domains has raised the need for task scheduling mechanisms specially adapted to sensor node specific requirements, often materialized in predictable jitter-less execution of tasks characterized by different criticality levels. This paper offers an efficient scheduling solution, named Hybrid Hard Real-Time Scheduling (H2RTS), which combines a static, clock driven method with a dynamic, event driven scheduling technique, in order to provide high execution predictability, while keeping a high node Central Processing Unit (CPU) utilization factor. From the detailed, integrated schedulability analysis of the H2RTS, a set of sufficiency tests are introduced and demonstrated based on the processor demand and linear upper bound metrics. The performance and correct behavior of the proposed hybrid scheduling technique have been extensively evaluated and validated both on a simulator and on a sensor mote equipped with ARM7 microcontroller. PMID:28672856

Developing operator capacity estimates for supervisory control of autonomous vehicles.

PubMed

Cummings, M L; Guerlain, Stephanie

2007-02-01

This study examined operators' capacity to successfully reallocate highly autonomous in-flight missiles to time-sensitive targets while performing secondary tasks of varying complexity. Regardless of the level of autonomy for unmanned systems, humans will be necessarily involved in the mission planning, higher level operation, and contingency interventions, otherwise known as human supervisory control. As a result, more research is needed that addresses the impact of dynamic decision support systems that support rapid planning and replanning in time-pressured scenarios, particularly on operator workload. A dual screen simulation that allows a single operator the ability to monitor and control 8, 12, or 16 missiles through high level replanning was tested on 42 U.S. Navy personnel. The most significant finding was that when attempting to control 16 missiles, participants' performance on three separate objective performance metrics and their situation awareness were significantly degraded. These results mirror studies of air traffic control that demonstrate a similar decline in performance for controllers managing 17 aircraft as compared with those managing only 10 to 11 aircraft. Moreover, the results suggest that a 70% utilization (percentage busy time) score is a valid threshold for predicting significant performance decay and could be a generalizable metric that can aid in manning predictions. This research is relevant to human supervisory control of networked military and commercial unmanned vehicles in the air, on the ground, and on and under the water.

The CREST Simulation Development Process: Training the Next Generation.

PubMed

Sweet, Robert M

2017-04-01

The challenges of training and assessing endourologic skill have driven the development of new training systems. The Center for Research in Education and Simulation Technologies (CREST) has developed a team and a methodology to facilitate this development process. Backwards design principles were applied. A panel of experts first defined desired clinical and educational outcomes. Outcomes were subsequently linked to learning objectives. Gross task deconstruction was performed, and the primary domain was classified as primarily involving decision-making, psychomotor skill, or communication. A more detailed cognitive task analysis was performed to elicit and prioritize relevant anatomy/tissues, metrics, and errors. Reference anatomy was created using a digital anatomist and clinician working off of a clinical data set. Three dimensional printing can facilitate this process. When possible, synthetic or virtual tissue behavior and textures were recreated using data derived from human tissue. Embedded sensors/markers and/or computer-based systems were used to facilitate the collection of objective metrics. A learning Verification and validation occurred throughout the engineering development process. Nine endourology-relevant training systems were created by CREST with this approach. Systems include basic laparoscopic skills (BLUS), vesicourethral anastomosis, pyeloplasty, cystoscopic procedures, stent placement, rigid and flexible ureteroscopy, GreenLight PVP (GL Sim), Percutaneous access with C-arm (CAT), Nephrolithotomy (NLM), and a vascular injury model. Mixed modalities have been used, including "smart" physical models, virtual reality, augmented reality, and video. Substantial validity evidence for training and assessment has been collected on systems. An open source manikin-based modular platform is under development by CREST with the Department of Defense that will unify these and other commercial task trainers through the common physiology engine, learning management system, standard data connectors, and standards. Using the CREST process has and will ensure that the systems we create meet the needs of training and assessing endourologic skills.

Effect of Auditory Constraints on Motor Performance Depends on Stage of Recovery Post-Stroke

PubMed Central

Aluru, Viswanath; Lu, Ying; Leung, Alan; Verghese, Joe; Raghavan, Preeti

2014-01-01

In order to develop evidence-based rehabilitation protocols post-stroke, one must first reconcile the vast heterogeneity in the post-stroke population and develop protocols to facilitate motor learning in the various subgroups. The main purpose of this study is to show that auditory constraints interact with the stage of recovery post-stroke to influence motor learning. We characterized the stages of upper limb recovery using task-based kinematic measures in 20 subjects with chronic hemiparesis. We used a bimanual wrist extension task, performed with a custom-made wrist trainer, to facilitate learning of wrist extension in the paretic hand under four auditory conditions: (1) without auditory cueing; (2) to non-musical happy sounds; (3) to self-selected music; and (4) to a metronome beat set at a comfortable tempo. Two bimanual trials (15 s each) were followed by one unimanual trial with the paretic hand over six cycles under each condition. Clinical metrics, wrist and arm kinematics, and electromyographic activity were recorded. Hierarchical cluster analysis with the Mahalanobis metric based on baseline speed and extent of wrist movement stratified subjects into three distinct groups, which reflected their stage of recovery: spastic paresis, spastic co-contraction, and minimal paresis. In spastic paresis, the metronome beat increased wrist extension, but also increased muscle co-activation across the wrist. In contrast, in spastic co-contraction, no auditory stimulation increased wrist extension and reduced co-activation. In minimal paresis, wrist extension did not improve under any condition. The results suggest that auditory task constraints interact with stage of recovery during motor learning after stroke, perhaps due to recruitment of distinct neural substrates over the course of recovery. The findings advance our understanding of the mechanisms of progression of motor recovery and lay the foundation for personalized treatment algorithms post-stroke. PMID:25002859

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

Intrasubject multimodal groupwise registration with the conditional template entropy.

PubMed

Polfliet, Mathias; Klein, Stefan; Huizinga, Wyke; Paulides, Margarethus M; Niessen, Wiro J; Vandemeulebroucke, Jef

2018-05-01

Image registration is an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. Multimodal registration in a groupwise setting remains difficult, due to the lack of generally applicable similarity metrics. In this work, a novel similarity metric for such groupwise registration problems is proposed. The metric calculates the sum of the conditional entropy between each image in the group and a representative template image constructed iteratively using principal component analysis. The proposed metric is validated in extensive experiments on synthetic and intrasubject clinical image data. These experiments showed equivalent or improved registration accuracy compared to other state-of-the-art (dis)similarity metrics and improved transformation consistency compared to pairwise mutual information. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions

PubMed Central

Giaro, Krzysztof

2017-01-01

Abstract Ability to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in the literature, the most commonly used seems to be the Robinson–Foulds distance. In this article, we define a new metric for rooted trees—the Matching Pair (MP) distance. The MP metric uses the concept of the minimum-weight perfect matching in a complete bipartite graph constructed from partitions of all pairs of leaves of the compared phylogenetic trees. We analyze the properties of the MP metric and present computational experiments showing its potential applicability in tasks related to finding the HGT events. PMID:28177699

Comparing Phylogenetic Trees by Matching Nodes Using the Transfer Distance Between Partitions.

PubMed

Bogdanowicz, Damian; Giaro, Krzysztof

2017-05-01

Ability to quantify dissimilarity of different phylogenetic trees describing the relationship between the same group of taxa is required in various types of phylogenetic studies. For example, such metrics are used to assess the quality of phylogeny construction methods, to define optimization criteria in supertree building algorithms, or to find horizontal gene transfer (HGT) events. Among the set of metrics described so far in the literature, the most commonly used seems to be the Robinson-Foulds distance. In this article, we define a new metric for rooted trees-the Matching Pair (MP) distance. The MP metric uses the concept of the minimum-weight perfect matching in a complete bipartite graph constructed from partitions of all pairs of leaves of the compared phylogenetic trees. We analyze the properties of the MP metric and present computational experiments showing its potential applicability in tasks related to finding the HGT events.

Systems Engineering Approach and Metrics for Evaluating Network-Centric Operations for U.S. Army Battle Command

DTIC Science & Technology

2013-07-01

Systems Engineering Approach and Metrics for Evaluating Network-Centric Operations for U.S. Army Battle Command by Jock O. Grynovicki and...Battle Command Jock O. Grynovicki and Teresa A. Branscome Human Research and Engineering Directorate, ARL...NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Jock O. Grynovicki and Teresa A. Branscome 5d. PROJECT NUMBER 622716H70 5e. TASK NUMBER

Distributed Trajectory Flexibility Preservation for Traffic Complexity Mitigation

NASA Technical Reports Server (NTRS)

Idris, Husni; Wing, David; Delahaye, Daniel

2009-01-01

The growing demand for air travel is increasing the need for mitigation of air traffic congestion and complexity problems, which are already at high levels. At the same time new information and automation technologies are enabling the distribution of tasks and decisions from the service providers to the users of the air traffic system, with potential capacity and cost benefits. This distribution of tasks and decisions raises the concern that independent user actions will decrease the predictability and increase the complexity of the traffic system, hence inhibiting and possibly reversing any potential benefits. In answer to this concern, the authors propose the introduction of decision-making metrics for preserving user trajectory flexibility. The hypothesis is that such metrics will make user actions naturally mitigate traffic complexity. In this paper, the impact of using these metrics on traffic complexity is investigated. The scenarios analyzed include aircraft in en route airspace with each aircraft meeting a required time of arrival in a one-hour time horizon while mitigating the risk of loss of separation with the other aircraft, thus preserving its trajectory flexibility. The experiments showed promising results in that the individual trajectory flexibility preservation induced self-separation and self-organization effects in the overall traffic situation. The effects were quantified using traffic complexity metrics based on Lyapunov exponents and traffic proximity.

Memory binding and white matter integrity in familial Alzheimer’s disease

PubMed Central

Saarimäki, Heini; Bastin, Mark E.; Londoño, Ana C.; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon

2015-01-01

Binding information in short-term and long-term memory are functions sensitive to Alzheimer’s disease. They have been found to be affected in patients who meet criteria for familial Alzheimer’s disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer’s disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer’s disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer’s disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer’s disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer’s disease. PMID:25762465

Functional network mediates age-related differences in reaction time: a replication and extension study

PubMed Central

Gazes, Yunglin; Habeck, Christian; O'Shea, Deirdre; Razlighi, Qolamreza R; Steffener, Jason; Stern, Yaakov

2015-01-01

Introduction A functional activation (i.e., ordinal trend) pattern was previously identified in both young and older adults during task-switching performance, the expression of which correlated with reaction time. The current study aimed to (1) replicate this functional activation pattern in a new group of fMRI activation data, and (2) extend the previous study by specifically examining whether the effect of aging on reaction time can be explained by differences in the activation of the functional activation pattern. Method A total of 47 young and 50 older participants were included in the extension analysis. Participants performed task-switching as the activation task and were cued by the color of the stimulus for the task to be performed in each block. To test for replication, two approaches were implemented. The first approach tested the replicability of the predictive power of the previously identified functional activation pattern by forward applying the pattern to the Study II data and the second approach was rederivation of the activation pattern in the Study II data. Results Both approaches showed successful replication in the new data set. Using mediation analysis, expression of the pattern from the first approach was found to partially mediate age-related effects on reaction time such that older age was associated with greater activation of the brain pattern and longer reaction time, suggesting that brain activation efficiency (defined as “the rate of activation increase with increasing task difficulty” in Neuropsychologia 47, 2009, 2015) of the regions in the Ordinal trend pattern directly accounts for age-related differences in task performance. Discussion The successful replication of the functional activation pattern demonstrates the versatility of the Ordinal Trend Canonical Variates Analysis, and the ability to summarize each participant's brain activation map into one number provides a useful metric in multimodal analysis as well as cross-study comparisons. PMID:25874162

Memory binding and white matter integrity in familial Alzheimer's disease.

PubMed

Parra, Mario A; Saarimäki, Heini; Bastin, Mark E; Londoño, Ana C; Pettit, Lewis; Lopera, Francisco; Della Sala, Sergio; Abrahams, Sharon

2015-05-01

Binding information in short-term and long-term memory are functions sensitive to Alzheimer's disease. They have been found to be affected in patients who meet criteria for familial Alzheimer's disease due to the mutation E280A of the PSEN1 gene. However, only short-term memory binding has been found to be affected in asymptomatic carriers of this mutation. The neural correlates of this dissociation are poorly understood. The present study used diffusion tensor magnetic resonance imaging to investigate whether the integrity of white matter structures could offer an account. A sample of 19 patients with familial Alzheimer's disease, 18 asymptomatic carriers and 21 non-carrier controls underwent diffusion tensor magnetic resonance imaging, neuropsychological and memory binding assessment. The short-term memory binding task required participants to detect changes across two consecutive screens displaying arrays of shapes, colours, or shape-colour bindings. The long-term memory binding task was a Paired Associates Learning Test. Performance on these tasks were entered into regression models. Relative to controls, patients with familial Alzheimer's disease performed poorly on both memory binding tasks. Asymptomatic carriers differed from controls only in the short-term memory binding task. White matter integrity explained poor memory binding performance only in patients with familial Alzheimer's disease. White matter water diffusion metrics from the frontal lobe accounted for poor performance on both memory binding tasks. Dissociations were found in the genu of corpus callosum which accounted for short-term memory binding impairments and in the hippocampal part of cingulum bundle which accounted for long-term memory binding deficits. The results indicate that white matter structures in the frontal and temporal lobes are vulnerable to the early stages of familial Alzheimer's disease and their damage is associated with impairments in two memory binding functions known to be markers for Alzheimer's disease. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Improving Pediatric Rapid Response Team Performance Through Crew Resource Management Training of Team Leaders.

PubMed

Siems, Ashley; Cartron, Alexander; Watson, Anne; McCarter, Robert; Levin, Amanda

2017-02-01

Rapid response teams (RRTs) improve the detection of and response to deteriorating patients. Professional hierarchies and the multidisciplinary nature of RRTs hinder team performance. This study assessed whether an intervention involving crew resource management training of team leaders could improve team performance. In situ observations of RRT activations were performed pre- and post-training intervention. Team performance and dynamics were measured by observed adherence to an ideal task list and by the Team Emergency Assessment Measure tool, respectively. Multiple quartile (median) and logistic regression models were developed to evaluate change in performance scores or completion of specific tasks. Team leader and team introductions (40% to 90%, P = .004; 7% to 45%, P = .03), floor team presentations in Situation Background Assessment Recommendation format (20% to 65%, P = .01), and confirmation of the plan (7% to 70%, P = .002) improved after training in patients transferred to the ICU (n = 35). The Team Emergency Assessment Measure metric was improved in all 4 categories: leadership (2.5 to 3.5, P < .001), teamwork (2.7 to 3.7, P < .001), task management (2.9 to 3.8, P < .001), and global scores (6.0 to 9.0, P < .001) for teams caring for patients who required transfer to the ICU. Targeted crew resource management training of the team leader resulted in improved team performance and dynamics for patients requiring transfer to the ICU. The intervention demonstrated that training the team leader improved behavior in RRT members who were not trained. Copyright © 2017 by the American Academy of Pediatrics.

Comparison between Decision Tree and Genetic Programming to distinguish healthy from stroke postural sway patterns.

PubMed

Marrega, Luiz H G; Silva, Simone M; Manffra, Elisangela F; Nievola, Julio C

2015-01-01

Maintaining balance is a motor task of crucial importance for humans to perform their daily activities safely and independently. Studies in the field of Artificial Intelligence have considered different classification methods in order to distinguish healthy subjects from patients with certain motor disorders based on their postural strategies during the balance control. The main purpose of this paper is to compare the performance between Decision Tree (DT) and Genetic Programming (GP) - both classification methods of easy interpretation by health professionals - to distinguish postural sway patterns produced by healthy and stroke individuals based on 16 widely used posturographic variables. For this purpose, we used a posturographic dataset of time-series of center-of-pressure displacements derived from 19 stroke patients and 19 healthy matched subjects in three quiet standing tasks of balance control. Then, DT and GP models were trained and tested under two different experiments where accuracy, sensitivity and specificity were adopted as performance metrics. The DT method has performed statistically significant (P < 0.05) better in both cases, showing for example an accuracy of 72.8% against 69.2% from GP in the second experiment of this paper.

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan.

PubMed

Davison, Elizabeth N; Turner, Benjamin O; Schlesinger, Kimberly J; Miller, Michael B; Grafton, Scott T; Bassett, Danielle S; Carlson, Jean M

2016-11-01

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

PubMed

Dasari, Deepika; Shou, Guofa; Ding, Lei

2017-01-01

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

An Investigation of the Use of Real-time Image Mosaicing for Facilitating Global Spatial Awareness in Visual Search

NASA Astrophysics Data System (ADS)

Soung Yee, Anthony

Three experiments have been completed to investigate whether and how a software technique called real-time image mosaicing applied to a restricted field of view (FOV) might influence target detection and path integration performance in simulated aerial search scenarios, representing local and global spatial awareness tasks respectively. The mosaiced FOV (mFOV) was compared to single FOV (sFOV) and one with double the single size (dFOV). In addition to advancing our understanding of visual information in mosaicing, the present study examines the advantages and limitations of a number of metrics used to evaluate performance in path integration tasks, with particular attention paid to measuring performance in identifying complex routes. The highlights of the results are summarized as follows, according to Experiments 1 through 3 respectively. 1. A novel response method for evaluating route identification performance was developed. The surmised benefits of the mFOV relative to sFOV and dFOV revealed no significant differences in performance for the relatively simple route shapes tested. Compared to the mFOV and dFOV conditions, target detection performance in the local task was found to be superior in the sFOV condition. 2. In order to appropriately quantify the observed differences in complex route selections made by the participants, a novel analysis method was developed using the Thurstonian Paired Comparisons Method. 3. To investigate the effect of display size and elevation angle (EA) in a complex route environment, a 2x3 experiment was conducted for the two spatial tasks, at a height selected from Experiment 2. Although no significant differences were found in the target detection task, contrasts in the Paired Comparisons Method results revealed that route identification performance were as hypothesised: mFOV > dFOV > sFOV for EA = 90°. Results were similar for EA = 45°, but with mFOV being no different than dFOV. As hypothesised, EA was found to have an effect on route selection performance, with a top down view performing better than an angled view for the mFOV and sFOV conditions.

An evaluation of touchscreen versus keyboard/mouse interaction for large screen process control displays.

PubMed

Noah, Benjamin; Li, Jingwen; Rothrock, Ling

2017-10-01

The objectives of this study were to test the effect of interaction device on performance in a process control task (managing a tank farm). The study compared the following two conditions: a) 4K-resolution 55" screen with a 21" touchscreen versus b) 4K-resolution 55″ screen with keyboard/mouse. The touchscreen acted both as an interaction device for data entry and navigation and as an additional source of information. A within-subject experiment was conducted among 20 college engineering students. A primary task of preventing tanks from overfilling as well as a secondary task of manual logging with situation awareness questions were designed for the study. Primary Task performance (including tank level at discharge, number of tank discharged and performance score), Secondary Task Performance (including Tank log count, performance score), system interaction times, subjective workload, situation awareness questionnaire, user experience survey regarding usability and condition comparison were used as the measures. Parametric data resulted in two metrics statistically different means between the two conditions: The 4K-keyboard condition resulted in faster Detection + Navigation time compared to the 4K-touchscreen condition, by about 2 s, while participants within the 4K-touchscreen condition were about 2 s faster in data entry than in the 4K-keyboard condition. No significant results were found for: performance on the secondary task, situation awareness, and workload. Additionally, no clear significant differences were found in the non-parametric data analysis. However, participants showed a slight preference for the 4K-touchscreen condition compared to the 4K-keyboard condition in subjective responses in comparing the conditions. Introducing the touchscreen as an additional/alternative input device showed to have an effect in interaction times, which suggests that proper design considerations need to be made. While having values shown on the interaction device provides value, a potential issue of visual distraction exists when having an additional visual display. The allocation of visual attention between primary displays and the touchscreen should be further investigated. Copyright © 2017 Elsevier Ltd. All rights reserved.

Real-time performance monitoring and management system

DOEpatents

Budhraja, Vikram S [Los Angeles, CA; Dyer, James D [La Mirada, CA; Martinez Morales, Carlos A [Upland, CA

2007-06-19

A real-time performance monitoring system for monitoring an electric power grid. The electric power grid has a plurality of grid portions, each grid portion corresponding to one of a plurality of control areas. The real-time performance monitoring system includes a monitor computer for monitoring at least one of reliability metrics, generation metrics, transmission metrics, suppliers metrics, grid infrastructure security metrics, and markets metrics for the electric power grid. The data for metrics being monitored by the monitor computer are stored in a data base, and a visualization of the metrics is displayed on at least one display computer having a monitor. The at least one display computer in one said control area enables an operator to monitor the grid portion corresponding to a different said control area.

Development and Applications of a Self-Contained, Non-Invasive EVA Joint Angle and Muscle Fatigue Sensor System

NASA Technical Reports Server (NTRS)

Ranniger, C. U.; Sorenson, E. A.; Akin, D. L.

1995-01-01

The University of Maryland Space Systems Laboratory, as a participant in NASA's INSTEP program, is developing a non-invasive, self-contained sensor system which can provide quantitative measurements of joint angles and muscle fatigue in the hand and forearm. The goal of this project is to develop a system with which hand/forearm motion and fatigue metrics can be determined in various terrestrial and zero-G work environments. A preliminary study of the prototype sensor systems and data reduction techniques for the fatigue measurement system are presented. The sensor systems evaluated include fiberoptics, used to measure joint angle, surface electrodes, which measure the electrical signals created in muscle as it contracts; microphones, which measure the noise made by contracting muscle; and accelerometers, which measure the lateral muscle acceleration during contraction. The prototype sensor systems were used to monitor joint motion of the metacarpophalangeal joint and muscle fatigue in flexor digitorum superficialis and flexor carpi ulnaris in subjects performing gripping tasks. Subjects were asked to sustain a 60-second constant-contraction (isometric) exercise and subsequently to perform a repetitive handgripping task to failure. Comparison of the electrical and mechanical signals of the muscles during the different tasks will be used to evaluate the applicability of muscle signal measurement techniques developed for isometric contraction tasks to fatigue prediction in quasi-dynamic exercises. Potential data reduction schemes are presented.

Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, J.; Hodge, B. M.; Florita, A.

2013-10-01

Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The resultsmore » show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.« less

Metrics in method engineering

NASA Astrophysics Data System (ADS)

Brinkkemper, S.; Rossi, M.

1994-12-01

As customizable computer aided software engineering (CASE) tools, or CASE shells, have been introduced in academia and industry, there has been a growing interest into the systematic construction of methods and their support environments, i.e. method engineering. To aid the method developers and method selectors in their tasks, we propose two sets of metrics, which measure the complexity of diagrammatic specification techniques on the one hand, and of complete systems development methods on the other hand. Proposed metrics provide a relatively fast and simple way to analyze the technique (or method) properties, and when accompanied with other selection criteria, can be used for estimating the cost of learning the technique and the relative complexity of a technique compared to others. To demonstrate the applicability of the proposed metrics, we have applied them to 34 techniques and 15 methods.

Accessible laparoscopic instrument tracking ("InsTrac"): construct validity in a take-home box simulator.

PubMed

Partridge, Roland W; Hughes, Mark A; Brennan, Paul M; Hennessey, Iain A M

2014-08-01

Objective performance feedback has potential to maximize the training benefit of laparoscopic simulators. Instrument movement metrics are, however, currently the preserve of complex and expensive systems. We aimed to develop and validate affordable, user-ready software that provides objective feedback by tracking instrument movement in a "take-home" laparoscopic simulator. Computer-vision processing tracks the movement of colored bands placed around the distal instrument shafts. The position of each instrument is logged from the simulator camera feed and movement metrics calculated in real time. Ten novices (junior doctors) and 13 general surgery trainees (StR) (training years 3-7) performed a standardized task (threading string through hoops) on the eoSim (eoSurgical™ Ltd., Edinburgh, Scotland, United Kingdom) take-home laparoscopic simulator. Statistical analysis was performed using unpaired t tests with Welch's correction. The software was able to track the instrument tips reliably and effectively. Significant differences between the two groups were observed in time to complete task (StR versus novice, 2 minutes 33 seconds versus 9 minutes 53 seconds; P=.01), total distance traveled by instruments (3.29 m versus 11.38 m, respectively; P=.01), average instrument motion smoothness (0.15 mm/second(3) versus 0.06 mm/second(3), respectively; P<.01), and handedness (mean difference between dominant and nondominant hand) (0.55 m versus 2.43 m, respectively; P=.03). There was no significant difference seen in the distance between instrument tips, acceleration, speed of instruments, or time off-screen. We have developed software that brings objective performance feedback to the portable laparoscopic box simulator. Construct validity has been demonstrated. Removing the need for additional motion-tracking hardware makes it affordable and accessible. It is user-ready and has the potential to enhance the training benefit of portable simulators both in the workplace and at home.

Metric-driven harm: an exploration of unintended consequences of performance measurement.

PubMed

Rambur, Betty; Vallett, Carol; Cohen, Judith A; Tarule, Jill Mattuck

2013-11-01

Performance measurement is an increasingly common element of the US health care system. Typically a proxy for high quality outcomes, there has been little systematic investigation of the potential negative unintended consequences of performance metrics, including metric-driven harm. This case study details an incidence of post-surgical metric-driven harm and offers Smith's 1995 work and a patient centered, context sensitive metric model for potential adoption by nurse researchers and clinicians. Implications for further research are discussed. © 2013.

Performance assessment in brain-computer interface-based augmentative and alternative communication

PubMed Central

2013-01-01

A large number of incommensurable metrics are currently used to report the performance of brain-computer interfaces (BCI) used for augmentative and alterative communication (AAC). The lack of standard metrics precludes the comparison of different BCI-based AAC systems, hindering rapid growth and development of this technology. This paper presents a review of the metrics that have been used to report performance of BCIs used for AAC from January 2005 to January 2012. We distinguish between Level 1 metrics used to report performance at the output of the BCI Control Module, which translates brain signals into logical control output, and Level 2 metrics at the Selection Enhancement Module, which translates logical control to semantic control. We recommend that: (1) the commensurate metrics Mutual Information or Information Transfer Rate (ITR) be used to report Level 1 BCI performance, as these metrics represent information throughput, which is of interest in BCIs for AAC; 2) the BCI-Utility metric be used to report Level 2 BCI performance, as it is capable of handling all current methods of improving BCI performance; (3) these metrics should be supplemented by information specific to each unique BCI configuration; and (4) studies involving Selection Enhancement Modules should report performance at both Level 1 and Level 2 in the BCI system. Following these recommendations will enable efficient comparison between both BCI Control and Selection Enhancement Modules, accelerating research and development of BCI-based AAC systems. PMID:23680020

No-Reference Video Quality Assessment Based on Statistical Analysis in 3D-DCT Domain.

PubMed

Li, Xuelong; Guo, Qun; Lu, Xiaoqiang

2016-05-13

It is an important task to design models for universal no-reference video quality assessment (NR-VQA) in multiple video processing and computer vision applications. However, most existing NR-VQA metrics are designed for specific distortion types which are not often aware in practical applications. A further deficiency is that the spatial and temporal information of videos is hardly considered simultaneously. In this paper, we propose a new NR-VQA metric based on the spatiotemporal natural video statistics (NVS) in 3D discrete cosine transform (3D-DCT) domain. In the proposed method, a set of features are firstly extracted based on the statistical analysis of 3D-DCT coefficients to characterize the spatiotemporal statistics of videos in different views. These features are used to predict the perceived video quality via the efficient linear support vector regression (SVR) model afterwards. The contributions of this paper are: 1) we explore the spatiotemporal statistics of videos in 3DDCT domain which has the inherent spatiotemporal encoding advantage over other widely used 2D transformations; 2) we extract a small set of simple but effective statistical features for video visual quality prediction; 3) the proposed method is universal for multiple types of distortions and robust to different databases. The proposed method is tested on four widely used video databases. Extensive experimental results demonstrate that the proposed method is competitive with the state-of-art NR-VQA metrics and the top-performing FR-VQA and RR-VQA metrics.

Categorical encoding of color in the brain

PubMed Central

Bird, Chris M.; Berens, Samuel C.; Horner, Aidan J.; Franklin, Anna

2014-01-01

The areas of the brain that encode color categorically have not yet been reliably identified. Here, we used functional MRI adaptation to identify neuronal populations that represent color categories irrespective of metric differences in color. Two colors were successively presented within a block of trials. The two colors were either from the same or different categories (e.g., “blue 1 and blue 2” or “blue 1 and green 1”), and the size of the hue difference was varied. Participants performed a target detection task unrelated to the difference in color. In the middle frontal gyrus of both hemispheres and to a lesser extent, the cerebellum, blood-oxygen level-dependent response was greater for colors from different categories relative to colors from the same category. Importantly, activation in these regions was not modulated by the size of the hue difference, suggesting that neurons in these regions represent color categorically, regardless of metric color difference. Representational similarity analyses, which investigated the similarity of the pattern of activity across local groups of voxels, identified other regions of the brain (including the visual cortex), which responded to metric but not categorical color differences. Therefore, categorical and metric hue differences appear to be coded in qualitatively different ways and in different brain regions. These findings have implications for the long-standing debate on the origin and nature of color categories, and also further our understanding of how color is processed by the brain. PMID:24591602

Automated Neuropsychological Assessment Metrics (ANAM) Traumatic Brain Injury (TBI): Human Factors Assessment

DTIC Science & Technology

2011-07-01

Lindsay, Cory Overby, Angela Jeter, Petra E. Alfred, Gary L. Boykin, Carita DeVilbiss, and Raymond Bateman ARL-TN-0440 July 2011...Neuropsychological Assessment Metrics (ANAM) Traumatic Brain Injury (TBI): Human Factors Assessment Valerie J. Rice, Petra E. Alfred, Gary L. Boykin...Angela Jeter*, Petra E. Alfred, Gary L. Boykin, Carita DeVilbiss, and Raymond Bateman 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT

Neurotechnology to accelerate learning: during marksmanship training.

PubMed

Behneman, Adrienne; Berka, Chris; Stevens, Ronald; Vila, Bryan; Tan, Veasna; Galloway, Trysha; Johnson, Robin; Raphael, Giby

2012-01-01

This article explores the psychophysiological metrics during expert and novice performances in marksmanship, combat deadly force judgment and decision making (DFJDM), and interactions of teams. Electroencephalography (EEG) and electrocardiography (ECG) are used to characterize the psychophysiological profiles within all categories. Closed-loop biofeedback was administered to accelerate learning during marksmanship training in which the results show a difference in groups that received feedback compared with the control. During known distance marksmanship and DFJDM scenarios, experts show superior ability to control physiology to meet the demands of the task. Expertise in teaming scenarios is characterized by higher levels of cohesiveness than those seen in novices.

Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

NASA Technical Reports Server (NTRS)

Young, Larry A.

2007-01-01

A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a theoretical perspective.

A simulator for surgery training: optimal sensory stimuli in a bone pinning simulation

NASA Astrophysics Data System (ADS)

Daenzer, Stefan; Fritzsche, Klaus

2008-03-01

Currently available low cost haptic devices allow inexpensive surgical training with no risk to patients. Major drawbacks of lower cost devices include limited maximum feedback force and the incapability to expose occurring moments. Aim of this work was the design and implementation of a surgical simulator that allows the evaluation of multi-sensory stimuli in order to overcome the occurring drawbacks. The simulator was built following a modular architecture to allow flexible combinations and thorough evaluation of different multi-sensory feedback modules. A Kirschner-Wire (K-Wire) tibial fracture fixation procedure was defined and implemented as a first test scenario. A set of computational metrics has been derived from the clinical requirements of the task to objectively assess the trainees performance during simulation. Sensory feedback modules for haptic and visual feedback have been developed, each in a basic and additionally in an enhanced form. First tests have shown that specific visual concepts can overcome some of the drawbacks coming along with low cost haptic devices. The simulator, the metrics and the surgery scenario together represent an important step towards a better understanding of the perception of multi-sensory feedback in complex surgical training tasks. Field studies on top of the architecture can open the way to risk-less and inexpensive surgical simulations that can keep up with traditional surgical training.

Best Practices Handbook: Traffic Engineering in Range Networks

DTIC Science & Technology

2016-03-01

units of measurement. Measurement Methodology - A repeatable measurement technique used to derive one or more metrics of interest . Network...Performance measures - Metrics that provide quantitative or qualitative measures of the performance of systems or subsystems of interest . Performance Metric

Simulation for the training of human performance and technical skills: the intersection of how we will train health care professionals in the future.

PubMed

Hamman, William R; Beaubien, Jeffrey M; Beaudin-Seiler, Beth M

2009-12-01

The aims of this research are to begin to understand health care teams in their operational environment, establish metrics of performance for these teams, and validate a series of scenarios in simulation that elicit team and technical skills. The focus is on defining the team model that will function in the operational environment in which health care professionals work. Simulations were performed across the United States in 70- to 1000-bed hospitals. Multidisciplinary health care teams analyzed more than 300 hours of videos of health care professionals performing simulations of team-based medical care in several different disciplines. Raters were trained to enhance inter-rater reliability. The study validated event sets that trigger team dynamics and established metrics for team-based care. Team skills were identified and modified using simulation scenarios that employed the event-set-design process. Specific skills (technical and team) were identified by criticality measurement and task analysis methodology. In situ simulation, which includes a purposeful and Socratic Method of debriefing, is a powerful intervention that can overcome inertia found in clinician behavior and latent environmental systems that present a challenge to quality and patient safety. In situ simulation can increase awareness of risks, personalize the risks, and encourage the reflection, effort, and attention needed to make changes to both behaviors and to systems.

Play to become a surgeon: impact of Nintendo Wii training on laparoscopic skills.

PubMed

Giannotti, Domenico; Patrizi, Gregorio; Di Rocco, Giorgio; Vestri, Anna Rita; Semproni, Camilla Proietti; Fiengo, Leslie; Pontone, Stefano; Palazzini, Giorgio; Redler, Adriano

2013-01-01

Video-games have become an integral part of the new multimedia culture. Several studies assessed video-gaming enhancement of spatial attention and eye-hand coordination. Considering the technical difficulty of laparoscopic procedures, legal issues and time limitations, the validation of appropriate training even outside of the operating rooms is ongoing. We investigated the influence of a four-week structured Nintendo® Wii™ training on laparoscopic skills by analyzing performance metrics with a validated simulator (Lap Mentor™, Simbionix™). We performed a prospective randomized study on 42 post-graduate I-II year residents in General, Vascular and Endoscopic Surgery. All participants were tested on a validated laparoscopic simulator and then randomized to group 1 (Controls, no training with the Nintendo® Wii™), and group 2 (training with the Nintendo® Wii™) with 21 subjects in each group, according to a computer-generated list. After four weeks, all residents underwent a testing session on the laparoscopic simulator of the same tasks as in the first session. All 42 subjects in both groups improved significantly from session 1 to session 2. Compared to controls, the Wii group showed a significant improvement in performance (p<0.05) for 13 of the 16 considered performance metrics. The Nintendo® Wii™ might be helpful, inexpensive and entertaining part of the training of young laparoscopists, in addition to a standard surgical education based on simulators and the operating room.

Metaheuristic optimisation methods for approximate solving of singular boundary value problems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Yadav, Neha; Gao, Kaizhou; Su, Rong

2017-07-01

This paper presents a novel approximation technique based on metaheuristics and weighted residual function (WRF) for tackling singular boundary value problems (BVPs) arising in engineering and science. With the aid of certain fundamental concepts of mathematics, Fourier series expansion, and metaheuristic optimisation algorithms, singular BVPs can be approximated as an optimisation problem with boundary conditions as constraints. The target is to minimise the WRF (i.e. error function) constructed in approximation of BVPs. The scheme involves generational distance metric for quality evaluation of the approximate solutions against exact solutions (i.e. error evaluator metric). Four test problems including two linear and two non-linear singular BVPs are considered in this paper to check the efficiency and accuracy of the proposed algorithm. The optimisation task is performed using three different optimisers including the particle swarm optimisation, the water cycle algorithm, and the harmony search algorithm. Optimisation results obtained show that the suggested technique can be successfully applied for approximate solving of singular BVPs.

Worldwide Protein Data Bank validation information: usage and trends.

PubMed

Smart, Oliver S; Horský, Vladimír; Gore, Swanand; Svobodová Vařeková, Radka; Bendová, Veronika; Kleywegt, Gerard J; Velankar, Sameer

2018-03-01

Realising the importance of assessing the quality of the biomolecular structures deposited in the Protein Data Bank (PDB), the Worldwide Protein Data Bank (wwPDB) partners established Validation Task Forces to obtain advice on the methods and standards to be used to validate structures determined by X-ray crystallography, nuclear magnetic resonance spectroscopy and three-dimensional electron cryo-microscopy. The resulting wwPDB validation pipeline is an integral part of the wwPDB OneDep deposition, biocuration and validation system. The wwPDB Validation Service webserver (https://validate.wwpdb.org) can be used to perform checks prior to deposition. Here, it is shown how validation metrics can be combined to produce an overall score that allows the ranking of macromolecular structures and domains in search results. The ValTrends DB database provides users with a convenient way to access and analyse validation information and other properties of X-ray crystal structures in the PDB, including investigating trends in and correlations between different structure properties and validation metrics.

Worldwide Protein Data Bank validation information: usage and trends

PubMed Central

Horský, Vladimír; Gore, Swanand; Svobodová Vařeková, Radka; Bendová, Veronika

2018-01-01

Realising the importance of assessing the quality of the biomolecular structures deposited in the Protein Data Bank (PDB), the Worldwide Protein Data Bank (wwPDB) partners established Validation Task Forces to obtain advice on the methods and standards to be used to validate structures determined by X-ray crystallography, nuclear magnetic resonance spectroscopy and three-dimensional electron cryo-microscopy. The resulting wwPDB validation pipeline is an integral part of the wwPDB OneDep deposition, biocuration and validation system. The wwPDB Validation Service webserver (https://validate.wwpdb.org) can be used to perform checks prior to deposition. Here, it is shown how validation metrics can be combined to produce an overall score that allows the ranking of macromolecular structures and domains in search results. The ValTrendsDB database provides users with a convenient way to access and analyse validation information and other properties of X-ray crystal structures in the PDB, including investigating trends in and correlations between different structure properties and validation metrics. PMID:29533231

Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT.

PubMed

Mazaheri, Samaneh; Sulaiman, Puteri Suhaiza; Wirza, Rahmita; Dimon, Mohd Zamrin; Khalid, Fatimah; Moosavi Tayebi, Rohollah

2015-01-01

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.

An exploratory analysis linking neuropsychological testing to quantification of tractography using High Definition Fiber Tracking (HDFT) in military TBI.

PubMed

Presson, Nora; Beers, Sue R; Morrow, Lisa; Wagener, Lauren M; Bird, William A; Van Eman, Gina; Krishnaswamy, Deepa; Penderville, Joshua; Borrasso, Allison J; Benso, Steven; Puccio, Ava; Fissell, Catherine; Okonkwo, David O; Schneider, Walter

2015-09-01

To realize the potential value of tractography in traumatic brain injury (TBI), we must identify metrics that provide meaningful information about functional outcomes. The current study explores quantitative metrics describing the spatial properties of tractography from advanced diffusion imaging (High Definition Fiber Tracking, HDFT). In a small number of right-handed males from military TBI (N = 7) and civilian control (N = 6) samples, both tract homologue symmetry and tract spread (proportion of brain mask voxels contacted) differed for several tracts among civilian controls and extreme groups in the TBI sample (high scorers and low scorers) for verbal recall, serial reaction time, processing speed index, and trail-making. Notably, proportion of voxels contacted in the arcuate fasciculus distinguished high and low performers on the CVLT-II and PSI, potentially reflecting linguistic task demands, and GFA in the left corticospinal tract distinguished high and low performers in PSI and Trail Making Test Part A, potentially reflecting right hand motor response demands. The results suggest that, for advanced diffusion imaging, spatial properties of tractography may add analytic value to measures of tract anisotropy.

"Take-home" box trainers are an effective alternative to virtual reality simulators.

PubMed

Yiasemidou, Marina; de Siqueira, Jonathan; Tomlinson, James; Glassman, Daniel; Stock, Simon; Gough, Michael

2017-06-01

Practice on virtual reality simulators (VRSs) has been shown to improve surgical performance. However, VRSs are expensive and usually housed in surgical skills centers that may be inaccessible at times convenient for surgical trainees to practice. Conversely, box trainers (BT) are inexpensive and can be used anywhere at anytime. This study assesses "take-home" BTs as an alternative to VRS. After baseline assessments (two simulated laparoscopic cholecystectomies, one on a VRS and one on a BT), 25 surgical trainees were randomized to two groups. Trainees were asked to practice three basic laparoscopic tasks for 6 wk (BT group using a "take-home" box trainer; VR group using VRS in clinical skills centers). After the practice period, all performed two laparoscopic cholecystectomy, one on a VRS and one on a BT; (i.e., posttraining assessment). VRS provided metrics (total time [TT], number of movements instrument tip path length), and expert video assessment of cholecystectomy in a BT (Global Operative Assessment of Laparoscopic Skills [GOALS] score) were recorded. Performance during pretraining and posttraining assessment was compared. The BT group showed a significant improvement for all VRS metrics (P = 0.008) and the efficiency category of GOALS score (P = 0.03). Only TT improved in the VRS group, and none of the GOALS categories demonstrated a statistically significant improvement after training. Finally, the improvement in VRS metrics in the BT group was significantly greater than in the VR group (TT P = 0.005, number of movements P = 0.042, path length P = 0.031), although there were no differences in the GOALS scores between the groups. This study suggests that a basic "take-home" BT is a suitable alternative to VRS. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparative performance evaluation of a new a-Si EPID that exceeds quad high-definition resolution.

PubMed

McConnell, Kristen A; Alexandrian, Ara; Papanikolaou, Niko; Stathakis, Sotiri

2018-01-01

Electronic portal imaging devices (EPIDs) are an integral part of the radiation oncology workflow for treatment setup verification. Several commercial EPID implementations are currently available, each with varying capabilities. To standardize performance evaluation, Task Group Report 58 (TG-58) and TG-142 outline specific image quality metrics to be measured. A LinaTech Image Viewing System (IVS), with the highest commercially available pixel matrix (2688x2688 pixels), was independently evaluated and compared to an Elekta iViewGT (1024x1024 pixels) and a Varian aSi-1000 (1024x768 pixels) using a PTW EPID QC Phantom. The IVS, iViewGT, and aSi-1000 were each used to acquire 20 images of the PTW QC Phantom. The QC phantom was placed on the couch and aligned at isocenter. The images were exported and analyzed using the epidSoft image quality assurance (QA) software. The reported metrics were signal linearity, isotropy of signal linearity, signal-tonoise ratio (SNR), low contrast resolution, and high-contrast resolution. These values were compared between the three EPID solutions. Computed metrics demonstrated comparable results between the EPID solutions with the IVS outperforming the aSi-1000 and iViewGT in the low and high-contrast resolution analysis. The performance of three commercial EPID solutions have been quantified, evaluated, and compared using results from the PTW QC Phantom. The IVS outperformed the other panels in low and high-contrast resolution, but to fully realize the benefits of the IVS, the selection of the monitor on which to view the high-resolution images is important to prevent down sampling and visual of resolution.

Face and Construct Validity of a Novel Virtual Reality-Based Bimanual Laparoscopic Force-Skills Trainer With Haptics Feedback.

PubMed

Prasad, Raghu; Muniyandi, Manivannan; Manoharan, Govindan; Chandramohan, Servarayan M

2018-05-01

The purpose of this study was to examine the face and construct validity of a custom-developed bimanual laparoscopic force-skills trainer with haptics feedback. The study also examined the effect of handedness on fundamental and complex tasks. Residents (n = 25) and surgeons (n = 25) performed virtual reality-based bimanual fundamental and complex tasks. Tool-tissue reaction forces were summed, recorded, and analysed. Seven different force-based measures and a 1-time measure were used as metrics. Subsequently, participants filled out face validity and demographic questionnaires. Residents and surgeons were positive on the design, workspace, and usefulness of the simulator. Construct validity results showed significant differences between residents and experts during the execution of fundamental and complex tasks. In both tasks, residents applied large forces with higher coefficient of variation and force jerks (P < .001). Experts, with their dominant hand, applied lower forces in complex tasks and higher forces in fundamental tasks (P < .001). The coefficients of force variation (CoV) of residents and experts were higher in complex tasks (P < .001). Strong correlations were observed between CoV and task time for fundamental (r = 0.70) and complex tasks (r = 0.85). Range of smoothness of force was higher for the non-dominant hand in both fundamental and complex tasks. The simulator was able to differentiate the force-skills of residents and surgeons, and objectively evaluate the effects of handedness on laparoscopic force-skills. Competency-based laparoscopic skills assessment curriculum should be updated to meet the requirements of bimanual force-based training.

Development of a virtual reality training curriculum for phacoemulsification surgery.

PubMed

Spiteri, A V; Aggarwal, R; Kersey, T L; Sira, M; Benjamin, L; Darzi, A W; Bloom, P A

2014-01-01

Training within a proficiency-based virtual reality (VR) curriculum may reduce errors during real surgical procedures. This study used a scientific methodology to develop a VR training curriculum for phacoemulsification surgery (PS). Ten novice-(n) (performed <10 cataract operations), 10 intermediate-(i) (50-200), and 10 experienced-(e) (>500) surgeons were recruited. Construct validity was defined as the ability to differentiate between the three levels of experience, based on the simulator-derived metrics for two abstract modules (four tasks) and three procedural modules (five tasks) on a high-fidelity VR simulator. Proficiency measures were based on the performance of experienced surgeons. Abstract modules demonstrated a 'ceiling effect' with construct validity established between groups (n) and (i) but not between groups (i) and (e)-Forceps 1 (46, 87, and 95; P<0.001). Increasing difficulty of task showed significantly reduced performance in (n) but minimal difference for (i) and (e)-Anti-tremor 4 (0, 51, and 59; P<0.001), Forceps 4 (11, 73, and 94; P<0.001). Procedural modules were found to be construct valid between groups (n) and (i) and between groups (i) and (e)-Lens-cracking (0, 22, and 51; P<0.05) and Phaco-quadrants (16, 53, and 87; P<0.05). This was also the case with Capsulorhexis (0, 19, and 63; P<0.05) with the performance decreasing in the (n) and (i) group but improving in the (e) group (0, 55, and 73; P<0.05) and (0, 48, and 76; P<0.05) as task difficulty increased. Experienced/intermediate benchmark skill levels are defined allowing the development of a proficiency-based VR training curriculum for PS for novices using a structured scientific methodology.

Dedifferentiation Does Not Account for Hyperconnectivity after Traumatic Brain Injury.

PubMed

Bernier, Rachel Anne; Roy, Arnab; Venkatesan, Umesh Meyyappan; Grossner, Emily C; Brenner, Einat K; Hillary, Frank Gerard

2017-01-01

Changes in functional network connectivity following traumatic brain injury (TBI) have received increasing attention in recent neuroimaging literature. This study sought to understand how disrupted systems adapt to injury during resting and goal-directed brain states. Hyperconnectivity has been a common finding, and dedifferentiation (or loss of segregation of networks) is one possible explanation for this finding. We hypothesized that individuals with TBI would show dedifferentiation of networks (as noted in other clinical populations) and these effects would be associated with cognitive dysfunction. Graph theory was implemented to examine functional connectivity during periods of task and rest in 19 individuals with moderate/severe TBI and 14 healthy controls (HCs). Using a functional brain atlas derived from 83 functional imaging studies, graph theory was used to examine network dynamics and determine whether dedifferentiation accounts for changes in connectivity. Regions of interest were assigned to one of three groups: task-positive, default mode, or other networks. Relationships between these metrics were then compared with performance on neuropsychological tests. Hyperconnectivity in TBI was most commonly observed as increased within-network connectivity. Network strengths within networks that showed differences between TBI and HCs were correlated with performance on five neuropsychological tests typically sensitive to deficits commonly reported in TBI. Hyperconnectivity within the default mode network (DMN) during task was associated with better performance on Digit Span Backward, a measure of working memory [ R 2 (18) = 0.28, p  = 0.02]. In other words, increased differentiation of networks during task was associated with better working memory. Hyperconnectivity within the task-positive network during rest was not associated with behavior. Negative correlation weights were not associated with behavior. The primary hypothesis that hyperconnectivity occurs through increased segregation of networks, rather than dedifferentiation, was not supported. Instead, enhanced connectivity post injury was observed within network. Results suggest that the relationship between increased connectivity and cognitive functioning may be both state (rest or task) and network dependent. High-cost network hubs were identical for both rest and task, and cost was negatively associated with performance on measures of psychomotor speed and set-shifting.

Status Report on Activities of the Systems Assessment Task Force, OECD-NEA Expert Group on Accident Tolerant Fuels for LWRs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bragg-Sitton, Shannon Michelle

The Organization for Economic Cooperation and Development /Nuclear Energy Agency (OECD/NEA) Nuclear Science Committee approved the formation of an Expert Group on Accident Tolerant Fuel (ATF) for LWRs (EGATFL) in 2014. Chaired by Kemal Pasamehmetoglu, INL Associate Laboratory Director for Nuclear Science and Technology, the mandate for the EGATFL defines work under three task forces: (1) Systems Assessment, (2) Cladding and Core Materials, and (3) Fuel Concepts. Scope for the Systems Assessment task force (TF1) includes definition of evaluation metrics for ATF, technology readiness level definition, definition of illustrative scenarios for ATF evaluation, and identification of fuel performance and systemmore » codes applicable to ATF evaluation. The Cladding and Core Materials (TF2) and Fuel Concepts (TF3) task forces will identify gaps and needs for modeling and experimental demonstration; define key properties of interest; identify the data necessary to perform concept evaluation under normal conditions and illustrative scenarios; identify available infrastructure (internationally) to support experimental needs; and make recommendations on priorities. Where possible, considering proprietary and other export restrictions (e.g., International Traffic in Arms Regulations), the Expert Group will facilitate the sharing of data and lessons learned across the international group membership. The Systems Assessment task force is chaired by Shannon Bragg-Sitton (Idaho National Laboratory [INL], U.S.), the Cladding Task Force is chaired by Marie Moatti (Electricite de France [EdF], France), and the Fuels Task Force is chaired by a Masaki Kurata (Japan Atomic Energy Agency [JAEA], Japan). The original Expert Group mandate was established for June 2014 to June 2016. In April 2016 the Expert Group voted to extend the mandate one additional year to June 2017 in order to complete the task force deliverables; this request was subsequently approved by the Nuclear Science Committee. This report provides an update on the status Systems Assessment Task Force activities.« less

A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task.

PubMed

Jangraw, David C; Gonzalez-Castillo, Javier; Handwerker, Daniel A; Ghane, Merage; Rosenberg, Monica D; Panwar, Puja; Bandettini, Peter A

2018-02-01

Sustaining attention to the task at hand is a crucial part of everyday life, from following a lecture at school to maintaining focus while driving. Lapses in sustained attention are frequent and often problematic, with conditions such as attention deficit hyperactivity disorder affecting millions of people worldwide. Recent work has had some success in finding signatures of sustained attention in whole-brain functional connectivity (FC) measures during basic tasks, but since FC can be dynamic and task-dependent, it remains unclear how fully these signatures would generalize to a more complex and naturalistic scenario. To this end, we used a previously defined whole-brain FC network - a marker of attention that was derived from a sustained attention task - to predict the ability of participants to recall material during a free-viewing reading task. Though the predictive network was trained on a different task and set of participants, the strength of FC in the sustained attention network predicted reading recall significantly better than permutation tests where behavior was scrambled to simulate chance performance. To test the generalization of the method used to derive the sustained attention network, we applied the same method to our reading task data to find a new FC network whose strength specifically predicts reading recall. Even though the sustained attention network provided significant prediction of recall, the reading network was more predictive of recall accuracy. The new reading network's spatial distribution indicates that reading recall is highest when temporal pole regions have higher FC with left occipital regions and lower FC with bilateral supramarginal gyrus. Right cerebellar to right frontal connectivity is also indicative of poor reading recall. We examine these and other differences between the two predictive FC networks, providing new insight into the task-dependent nature of FC-based performance metrics. Published by Elsevier Inc.

Computer-based evaluation of Alzheimer's disease and mild cognitive impairment patients during a picture description task.

PubMed

Hernández-Domínguez, Laura; Ratté, Sylvie; Sierra-Martínez, Gerardo; Roche-Bergua, Andrés

2018-01-01

We present a methodology to automatically evaluate the performance of patients during picture description tasks. Transcriptions and audio recordings of the Cookie Theft picture description task were used. With 25 healthy elderly control (HC) samples and an information coverage measure, we automatically generated a population-specific referent. We then assessed 517 transcriptions (257 Alzheimer's disease [AD], 217 HC, and 43 mild cognitively impaired samples) according to their informativeness and pertinence against this referent. We extracted linguistic and phonetic metrics which previous literature correlated to early-stage AD. We trained two learners to distinguish HCs from cognitively impaired individuals. Our measures significantly ( P  < .001) correlated with the severity of the cognitive impairment and the Mini-Mental State Examination score. The classification sensitivity was 81% (area under the curve of receiver operating characteristics = 0.79) and 85% (area under the curve of receiver operating characteristics = 0.76) between HCs and AD and between HCs and AD and mild cognitively impaired, respectively. An automated assessment of a picture description task could assist clinicians in the detection of early signs of cognitive impairment and AD.

Characterizing quantum supremacy in near-term devices

NASA Astrophysics Data System (ADS)

Boixo, Sergio; Isakov, Sergei V.; Smelyanskiy, Vadim N.; Babbush, Ryan; Ding, Nan; Jiang, Zhang; Bremner, Michael J.; Martinis, John M.; Neven, Hartmut

2018-06-01

A critical question for quantum computing in the near future is whether quantum devices without error correction can perform a well-defined computational task beyond the capabilities of supercomputers. Such a demonstration of what is referred to as quantum supremacy requires a reliable evaluation of the resources required to solve tasks with classical approaches. Here, we propose the task of sampling from the output distribution of random quantum circuits as a demonstration of quantum supremacy. We extend previous results in computational complexity to argue that this sampling task must take exponential time in a classical computer. We introduce cross-entropy benchmarking to obtain the experimental fidelity of complex multiqubit dynamics. This can be estimated and extrapolated to give a success metric for a quantum supremacy demonstration. We study the computational cost of relevant classical algorithms and conclude that quantum supremacy can be achieved with circuits in a two-dimensional lattice of 7 × 7 qubits and around 40 clock cycles. This requires an error rate of around 0.5% for two-qubit gates (0.05% for one-qubit gates), and it would demonstrate the basic building blocks for a fault-tolerant quantum computer.

Quality metrics for sensor images

NASA Technical Reports Server (NTRS)

Ahumada, AL

1993-01-01

Methods are needed for evaluating the quality of augmented visual displays (AVID). Computational quality metrics will help summarize, interpolate, and extrapolate the results of human performance tests with displays. The FLM Vision group at NASA Ames has been developing computational models of visual processing and using them to develop computational metrics for similar problems. For example, display modeling systems use metrics for comparing proposed displays, halftoning optimizing methods use metrics to evaluate the difference between the halftone and the original, and image compression methods minimize the predicted visibility of compression artifacts. The visual discrimination models take as input two arbitrary images A and B and compute an estimate of the probability that a human observer will report that A is different from B. If A is an image that one desires to display and B is the actual displayed image, such an estimate can be regarded as an image quality metric reflecting how well B approximates A. There are additional complexities associated with the problem of evaluating the quality of radar and IR enhanced displays for AVID tasks. One important problem is the question of whether intruding obstacles are detectable in such displays. Although the discrimination model can handle detection situations by making B the original image A plus the intrusion, this detection model makes the inappropriate assumption that the observer knows where the intrusion will be. Effects of signal uncertainty need to be added to our models. A pilot needs to make decisions rapidly. The models need to predict not just the probability of a correct decision, but the probability of a correct decision by the time the decision needs to be made. That is, the models need to predict latency as well as accuracy. Luce and Green have generated models for auditory detection latencies. Similar models are needed for visual detection. Most image quality models are designed for static imagery. Watson has been developing a general spatial-temporal vision model to optimize video compression techniques. These models need to be adapted and calibrated for AVID applications.

Task-driven optimization of CT tube current modulation and regularization in model-based iterative reconstruction

NASA Astrophysics Data System (ADS)

Gang, Grace J.; Siewerdsen, Jeffrey H.; Webster Stayman, J.

2017-06-01

Tube current modulation (TCM) is routinely adopted on diagnostic CT scanners for dose reduction. Conventional TCM strategies are generally designed for filtered-backprojection (FBP) reconstruction to satisfy simple image quality requirements based on noise. This work investigates TCM designs for model-based iterative reconstruction (MBIR) to achieve optimal imaging performance as determined by a task-based image quality metric. Additionally, regularization is an important aspect of MBIR that is jointly optimized with TCM, and includes both the regularization strength that controls overall smoothness as well as directional weights that permits control of the isotropy/anisotropy of the local noise and resolution properties. Initial investigations focus on a known imaging task at a single location in the image volume. The framework adopts Fourier and analytical approximations for fast estimation of the local noise power spectrum (NPS) and modulation transfer function (MTF)—each carrying dependencies on TCM and regularization. For the single location optimization, the local detectability index (d‧) of the specific task was directly adopted as the objective function. A covariance matrix adaptation evolution strategy (CMA-ES) algorithm was employed to identify the optimal combination of imaging parameters. Evaluations of both conventional and task-driven approaches were performed in an abdomen phantom for a mid-frequency discrimination task in the kidney. Among the conventional strategies, the TCM pattern optimal for FBP using a minimum variance criterion yielded a worse task-based performance compared to an unmodulated strategy when applied to MBIR. Moreover, task-driven TCM designs for MBIR were found to have the opposite behavior from conventional designs for FBP, with greater fluence assigned to the less attenuating views of the abdomen and less fluence to the more attenuating lateral views. Such TCM patterns exaggerate the intrinsic anisotropy of the MTF and NPS as a result of the data weighting in MBIR. Directional penalty design was found to reinforce the same trend. The task-driven approaches outperform conventional approaches, with the maximum improvement in d‧ of 13% given by the joint optimization of TCM and regularization. This work demonstrates that the TCM optimal for MBIR is distinct from conventional strategies proposed for FBP reconstruction and strategies optimal for FBP are suboptimal and may even reduce performance when applied to MBIR. The task-driven imaging framework offers a promising approach for optimizing acquisition and reconstruction for MBIR that can improve imaging performance and/or dose utilization beyond conventional imaging strategies.

Identifying cognitive distraction using steering wheel reversal rates.

PubMed

Kountouriotis, Georgios K; Spyridakos, Panagiotis; Carsten, Oliver M J; Merat, Natasha

2016-11-01

The influence of driver distraction on driving performance is not yet well understood, but it can have detrimental effects on road safety. In this study, we examined the effects of visual and non-visual distractions during driving, using a high-fidelity driving simulator. The visual task was presented either at an offset angle on an in-vehicle screen, or on the back of a moving lead vehicle. Similar to results from previous studies in this area, non-visual (cognitive) distraction resulted in improved lane keeping performance and increased gaze concentration towards the centre of the road, compared to baseline driving, and further examination of the steering control metrics indicated an increase in steering wheel reversal rates, steering wheel acceleration, and steering entropy. We show, for the first time, that when the visual task is presented centrally, drivers' lane deviation reduces (similar to non-visual distraction), whilst measures of steering control, overall, indicated more steering activity, compared to baseline. When using a visual task that required the diversion of gaze to an in-vehicle display, but without a manual element, lane keeping performance was similar to baseline driving. Steering wheel reversal rates were found to adequately tease apart the effects of non-visual distraction (increase of 0.5° reversals) and visual distraction with offset gaze direction (increase of 2.5° reversals). These findings are discussed in terms of steering control during different types of in-vehicle distraction, and the possible role of manual interference by distracting secondary tasks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adapting to the 30-degree visual perspective by emulating the angled laparoscope: a simple and low-cost solution for basic surgical training.

PubMed

Daniel, Lorias Espinoza; Tapia, Fernando Montes; Arturo, Minor Martínez; Ricardo, Ordorica Flores

2014-12-01

The ability to handle and adapt to the visual perspectives generated by angled laparoscopes is crucial for skilled laparoscopic surgery. However, the control of the visual work space depends on the ability of the operator of the camera, who is often not the most experienced member of the surgical team. Here, we present a simple, low-cost option for surgical training that challenges the learner with static and dynamic visual perspectives at 30 degrees using a system that emulates the angled laparoscope. A system was developed using a low-cost camera and readily available materials to emulate the angled laparoscope. Nine participants undertook 3 tasks to test spatial adaptation to the static and dynamic visual perspectives at 30 degrees. Completing each task to a predefined satisfactory level ensured precision of execution of the tasks. Associated metrics (time and error rate) were recorded, and the performance of participants were determined. A total of 450 repetitions were performed by 9 residents at various stages of training. All the tasks were performed with a visual perspective of 30 degrees using the system. Junior residents were more proficient than senior residents. This system is a viable and low-cost alternative for developing the basic psychomotor skills necessary for the handling and adaptation to visual perspectives of 30 degrees, without depending on a laparoscopic tower, in junior residents. More advanced skills may then be acquired by other means, such as in the operating theater or through clinical experience.

Evaluation of a pilot workload metric for simulated VTOL landing tasks

NASA Technical Reports Server (NTRS)

North, R. A.; Graffunder, K.

1979-01-01

A methodological approach to measuring workload was investigated for evaluation of new concepts in VTOL aircraft displays. Multivariate discriminant functions were formed from conventional flight performance and/or visual response variables to maximize detection of experimental differences. The flight performance variable discriminant showed maximum differentiation between crosswind conditions. The visual response measure discriminant maximized differences between fixed vs. motion base conditions and experimental displays. Physiological variables were used to attempt to predict the discriminant function values for each subject/condition/trial. The weights of the physiological variables in these equations showed agreement with previous studies. High muscle tension, light but irregular breathing patterns, and higher heart rate with low amplitude all produced higher scores on this scale and thus, represented higher workload levels.

DCS: A Case Study of Identification of Knowledge and Disposition Gaps Using Principles of Continuous Risk Management

NASA Technical Reports Server (NTRS)

Norcross, Jason; Steinberg, Susan; Kundrot, Craig; Charles, John

2011-01-01

The Human Research Program (HRP) is formulated around the program architecture of Evidence-Risk-Gap-Task-Deliverable. Review of accumulated evidence forms the basis for identification of high priority risks to human health and performance in space exploration. Gaps in knowledge or disposition are identified for each risk, and a portfolio of research tasks is developed to fill them. Deliverables from the tasks inform the evidence base with the ultimate goal of defining the level of risk and reducing it to an acceptable level. A comprehensive framework for gap identification, focus, and metrics has been developed based on principles of continuous risk management and clinical care. Research towards knowledge gaps improves understanding of the likelihood, consequence or timeframe of the risk. Disposition gaps include development of standards or requirements for risk acceptance, development of countermeasures or technology to mitigate the risk, and yearly technology assessment related to watching developments related to the risk. Standard concepts from clinical care: prevention, diagnosis, treatment, monitoring, rehabilitation, and surveillance, can be used to focus gaps dealing with risk mitigation. The research plan for the new HRP Risk of Decompression Sickness (DCS) used the framework to identify one disposition gap related to establishment of a DCS standard for acceptable risk, two knowledge gaps related to DCS phenomenon and mission attributes, and three mitigation gaps focused on prediction, prevention, and new technology watch. These gaps were organized in this manner primarily based on target for closure and ease of organizing interim metrics so that gap status could be quantified. Additional considerations for the knowledge gaps were that one was highly design reference mission specific and the other gap was focused on DCS phenomenon.

Performance Metrics for Liquid Chromatography-Tandem Mass Spectrometry Systems in Proteomics Analyses*

PubMed Central

Rudnick, Paul A.; Clauser, Karl R.; Kilpatrick, Lisa E.; Tchekhovskoi, Dmitrii V.; Neta, Pedatsur; Blonder, Nikša; Billheimer, Dean D.; Blackman, Ronald K.; Bunk, David M.; Cardasis, Helene L.; Ham, Amy-Joan L.; Jaffe, Jacob D.; Kinsinger, Christopher R.; Mesri, Mehdi; Neubert, Thomas A.; Schilling, Birgit; Tabb, David L.; Tegeler, Tony J.; Vega-Montoto, Lorenzo; Variyath, Asokan Mulayath; Wang, Mu; Wang, Pei; Whiteaker, Jeffrey R.; Zimmerman, Lisa J.; Carr, Steven A.; Fisher, Susan J.; Gibson, Bradford W.; Paulovich, Amanda G.; Regnier, Fred E.; Rodriguez, Henry; Spiegelman, Cliff; Tempst, Paul; Liebler, Daniel C.; Stein, Stephen E.

2010-01-01

A major unmet need in LC-MS/MS-based proteomics analyses is a set of tools for quantitative assessment of system performance and evaluation of technical variability. Here we describe 46 system performance metrics for monitoring chromatographic performance, electrospray source stability, MS1 and MS2 signals, dynamic sampling of ions for MS/MS, and peptide identification. Applied to data sets from replicate LC-MS/MS analyses, these metrics displayed consistent, reasonable responses to controlled perturbations. The metrics typically displayed variations less than 10% and thus can reveal even subtle differences in performance of system components. Analyses of data from interlaboratory studies conducted under a common standard operating procedure identified outlier data and provided clues to specific causes. Moreover, interlaboratory variation reflected by the metrics indicates which system components vary the most between laboratories. Application of these metrics enables rational, quantitative quality assessment for proteomics and other LC-MS/MS analytical applications. PMID:19837981

A Classification Scheme for Smart Manufacturing Systems’ Performance Metrics

PubMed Central

Lee, Y. Tina; Kumaraguru, Senthilkumaran; Jain, Sanjay; Robinson, Stefanie; Helu, Moneer; Hatim, Qais Y.; Rachuri, Sudarsan; Dornfeld, David; Saldana, Christopher J.; Kumara, Soundar

2017-01-01

This paper proposes a classification scheme for performance metrics for smart manufacturing systems. The discussion focuses on three such metrics: agility, asset utilization, and sustainability. For each of these metrics, we discuss classification themes, which we then use to develop a generalized classification scheme. In addition to the themes, we discuss a conceptual model that may form the basis for the information necessary for performance evaluations. Finally, we present future challenges in developing robust, performance-measurement systems for real-time, data-intensive enterprises. PMID:28785744

Performance regression manager for large scale systems

DOEpatents

Faraj, Daniel A.

2017-10-17

System and computer program product to perform an operation comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputting for display an indication of a result of the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.

Control devices and steering strategies in pathway surgery.

PubMed

Fan, Chunman; Jelínek, Filip; Dodou, Dimitra; Breedveld, Paul

2015-02-01

For pathway surgery, that is, minimally invasive procedures carried out transluminally or through instrument-created pathways, handheld maneuverable instruments are being developed. As the accompanying control interfaces of such instruments have not been optimized for intuitive manipulation, we investigated the effect of control mode (1DoF or 2DoF), and control device (joystick or handgrip) on human performance in a navigation task. The experiments were conducted using the Endo-PaC (Endoscopic-Path Controller), a simulator that emulates the shaft and handle of a maneuverable instrument, combined with custom-developed software animating pathway surgical scenarios. Participants were asked to guide a virtual instrument without collisions toward a target located at the end of a virtual curved tunnel. The performance was assessed in terms of task completion time, path length traveled by the virtual instrument, motion smoothness, collision metrics, subjective workload, and personal preference. The results indicate that 2DoF control leads to faster task completion and fewer collisions with the tunnel wall combined with a strong subjective preference compared with 1DoF control. Handgrip control appeared to be more intuitive to master than joystick control. However, the participants experienced greater physical demand and had longer path lengths with handgrip than joystick control. Copyright © 2015 Elsevier Inc. All rights reserved.

Maximizing sensitivity of the psychomotor vigilance test (PVT) to sleep loss.

PubMed

Basner, Mathias; Dinges, David F

2011-05-01

The psychomotor vigilance test (PVT) is among the most widely used measures of behavioral alertness, but there is large variation among published studies in PVT performance outcomes and test durations. To promote standardization of the PVT and increase its sensitivity and specificity to sleep loss, we determined PVT metrics and task durations that optimally discriminated sleep deprived subjects from alert subjects. Repeated-measures experiments involving 10-min PVT assessments every 2 h across both acute total sleep deprivation (TSD) and 5 days of chronic partial sleep deprivation (PSD). Controlled laboratory environment. 74 healthy subjects (34 female), aged 22-45 years. TSD experiment involving 33 h awake (N = 31 subjects) and a PSD experiment involving 5 nights of 4 h time in bed (N = 43 subjects). In a paired t-test paradigm and for both TSD and PSD, effect sizes of 10 different PVT performance outcomes were calculated. Effect sizes were high for both TSD (1.59-1.94) and PSD (0.88-1.21) for PVT metrics related to lapses and to measures of psychomotor speed, i.e., mean 1/RT (response time) and mean slowest 10% 1/RT. In contrast, PVT mean and median RT outcomes scored low to moderate effect sizes influenced by extreme values. Analyses facilitating only portions of the full 10-min PVT indicated that for some outcomes, high effect sizes could be achieved with PVT durations considerably shorter than 10 min, although metrics involving lapses seemed to profit from longer test durations in TSD. Due to their superior conceptual and statistical properties and high sensitivity to sleep deprivation, metrics involving response speed and lapses should be considered primary outcomes for the 10-min PVT. In contrast, PVT mean and median metrics, which are among the most widely used outcomes, should be avoided as primary measures of alertness. Our analyses also suggest that some shorter-duration PVT versions may be sensitive to sleep loss, depending on the outcome variable selected, although this will need to be confirmed in comparative analyses of separate duration versions of the PVT. Using both sensitive PVT metrics and optimal test durations maximizes the sensitivity of the PVT to sleep loss and therefore potentially decreases the sample size needed to detect the same neurobehavioral deficit. We propose criteria to better standardize the 10-min PVT and facilitate between-study comparisons and meta-analyses.

Do resident's leadership skills relate to ratings of technical skill?

PubMed

Gannon, Samantha J; Law, Katherine E; Ray, Rebecca D; Nathwani, Jay N; DiMarco, Shannon M; D'Angelo, Anne-Lise D; Pugh, Carla M

2016-12-01

This study sought to compare general surgery research residents' survey information regarding self-efficacy ratings to their observed performance during a simulated small bowel repair. Their observed performance ratings were based on their leadership skills in directing their assistant. Participants were given 15 min to perform a bowel repair using bovine intestines with standardized injuries. Operative assistants were assigned to help assist with the repair. Before the procedure, participants were asked to rate their expected skills decay, task difficulty, and confidence in addressing the small bowel injury. Interactions were coded to identify the number of instructions given by the participants to the assistant during the repair. Statistical analyses assessed the relationship between the number of directional instructions and participants' perceptions self-efficacy measures. Directional instructions were defined as any dialog by the participant who guided the assistant to perform an action. Thirty-six residents (58.3% female) participated in the study. Participants who rated lower levels of decay in their intraoperative decision-making and small bowel repair skills were noted to use their assistant more by giving more instructions. Similarly, a higher number of instructions correlated with lower perceived difficulty in selecting the correct suture, suture pattern, and completing the entire surgical task. General surgery research residents' intraoperative leadership skills showed significant correlations to their perceptions of skill decay and task difficulty during a bowel repair. Evaluating resident's directional instructions may provide an additional individualized intraoperative assessment metric. Further evaluation relating to operative performance outcomes is warranted. Copyright © 2016 Elsevier Inc. All rights reserved.

Real-time simultaneous and proportional myoelectric control using intramuscular EMG

PubMed Central

Kuiken, Todd A; Hargrove, Levi J

2014-01-01

Objective Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main Results Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts' Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts' Law tasks with high levels of path efficiency. Significance These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control. PMID:25394366

Real-time simultaneous and proportional myoelectric control using intramuscular EMG

NASA Astrophysics Data System (ADS)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2014-12-01

Objective. Myoelectric prostheses use electromyographic (EMG) signals to control movement of prosthetic joints. Clinically available myoelectric control strategies do not allow simultaneous movement of multiple degrees of freedom (DOFs); however, the use of implantable devices that record intramuscular EMG signals could overcome this constraint. The objective of this study was to evaluate the real-time simultaneous control of three DOFs (wrist rotation, wrist flexion/extension, and hand open/close) using intramuscular EMG. Approach. We evaluated task performance of five able-bodied subjects in a virtual environment using two control strategies with fine-wire EMG: (i) parallel dual-site differential control, which enabled simultaneous control of three DOFs and (ii) pattern recognition control, which required sequential control of DOFs. Main results. Over the course of the experiment, subjects using parallel dual-site control demonstrated increased use of simultaneous control and improved performance in a Fitts’ Law test. By the end of the experiment, performance using parallel dual-site control was significantly better (up to a 25% increase in throughput) than when using sequential pattern recognition control for tasks requiring multiple DOFs. The learning trends with parallel dual-site control suggested that further improvements in performance metrics were possible. Subjects occasionally experienced difficulty in performing isolated single-DOF movements with parallel dual-site control but were able to accomplish related Fitts’ Law tasks with high levels of path efficiency. Significance. These results suggest that intramuscular EMG, used in a parallel dual-site configuration, can provide simultaneous control of a multi-DOF prosthetic wrist and hand and may outperform current methods that enforce sequential control.

Initial validation of a virtual-reality robotic simulator.

PubMed

Lendvay, Thomas S; Casale, Pasquale; Sweet, Robert; Peters, Craig

2008-09-01

Robotic surgery is an accepted adjunct to minimally invasive surgery, but training is restricted to console time. Virtual-reality (VR) simulation has been shown to be effective for laparoscopic training and so we seek to validate a novel VR robotic simulator. The American Urological Association (AUA) Office of Education approved this study. Subjects enrolled in a robotics training course at the 2007 AUA annual meeting underwent skills training in a da Vinci dry-lab module and a virtual-reality robotics module which included a three-dimensional (3D) VR robotic simulator. Demographic and acceptability data were obtained, and performance metrics from the simulator were compared between experienced and nonexperienced roboticists for a ring transfer task. Fifteen subjects-four with previous robotic surgery experience and 11 without-participated. Nine subjects were still in urology training and nearly half of the group had reported playing video games. Overall performance of the da Vinci system and the simulator were deemed acceptable by a Likert scale (0-6) rating of 5.23 versus 4.69, respectively. Experienced subjects outperformed nonexperienced subjects on the simulator on three metrics: total task time (96 s versus 159 s, P < 0.02), economy of motion (1,301 mm versus 2,095 mm, P < 0.04), and time the telemanipulators spent outside of the center of the platform's workspace (4 s versus 35 s, P < 0.02). This is the first demonstration of face and construct validity of a virtual-reality robotic simulator. Further studies assessing predictive validity are ultimately required to support incorporation of VR robotic simulation into training curricula.

Quantification of Dynamic Model Validation Metrics Using Uncertainty Propagation from Requirements

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Peck, Jeffrey A.; Stewart, Eric C.

2018-01-01

The Space Launch System, NASA's new large launch vehicle for long range space exploration, is presently in the final design and construction phases, with the first launch scheduled for 2019. A dynamic model of the system has been created and is critical for calculation of interface loads and natural frequencies and mode shapes for guidance, navigation, and control (GNC). Because of the program and schedule constraints, a single modal test of the SLS will be performed while bolted down to the Mobile Launch Pad just before the first launch. A Monte Carlo and optimization scheme will be performed to create thousands of possible models based on given dispersions in model properties and to determine which model best fits the natural frequencies and mode shapes from modal test. However, the question still remains as to whether this model is acceptable for the loads and GNC requirements. An uncertainty propagation and quantification (UP and UQ) technique to develop a quantitative set of validation metrics that is based on the flight requirements has therefore been developed and is discussed in this paper. There has been considerable research on UQ and UP and validation in the literature, but very little on propagating the uncertainties from requirements, so most validation metrics are "rules-of-thumb;" this research seeks to come up with more reason-based metrics. One of the main assumptions used to achieve this task is that the uncertainty in the modeling of the fixed boundary condition is accurate, so therefore that same uncertainty can be used in propagating the fixed-test configuration to the free-free actual configuration. The second main technique applied here is the usage of the limit-state formulation to quantify the final probabilistic parameters and to compare them with the requirements. These techniques are explored with a simple lumped spring-mass system and a simplified SLS model. When completed, it is anticipated that this requirements-based validation metric will provide a quantified confidence and probability of success for the final SLS dynamics model, which will be critical for a successful launch program, and can be applied in the many other industries where an accurate dynamic model is required.

On Applying the Prognostic Performance Metrics

NASA Technical Reports Server (NTRS)

Saxena, Abhinav; Celaya, Jose; Saha, Bhaskar; Saha, Sankalita; Goebel, Kai

2009-01-01

Prognostics performance evaluation has gained significant attention in the past few years. As prognostics technology matures and more sophisticated methods for prognostic uncertainty management are developed, a standardized methodology for performance evaluation becomes extremely important to guide improvement efforts in a constructive manner. This paper is in continuation of previous efforts where several new evaluation metrics tailored for prognostics were introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. Several shortcomings identified, while applying these metrics to a variety of real applications, are also summarized along with discussions that attempt to alleviate these problems. Further, these metrics have been enhanced to include the capability of incorporating probability distribution information from prognostic algorithms as opposed to evaluation based on point estimates only. Several methods have been suggested and guidelines have been provided to help choose one method over another based on probability distribution characteristics. These approaches also offer a convenient and intuitive visualization of algorithm performance with respect to some of these new metrics like prognostic horizon and alpha-lambda performance, and also quantify the corresponding performance while incorporating the uncertainty information.

Training safer orthopedic surgeons. Construct validation of a virtual-reality simulator for hip fracture surgery.

PubMed

Akhtar, Kashif; Sugand, Kapil; Sperrin, Matthew; Cobb, Justin; Standfield, Nigel; Gupte, Chinmay

2015-01-01

Virtual-reality (VR) simulation in orthopedic training is still in its infancy, and much of the work has been focused on arthroscopy. We evaluated the construct validity of a new VR trauma simulator for performing dynamic hip screw (DHS) fixation of a trochanteric femoral fracture. 30 volunteers were divided into 3 groups according to the number of postgraduate (PG) years and the amount of clinical experience: novice (1-4 PG years; less than 10 DHS procedures); intermediate (5-12 PG years; 10-100 procedures); expert (> 12 PG years; > 100 procedures). Each participant performed a DHS procedure and objective performance metrics were recorded. These data were analyzed with each performance metric taken as the dependent variable in 3 regression models. There were statistically significant differences in performance between groups for (1) number of attempts at guide-wire insertion, (2) total fluoroscopy time, (3) tip-apex distance, (4) probability of screw cutout, and (5) overall simulator score. The intermediate group performed the procedure most quickly, with the lowest fluoroscopy time, the lowest tip-apex distance, the lowest probability of cutout, and the highest simulator score, which correlated with their frequency of exposure to running the trauma lists for hip fracture surgery. This study demonstrates the construct validity of a haptic VR trauma simulator with surgeons undertaking the procedure most frequently performing best on the simulator. VR simulation may be a means of addressing restrictions on working hours and allows trainees to practice technical tasks without putting patients at risk. The VR DHS simulator evaluated in this study may provide valid assessment of technical skill.

75 FR 7581 - RTO/ISO Performance Metrics; Notice Requesting Comments on RTO/ISO Performance Metrics

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-22

... performance communicate about the benefits of RTOs and, where appropriate, (2) changes that need to be made to... of staff from all the jurisdictional ISOs/RTOs to develop a set of performance metrics that the ISOs/RTOs will use to report annually to the Commission. Commission staff and representatives from the ISOs...

Performance regression manager for large scale systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faraj, Daniel A.

Methods comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputting for display an indication of a result ofmore » the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.« less

Performance regression manager for large scale systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faraj, Daniel A.

System and computer program product to perform an operation comprising generating, based on a first output generated by a first execution instance of a command, a first output file specifying a value of at least one performance metric, wherein the first output file is formatted according to a predefined format, comparing the value of the at least one performance metric in the first output file to a value of the performance metric in a second output file, the second output file having been generated based on a second output generated by a second execution instance of the command, and outputtingmore » for display an indication of a result of the comparison of the value of the at least one performance metric of the first output file to the value of the at least one performance metric of the second output file.« less

Brain-Inspired Photonic Signal Processor for Generating Periodic Patterns and Emulating Chaotic Systems

NASA Astrophysics Data System (ADS)

Antonik, Piotr; Haelterman, Marc; Massar, Serge

2017-05-01

Reservoir computing is a bioinspired computing paradigm for processing time-dependent signals. Its hardware implementations have received much attention because of their simplicity and remarkable performance on a series of benchmark tasks. In previous experiments, the output was uncoupled from the system and, in most cases, simply computed off-line on a postprocessing computer. However, numerical investigations have shown that feeding the output back into the reservoir opens the possibility of long-horizon time-series forecasting. Here, we present a photonic reservoir computer with output feedback, and we demonstrate its capacity to generate periodic time series and to emulate chaotic systems. We study in detail the effect of experimental noise on system performance. In the case of chaotic systems, we introduce several metrics, based on standard signal-processing techniques, to evaluate the quality of the emulation. Our work significantly enlarges the range of tasks that can be solved by hardware reservoir computers and, therefore, the range of applications they could potentially tackle. It also raises interesting questions in nonlinear dynamics and chaos theory.

Intelligent vehicle control: Opportunities for terrestrial-space system integration

NASA Technical Reports Server (NTRS)

Shoemaker, Charles

1994-01-01

For 11 years the Department of Defense has cooperated with a diverse array of other Federal agencies including the National Institute of Standards and Technology, the Jet Propulsion Laboratory, and the Department of Energy, to develop robotics technology for unmanned ground systems. These activities have addressed control system architectures supporting sharing of tasks between the system operator and various automated subsystems, man-machine interfaces to intelligent vehicles systems, video compression supporting vehicle driving in low data rate digital communication environments, multiple simultaneous vehicle control by a single operator, path planning and retrace, and automated obstacle detection and avoidance subsystem. Performance metrics and test facilities for robotic vehicles were developed permitting objective performance assessment of a variety of operator-automated vehicle control regimes. Progress in these areas will be described in the context of robotic vehicle testbeds specifically developed for automated vehicle research. These initiatives, particularly as regards the data compression, task sharing, and automated mobility topics, also have relevance in the space environment. The intersection of technology development interests between these two communities will be discussed in this paper.

Reference Standards, Judges, and Comparison Subjects

PubMed Central

Hripcsak, George; Wilcox, Adam

2002-01-01

Medical informatics systems are often designed to perform at the level of human experts. Evaluation of the performance of these systems is often constrained by lack of reference standards, either because the appropriate response is not known or because no simple appropriate response exists. Even when performance can be assessed, it is not always clear whether the performance is sufficient or reasonable. These challenges can be addressed if an evaluator enlists the help of clinical domain experts. 1) The experts can carry out the same tasks as the system, and then their responses can be combined to generate a reference standard. 2)The experts can judge the appropriateness of system output directly. 3) The experts can serve as comparison subjects with which the system can be compared. These are separate roles that have different implications for study design, metrics, and issues of reliability and validity. Diagrams help delineate the roles of experts in complex study designs. PMID:11751799

On the use of drawing tasks in neuropsychological assessment.

PubMed

Smith, Alastair D

2009-03-01

Drawing tasks have attained a central position in neuropsychological assessment and are considered a rich source of information about the presence (or absence) of cognitive and perceptuo-motor abilities. However, unlike other tests of cognitive impairment, drawing tasks are often administered without reference to normative models of graphic production, and their results are often analyzed qualitatively. I begin this article by delineating the different ways in which drawing errors have been used to indicate particular functional deficits in neurological patients. I then describe models of drawing that have been explicitly based on the errors observed in patient drawings. Finally, the case is made for developing a more sensitive set of metrics in order to quantitatively assess patient performance. By providing a finer grain of analysis to assessment we will not only be better able to characterize the consequences of cognitive dysfunction, but may also be able to more subtly characterize and dissociate patients who would otherwise have been placed in the same broad category of impairment. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

3D-printing a 'family' of biomimetic models to explain armored grasping in syngnathid fishes.

PubMed

Porter, Michael M; Ravikumar, Nakul

2017-11-06

Seahorses and pipehorses evolved at least two independent strategies for tail grasping, despite being armored with a heavy body plating. To help explain mechanical trade-offs associated with the different designs, we created a 'family' of 3D-printed models that mimic variations in the presence and size of their armored plates. We measured the performance of the biomimetic proxies across several mechanical metrics, representative of their protective and prehensile capacities. Our results show that the models mimicking the tails of seahorses are the best all-around performers, while those of the distal-most, prehensile region of pipehorses are more flexible, but less protected. The comparison also reveals that different adaptive strategies provide different task-specific performance advantages, which could be leveraged for the design of armored manipulators or other bio-inspired technologies.

The effect of saccade metrics on the corollary discharge contribution to perceived eye location

PubMed Central

Bansal, Sonia; Jayet Bray, Laurence C.; Peterson, Matthew S.

2015-01-01

Corollary discharge (CD) is hypothesized to provide the movement information (direction and amplitude) required to compensate for the saccade-induced disruptions to visual input. Here, we investigated to what extent these conveyed metrics influence perceptual stability in human subjects with a target-displacement detection task. Subjects made saccades to targets located at different amplitudes (4°, 6°, or 8°) and directions (horizontal or vertical). During the saccade, the target disappeared and then reappeared at a shifted location either in the same direction or opposite to the movement vector. Subjects reported the target displacement direction, and from these reports we determined the perceptual threshold for shift detection and estimate of target location. Our results indicate that the thresholds for all amplitudes and directions generally scaled with saccade amplitude. Additionally, subjects on average produced hypometric saccades with an estimated CD gain <1. Finally, we examined the contribution of different error signals to perceptual performance, the saccade error (movement-to-movement variability in saccade amplitude) and visual error (distance between the fovea and the shifted target location). Perceptual judgment was not influenced by the fluctuations in movement amplitude, and performance was largely the same across movement directions for different magnitudes of visual error. Importantly, subjects reported the correct direction of target displacement above chance level for very small visual errors (<0.75°), even when these errors were opposite the target-shift direction. Collectively, these results suggest that the CD-based compensatory mechanisms for visual disruptions are highly accurate and comparable for saccades with different metrics. PMID:25761955

An Increase in Postural Load Facilitates an Anterior Shift of Processing Resources to Frontal Executive Function in a Postural-Suprapostural Task

PubMed Central

Huang, Cheng-Ya; Chang, Gwo-Ching; Tsai, Yi-Ying; Hwang, Ing-Shiou

2016-01-01

Increase in postural-demand resources does not necessarily degrade a concurrent motor task, according to the adaptive resource-sharing hypothesis of postural-suprapostural dual-tasking. This study investigated how brain networks are organized to optimize a suprapostural motor task when the postural load increases and shifts postural control into a less automatic process. Fourteen volunteers executed a designated force-matching task from a level surface (a relative automatic process in posture) and from a stabilometer board while maintaining balance at a target angle (a relatively controlled process in posture). Task performance of the postural and suprapostural tasks, synchronization likelihood (SL) of scalp EEG, and graph-theoretical metrics were assessed. Behavioral results showed that the accuracy and reaction time of force-matching from a stabilometer board were not affected, despite a significant increase in postural sway. However, force-matching in the stabilometer condition showed greater local and global efficiencies of the brain networks than force-matching in the level-surface condition. Force-matching from a stabilometer board was also associated with greater frontal cluster coefficients, greater mean SL of the frontal and sensorimotor areas, and smaller mean SL of the parietal-occipital cortex than force-matching from a level surface. The contrast of supra-threshold links in the upper alpha and beta bands between the two stance conditions validated load-induced facilitation of inter-regional connections between the frontal and sensorimotor areas, but that contrast also indicated connection suppression between the right frontal-temporal and the parietal-occipital areas for the stabilometer stance condition. In conclusion, an increase in stance difficulty alters the neurocognitive processes in executing a postural-suprapostural task. Suprapostural performance is not degraded by increase in postural load, due to (1) increased effectiveness of information transfer, (2) an anterior shift of processing resources toward frontal executive function, and (3) cortical dissociation of control hubs in the parietal-occipital cortex for neural economy. PMID:27594830

Oculomotor evidence for neocortical systems but not cerebellar dysfunction in autism

PubMed Central

Minshew, Nancy J.; Luna, Beatriz; Sweeney, John A.

2010-01-01

Objective To investigate the functional integrity of cerebellar and frontal system in autism using oculomotor paradigms. Background Cerebellar and neocortical systems models of autism have been proposed. Courchesne and colleagues have argued that cognitive deficits such as shifting attention disturbances result from dysfunction of vermal lobules VI and VII. Such a vermal deficit should be associated with dysmetric saccadic eye movements because of the major role these areas play in guiding the motor precision of saccades. In contrast, neocortical models of autism predict intact saccade metrics, but impairments on tasks requiring the higher cognitive control of saccades. Methods A total of 26 rigorously diagnosed nonmentally retarded autistic subjects and 26 matched healthy control subjects were assessed with a visually guided saccade task and two volitional saccade tasks, the oculomotor delayed-response task and the antisaccade task. Results Metrics and dynamic of the visually guided saccades were normal in autistic subjects, documenting the absence of disturbances in cerebellar vermal lobules VI and VII and in automatic shifts of visual attention. Deficits were demonstrated on both volitional saccade tasks, indicating dysfunction in the circuitry of prefrontal cortex and its connections with the parietal cortex, and associated cognitive impairments in spatial working memory and in the ability to voluntarily suppress context-inappropriate responses. Conclusions These findings demonstrate intrinsic neocortical, not cerebellar, dysfunction in autism, and parallel deficits in higher order cognitive mechanisms and not in elementary attentional and sensorimotor systems in autism. PMID:10102406

Sit Up Straight

NASA Technical Reports Server (NTRS)

1998-01-01

BioMetric Systems has an exclusive license to the Posture Video Analysis Tool (PVAT) developed at Johnson Space Center. PVAT uses videos from Space Shuttle flights to identify limiting posture and other human factors in the workplace that could be limiting. The software also provides data that recommends appropriate postures for certain tasks and safe duration for potentially harmful positions. BioMetric Systems has further developed PVAT for use by hospitals, physical rehabilitation facilities, insurance companies, sports medicine clinics, oil companies, manufacturers, and the military.

USSR Report, Agriculture, No. 1392

DTIC Science & Technology

1983-07-26

from more than 200,000 hectares: 60,000 metric tons of hay and 130,000 metric tons of haylage have been procured. (1100 GMT) Kuban farmers have...total of about 1 million tons of hay, almost 2.5 million tons of haylage has been laid in and 200,000 tons of vitaminwsf [as printed] grass meal has...is being given to deliveries of haylage . In Krasnodar Kray the percentage of task fulfill- ment for this kind of fodder is now twice as high as for

Recommendations of the wwPDB NMR Validation Task Force

PubMed Central

Montelione, Gaetano T.; Nilges, Michael; Bax, Ad; Güntert, Peter; Herrmann, Torsten; Richardson, Jane S.; Schwieters, Charles; Vranken, Wim F.; Vuister, Geerten W.; Wishart, David S.; Berman, Helen M.; Kleywegt, Gerard J.; Markley, John L.

2013-01-01

As methods for analysis of biomolecular structure and dynamics using nuclear magnetic resonance spectroscopy (NMR) continue to advance, the resulting 3D structures, chemical shifts, and other NMR data are broadly impacting biology, chemistry, and medicine. Structure model assessment is a critical area of NMR methods development, and is an essential component of the process of making these structures accessible and useful to the wider scientific community. For these reasons, the Worldwide Protein Data Bank (wwPDB) has convened an NMR Validation Task Force (NMR-VTF) to work with the wwPDB partners in developing metrics and policies for biomolecular NMR data harvesting, structure representation, and structure quality assessment. This paper summarizes the recommendations of the NMR-VTF, and lays the groundwork for future work in developing standards and metrics for biomolecular NMR structure quality assessment. PMID:24010715

Prenatal ethanol exposure impairs temporal ordering behaviours in young adult rats.

PubMed

Patten, Anna R; Sawchuk, Scott; Wortman, Ryan C; Brocardo, Patricia S; Gil-Mohapel, Joana; Christie, Brian R

2016-02-15

Prenatal ethanol exposure (PNEE) causes significant deficits in functional (i.e., synaptic) plasticity in the dentate gyrus (DG) and cornu ammonis (CA) hippocampal sub-regions of young adult male rats. Previous research has shown that in the DG, these deficits are not apparent in age-matched PNEE females. This study aimed to expand these findings and determine if PNEE induces deficits in hippocampal-dependent behaviours in both male and female young adult rats (PND 60). The metric change behavioural test examines DG-dependent deficits by determining whether an animal can detect a metric change between two identical objects. The temporal order behavioural test is thought to rely in part on the CA sub-region of the hippocampus and determines whether an animal will spend more time exploring an object that it has not seen for a larger temporal window as compared to an object that it has seen more recently. Using the liquid diet model of FASD (where 6.6% (v/v) ethanol is provided through a liquid diet consumed ad libitum throughout the entire gestation), we found that PNEE causes a significant impairment in the temporal order task, while no deficits in the DG-dependent metric change task were observed. There were no significant differences between males and females for either task. These results indicate that behaviours relying partially on the CA-region may be more affected by PNEE than those that rely on the DG. Copyright © 2015 Elsevier B.V. All rights reserved.

A New Perspective for the Training Assessment: Machine Learning-Based Neurometric for Augmented User's Evaluation

PubMed Central

Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Sciaraffa, Nicolina; Colosimo, Alfredo; Herrero, Maria-Trinidad; Bezerianos, Anastasios; Thakor, Nitish V.; Babiloni, Fabio

2017-01-01

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity (neurometric) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs. PMID:28659751

A New Perspective for the Training Assessment: Machine Learning-Based Neurometric for Augmented User's Evaluation.

PubMed

Borghini, Gianluca; Aricò, Pietro; Di Flumeri, Gianluca; Sciaraffa, Nicolina; Colosimo, Alfredo; Herrero, Maria-Trinidad; Bezerianos, Anastasios; Thakor, Nitish V; Babiloni, Fabio

2017-01-01

Inappropriate training assessment might have either high social costs and economic impacts, especially in high risks categories, such as Pilots, Air Traffic Controllers, or Surgeons. One of the current limitations of the standard training assessment procedures is the lack of information about the amount of cognitive resources requested by the user for the correct execution of the proposed task. In fact, even if the task is accomplished achieving the maximum performance, by the standard training assessment methods, it would not be possible to gather and evaluate information about cognitive resources available for dealing with unexpected events or emergency conditions. Therefore, a metric based on the brain activity ( neurometric ) able to provide the Instructor such a kind of information should be very important. As a first step in this direction, the Electroencephalogram (EEG) and the performance of 10 participants were collected along a training period of 3 weeks, while learning the execution of a new task. Specific indexes have been estimated from the behavioral and EEG signal to objectively assess the users' training progress. Furthermore, we proposed a neurometric based on a machine learning algorithm to quantify the user's training level within each session by considering the level of task execution, and both the behavioral and cognitive stabilities between consecutive sessions. The results demonstrated that the proposed methodology and neurometric could quantify and track the users' progresses, and provide the Instructor information for a more objective evaluation and better tailoring of training programs.

Usability Operations on Touch Mobile Devices for Users with Autism.

PubMed

Quezada, Angeles; Juárez-Ramírez, Reyes; Jiménez, Samantha; Noriega, Alan Ramírez; Inzunza, Sergio; Garza, Arnulfo Alanis

2017-10-14

The Autistic Spectrum Disorder is a cognitive disorder that affects the cognitive and motor skills; due that, users cannot perform digital and fine motor tasks. It is necessary to create software applications that adapt to the abilities of these users. In recent years has been an increase in the research of the use of technology to support autistic users to develop their communication skills and to improve learning. However, the applications' usability for disable users is not assessed objectively as the existing models do not consider interaction operators for disable users. This article focuses on identifying the operations that can easily be performed by autistic users following the metrics of KML-GOMS, TLM and FLM. In addition, users of typical development were included in order to do a comparison between both types of users. The experiment was carried out using four applications designed for autistic users. Participants were subjects divided in two groups: level 1 and level 2 autistic users, and a group of users of typical development. During the experimentation, users performed a use case for each application; the time needed to perform each task was measured. Results show that the easiest operations for autistic users are K (Keystroke), D (Drag), Initial Act (I) and Tapping (T).

Developing a confidence metric for the Landsat land surface temperature product

NASA Astrophysics Data System (ADS)

Laraby, Kelly G.; Schott, John R.; Raqueno, Nina

2016-05-01

Land Surface Temperature (LST) is an important Earth system data record that is useful to fields such as change detection, climate research, environmental monitoring, and smaller scale applications such as agriculture. Certain Earth-observing satellites can be used to derive this metric, and it would be extremely useful if such imagery could be used to develop a global product. Through the support of the National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS), a LST product for the Landsat series of satellites has been developed. Currently, it has been validated for scenes in North America, with plans to expand to a trusted global product. For ideal atmospheric conditions (e.g. stable atmosphere with no clouds nearby), the LST product underestimates the surface temperature by an average of 0.26 K. When clouds are directly above or near the pixel of interest, however, errors can extend to several Kelvin. As the product approaches public release, our major goal is to develop a quality metric that will provide the user with a per-pixel map of estimated LST errors. There are several sources of error that are involved in the LST calculation process, but performing standard error propagation is a difficult task due to the complexity of the atmospheric propagation component. To circumvent this difficulty, we propose to utilize the relationship between cloud proximity and the error seen in the LST process to help develop a quality metric. This method involves calculating the distance to the nearest cloud from a pixel of interest in a scene, and recording the LST error at that location. Performing this calculation for hundreds of scenes allows us to observe the average LST error for different ranges of distances to the nearest cloud. This paper describes this process in full, and presents results for a large set of Landsat scenes.

The power metric: a new statistically robust enrichment-type metric for virtual screening applications with early recovery capability.

PubMed

Lopes, Julio Cesar Dias; Dos Santos, Fábio Mendes; Martins-José, Andrelly; Augustyns, Koen; De Winter, Hans

2017-01-01

A new metric for the evaluation of model performance in the field of virtual screening and quantitative structure-activity relationship applications is described. This metric has been termed the power metric and is defined as the fraction of the true positive rate divided by the sum of the true positive and false positive rates, for a given cutoff threshold. The performance of this metric is compared with alternative metrics such as the enrichment factor, the relative enrichment factor, the receiver operating curve enrichment factor, the correct classification rate, Matthews correlation coefficient and Cohen's kappa coefficient. The performance of this new metric is found to be quite robust with respect to variations in the applied cutoff threshold and ratio of the number of active compounds to the total number of compounds, and at the same time being sensitive to variations in model quality. It possesses the correct characteristics for its application in early-recognition virtual screening problems.

Uncooperative target-in-the-loop performance with backscattered speckle-field effects

NASA Astrophysics Data System (ADS)

Kansky, Jan E.; Murphy, Daniel V.

2007-09-01

Systems utilizing target-in-the-loop (TIL) techniques for adaptive optics phase compensation rely on a metric sensor to perform a hill climbing algorithm that maximizes the far-field Strehl ratio. In uncooperative TIL, the metric signal is derived from the light backscattered from a target. In cases where the target is illuminated with a laser with suffciently long coherence length, the potential exists for the validity of the metric sensor to be compromised by speckle-field effects. We report experimental results from a scaled laboratory designed to evaluate TIL performance in atmospheric turbulence and thermal blooming conditions where the metric sensors are influenced by varying degrees of backscatter speckle. We compare performance of several TIL configurations and metrics for cases with static speckle, and for cases with speckle fluctuations within the frequency range that the TIL system operates. The roles of metric sensor filtering and system bandwidth are discussed.

Impact of Different Economic Performance Metrics on the Perceived Value of Solar Photovoltaics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drury, E.; Denholm, P.; Margolis, R.

2011-10-01

Photovoltaic (PV) systems are installed by several types of market participants, ranging from residential customers to large-scale project developers and utilities. Each type of market participant frequently uses a different economic performance metric to characterize PV value because they are looking for different types of returns from a PV investment. This report finds that different economic performance metrics frequently show different price thresholds for when a PV investment becomes profitable or attractive. Several project parameters, such as financing terms, can have a significant impact on some metrics [e.g., internal rate of return (IRR), net present value (NPV), and benefit-to-cost (B/C)more » ratio] while having a minimal impact on other metrics (e.g., simple payback time). As such, the choice of economic performance metric by different customer types can significantly shape each customer's perception of PV investment value and ultimately their adoption decision.« less

An exploratory survey of methods used to develop measures of performance

NASA Astrophysics Data System (ADS)

Hamner, Kenneth L.; Lafleur, Charles A.

1993-09-01

Nonmanufacturing organizations are being challenged to provide high-quality products and services to their customers, with an emphasis on continuous process improvement. Measures of performance, referred to as metrics, can be used to foster process improvement. The application of performance measurement to nonmanufacturing processes can be very difficult. This research explored methods used to develop metrics in nonmanufacturing organizations. Several methods were formally defined in the literature, and the researchers used a two-step screening process to determine the OMB Generic Method was most likely to produce high-quality metrics. The OMB Generic Method was then used to develop metrics. A few other metric development methods were found in use at nonmanufacturing organizations. The researchers interviewed participants in metric development efforts to determine their satisfaction and to have them identify the strengths and weaknesses of, and recommended improvements to, the metric development methods used. Analysis of participants' responses allowed the researchers to identify the key components of a sound metrics development method. Those components were incorporated into a proposed metric development method that was based on the OMB Generic Method, and should be more likely to produce high-quality metrics that will result in continuous process improvement.

Specification and implementation of IFC based performance metrics to support building life cycle assessment of hybrid energy systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morrissey, Elmer; O'Donnell, James; Keane, Marcus

2004-03-29

Minimizing building life cycle energy consumption is becoming of paramount importance. Performance metrics tracking offers a clear and concise manner of relating design intent in a quantitative form. A methodology is discussed for storage and utilization of these performance metrics through an Industry Foundation Classes (IFC) instantiated Building Information Model (BIM). The paper focuses on storage of three sets of performance data from three distinct sources. An example of a performance metrics programming hierarchy is displayed for a heat pump and a solar array. Utilizing the sets of performance data, two discrete performance effectiveness ratios may be computed, thus offeringmore » an accurate method of quantitatively assessing building performance.« less

Citizen science: A new perspective to evaluate spatial patterns in hydrology.

NASA Astrophysics Data System (ADS)

Koch, J.; Stisen, S.

2016-12-01

Citizen science opens new pathways that can complement traditional scientific practice. Intuition and reasoning make humans often more effective than computer algorithms in various realms of problem solving. In particular, a simple visual comparison of spatial patterns is a task where humans are often considered to be more reliable than computer algorithms. However, in practice, science still largely depends on computer based solutions, which is inevitable giving benefits such as speed and the possibility to automatize processes. This study highlights the integration of the generally underused human resource into hydrology. We established a citizen science project on the zooniverse platform entitled Pattern Perception. The aim is to employ the human perception to rate similarity and dissimilarity between simulated spatial patterns of a hydrological catchment model. In total, the turnout counts more than 2,800 users that provided over 46,000 classifications of 1,095 individual subjects within 64 days after the launch. Each subject displays simulated spatial patterns of land-surface variables of a baseline model and six modelling scenarios. The citizen science data discloses a numeric pattern similarity score for each of the scenarios with respect to the reference. We investigate the capability of a set of innovative statistical performance metrics to mimic the human perception to distinguish between similarity and dissimilarity. Results suggest that more complex metrics are not necessarily better at emulating the human perception, but clearly provide flexibility and auxiliary information that is valuable for model diagnostics. The metrics clearly differ in their ability to unambiguously distinguish between similar and dissimilar patterns which is regarded a key feature of a reliable metric.