Interface Prostheses With Classifier-Feedback-Based User Training.

PubMed

Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

2017-11-01

It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.

Development and evaluation of a hand tracker using depth images captured from an overhead perspective.

PubMed

Czarnuch, Stephen; Mihailidis, Alex

2015-03-27

We present the development and evaluation of a robust hand tracker based on single overhead depth images for use in the COACH, an assistive technology for people with dementia. The new hand tracker was designed to overcome limitations experienced by the COACH in previous clinical trials. We train a random decision forest classifier using ∼5000 manually labeled, unbalanced, training images. Hand positions from the classifier are translated into task actions based on proximity to environmental objects. Tracker performance is evaluated using a large set of ∼24 000 manually labeled images captured from 41 participants in a fully-functional washroom, and compared to the system's previous colour-based hand tracker. Precision and recall were 0.994 and 0.938 for the depth tracker compared to 0.981 and 0.822 for the colour tracker with the current data, and 0.989 and 0.466 in the previous study. The improved tracking performance supports integration of the depth-based tracker into the COACH toward unsupervised, real-world trials. Implications for Rehabilitation The COACH is an intelligent assistive technology that can enable people with cognitive disabilities to stay at home longer, supporting the concept of aging-in-place. Automated prompting systems, a type of intelligent assistive technology, can help to support the independent completion of activities of daily living, increasing the independence of people with cognitive disabilities while reducing the burden of care experienced by caregivers. Robust motion tracking using depth imaging supports the development of intelligent assistive technologies like the COACH. Robust motion tracking also has application to other forms of assistive technologies including gaming, human-computer interaction and automated assessments.

Neural networks for sign language translation

NASA Astrophysics Data System (ADS)

Wilson, Beth J.; Anspach, Gretel

1993-09-01

A neural network is used to extract relevant features of sign language from video images of a person communicating in American Sign Language or Signed English. The key features are hand motion, hand location with respect to the body, and handshape. A modular hybrid design is under way to apply various techniques, including neural networks, in the development of a translation system that will facilitate communication between deaf and hearing people. One of the neural networks described here is used to classify video images of handshapes into their linguistic counterpart in American Sign Language. The video image is preprocessed to yield Fourier descriptors that encode the shape of the hand silhouette. These descriptors are then used as inputs to a neural network that classifies their shapes. The network is trained with various examples from different signers and is tested with new images from new signers. The results have shown that for coarse handshape classes, the network is invariant to the type of camera used to film the various signers and to the segmentation technique.

The investigation of brain-computer interface for motor imagery and execution using functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Zhen; Jiao, Xuejun; Xu, Fengang; Jiang, Jin; Yang, Hanjun; Cao, Yong; Fu, Jiahao

2017-01-01

Functional near-infrared spectroscopy (fNIRS), which can measure cortex hemoglobin activity, has been widely adopted in brain-computer interface (BCI). To explore the feasibility of recognizing motor imagery (MI) and motor execution (ME) in the same motion. We measured changes of oxygenated hemoglobin (HBO) and deoxygenated hemoglobin (HBR) on PFC and Motor Cortex (MC) when 15 subjects performing hand extension and finger tapping tasks. The mean, slope, quadratic coefficient and approximate entropy features were extracted from HBO as the input of support vector machine (SVM). For the four-class fNIRS-BCI classifiers, we realized 87.65% and 87.58% classification accuracy corresponding to hand extension and finger tapping tasks. In conclusion, it is effective for fNIRS-BCI to recognize MI and ME in the same motion.

Bilinear modeling of EMG signals to extract user-independent features for multiuser myoelectric interface.

PubMed

Matsubara, Takamitsu; Morimoto, Jun

2013-08-01

In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user-dependent factor through only a few interactions. The bilinear EMG model with the estimated user-dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%.

Exploration of Hand Grasp Patterns Elicitable Through Non-Invasive Proximal Nerve Stimulation.

PubMed

Shin, Henry; Watkins, Zach; Hu, Xiaogang

2017-11-29

Various neurological conditions, such as stroke or spinal cord injury, result in an impaired control of the hand. One method of restoring this impairment is through functional electrical stimulation (FES). However, traditional FES techniques often lead to quick fatigue and unnatural ballistic movements. In this study, we sought to explore the capabilities of a non-invasive proximal nerve stimulation technique in eliciting various hand grasp patterns. The ulnar and median nerves proximal to the elbow joint were activated transcutanously using a programmable stimulator, and the resultant finger flexion joint angles were recorded using a motion capture system. The individual finger motions averaged across the three joints were analyzed using a cluster analysis, in order to classify the different hand grasp patterns. With low current intensity (<5 mA and 100 µs pulse width) stimulation, our results show that all of our subjects demonstrated a variety of consistent hand grasp patterns including single finger movement and coordinated multi-finger movements. This study provides initial evidence on the feasibility of a proximal nerve stimulation technique in controlling a variety of finger movements and grasp patterns. Our approach could also be developed into a rehabilitative/assistive tool that can result in flexible movements of the fingers.

Biomechanical Reconstruction Using the Tacit Learning System: Intuitive Control of Prosthetic Hand Rotation.

PubMed

Oyama, Shintaro; Shimoda, Shingo; Alnajjar, Fady S K; Iwatsuki, Katsuyuki; Hoshiyama, Minoru; Tanaka, Hirotaka; Hirata, Hitoshi

2016-01-01

Background: For mechanically reconstructing human biomechanical function, intuitive proportional control, and robustness to unexpected situations are required. Particularly, creating a functional hand prosthesis is a typical challenge in the reconstruction of lost biomechanical function. Nevertheless, currently available control algorithms are in the development phase. The most advanced algorithms for controlling multifunctional prosthesis are machine learning and pattern recognition of myoelectric signals. Despite the increase in computational speed, these methods cannot avoid the requirement of user consciousness and classified separation errors. "Tacit Learning System" is a simple but novel adaptive control strategy that can self-adapt its posture to environment changes. We introduced the strategy in the prosthesis rotation control to achieve compensatory reduction, as well as evaluated the system and its effects on the user. Methods: We conducted a non-randomized study involving eight prosthesis users to perform a bar relocation task with/without Tacit Learning System support. Hand piece and body motions were recorded continuously with goniometers, videos, and a motion-capture system. Findings: Reduction in the participants' upper extremity rotatory compensation motion was monitored during the relocation task in all participants. The estimated profile of total body energy consumption improved in five out of six participants. Interpretation: Our system rapidly accomplished nearly natural motion without unexpected errors. The Tacit Learning System not only adapts human motions but also enhances the human ability to adapt to the system quickly, while the system amplifies compensation generated by the residual limb. The concept can be extended to various situations for reconstructing lost functions that can be compensated.

Real-time and simultaneous control of artificial limbs based on pattern recognition algorithms.

PubMed

Ortiz-Catalan, Max; Håkansson, Bo; Brånemark, Rickard

2014-07-01

The prediction of simultaneous limb motions is a highly desirable feature for the control of artificial limbs. In this work, we investigate different classification strategies for individual and simultaneous movements based on pattern recognition of myoelectric signals. Our results suggest that any classifier can be potentially employed in the prediction of simultaneous movements if arranged in a distributed topology. On the other hand, classifiers inherently capable of simultaneous predictions, such as the multi-layer perceptron (MLP), were found to be more cost effective, as they can be successfully employed in their simplest form. In the prediction of individual movements, the one-vs-one (OVO) topology was found to improve classification accuracy across different classifiers and it was therefore used to benchmark the benefits of simultaneous control. As opposed to previous work reporting only offline accuracy, the classification performance and the resulting controllability are evaluated in real time using the motion test and target achievement control (TAC) test, respectively. We propose a simultaneous classification strategy based on MLP that outperformed a top classifier for individual movements (LDA-OVO), thus improving the state-of-the-art classification approach. Furthermore, all the presented classification strategies and data collected in this study are freely available in BioPatRec, an open source platform for the development of advanced prosthetic control strategies.

Wavelets for sign language translation

NASA Astrophysics Data System (ADS)

Wilson, Beth J.; Anspach, Gretel

1993-10-01

Wavelet techniques are applied to help extract the relevant parameters of sign language from video images of a person communicating in American Sign Language or Signed English. The compression and edge detection features of two-dimensional wavelet analysis are exploited to enhance the algorithms under development to classify the hand motion, hand location with respect to the body, and handshape. These three parameters have different processing requirements and complexity issues. The results are described for applying various quadrature mirror filter designs to a filterbank implementation of the desired wavelet transform. The overall project is to develop a system that will translate sign language to English to facilitate communication between deaf and hearing people.

Influence of upper limb disability, manual dexterity and fine motor skill on general self-efficacy in institutionalized elderly with osteoarthritis.

PubMed

Pérez-Mármol, Jose Manuel; Ortega-Valdivieso, María Azucena; Cano-Deltell, Enrique Elías; Peralta-Ramírez, María Isabel; García-Ríos, M Carmen; Aguilar-Ferrándiz, María Encarnación

2016-01-01

Descriptive, cross-sectional. The impact of upper limb (UL) disability, dexterity and fine motor skill on self-efficacy in older adults with osteoarthritis (OA) is not well known yet. To evaluate the self-efficacy and its relationship with UL function/disability in institutionalized OA. Institutionalized adults (n = 45) over the age of 65 years with OA were evaluated in a single session, to determine pinch strength, active range of motion of the hand and UL disability and functionality. They were classified as self-efficacious or not based on their general self-efficacy level. The influence on self-efficacy on upper limb function was statistically analyzed using bivariate and multivariate regression analyses. Self-effective older adults showed significantly lower scores in disability and higher scores in pinch strength, dexterity and motion of thumb than those who were classified as non-self-effective. Self-efficacy was associated with pinch strength (p ≤ 0.038), disability (p < 0.001) and dexterity (p ≤ 0.048). Multiple regression analyses showed that disability explained almost 40% of the variability of self-efficacy. Older adults classified as non-self-effective have higher UL disability and less pinch strength, manual dexterity and thumb motion than those who are self-effective, suggesting a relationship between impairment and perceived ability. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

EEG classification for motor imagery and resting state in BCI applications using multi-class Adaboost extreme learning machine

NASA Astrophysics Data System (ADS)

Gao, Lin; Cheng, Wei; Zhang, Jinhua; Wang, Jue

2016-08-01

Brain-computer interface (BCI) systems provide an alternative communication and control approach for people with limited motor function. Therefore, the feature extraction and classification approach should differentiate the relative unusual state of motion intention from a common resting state. In this paper, we sought a novel approach for multi-class classification in BCI applications. We collected electroencephalographic (EEG) signals registered by electrodes placed over the scalp during left hand motor imagery, right hand motor imagery, and resting state for ten healthy human subjects. We proposed using the Kolmogorov complexity (Kc) for feature extraction and a multi-class Adaboost classifier with extreme learning machine as base classifier for classification, in order to classify the three-class EEG samples. An average classification accuracy of 79.5% was obtained for ten subjects, which greatly outperformed commonly used approaches. Thus, it is concluded that the proposed method could improve the performance for classification of motor imagery tasks for multi-class samples. It could be applied in further studies to generate the control commands to initiate the movement of a robotic exoskeleton or orthosis, which finally facilitates the rehabilitation of disabled people.

A comparative study of surface EMG classification by fuzzy relevance vector machine and fuzzy support vector machine.

PubMed

Xie, Hong-Bo; Huang, Hu; Wu, Jianhua; Liu, Lei

2015-02-01

We present a multiclass fuzzy relevance vector machine (FRVM) learning mechanism and evaluate its performance to classify multiple hand motions using surface electromyographic (sEMG) signals. The relevance vector machine (RVM) is a sparse Bayesian kernel method which avoids some limitations of the support vector machine (SVM). However, RVM still suffers the difficulty of possible unclassifiable regions in multiclass problems. We propose two fuzzy membership function-based FRVM algorithms to solve such problems, based on experiments conducted on seven healthy subjects and two amputees with six hand motions. Two feature sets, namely, AR model coefficients and room mean square value (AR-RMS), and wavelet transform (WT) features, are extracted from the recorded sEMG signals. Fuzzy support vector machine (FSVM) analysis was also conducted for wide comparison in terms of accuracy, sparsity, training and testing time, as well as the effect of training sample sizes. FRVM yielded comparable classification accuracy with dramatically fewer support vectors in comparison with FSVM. Furthermore, the processing delay of FRVM was much less than that of FSVM, whilst training time of FSVM much faster than FRVM. The results indicate that FRVM classifier trained using sufficient samples can achieve comparable generalization capability as FSVM with significant sparsity in multi-channel sEMG classification, which is more suitable for sEMG-based real-time control applications.

Analysis and Visualization of 3D Motion Data for UPDRS Rating of Patients with Parkinson's Disease.

PubMed

Piro, Neltje E; Piro, Lennart K; Kassubek, Jan; Blechschmidt-Trapp, Ronald A

2016-06-21

Remote monitoring of Parkinson's Disease (PD) patients with inertia sensors is a relevant method for a better assessment of symptoms. We present a new approach for symptom quantification based on motion data: the automatic Unified Parkinson Disease Rating Scale (UPDRS) classification in combination with an animated 3D avatar giving the neurologist the impression of having the patient live in front of him. In this study we compared the UPDRS ratings of the pronation-supination task derived from: (a) an examination based on video recordings as a clinical reference; (b) an automatically classified UPDRS; and (c) a UPDRS rating from the assessment of the animated 3D avatar. Data were recorded using Magnetic, Angular Rate, Gravity (MARG) sensors with 15 subjects performing a pronation-supination movement of the hand. After preprocessing, the data were classified with a J48 classifier and animated as a 3D avatar. Video recording of the movements, as well as the 3D avatar, were examined by movement disorder specialists and rated by UPDRS. The mean agreement between the ratings based on video and (b) the automatically classified UPDRS is 0.48 and with (c) the 3D avatar it is 0.47. The 3D avatar is similarly suitable for assessing the UPDRS as video recordings for the examined task and will be further developed by the research team.

Classifying Motion.

ERIC Educational Resources Information Center

Duzen, Carl; And Others

1992-01-01

Presents a series of activities that utilizes a leveling device to classify constant and accelerated motion. Applies this classification system to uniform circular motion and motion produced by gravitational force. (MDH)

Function in patients with cervical radiculopathy or chronic whiplash-associated disorders compared with healthy volunteers.

PubMed

Peolsson, Anneli; Ludvigsson, Maria Landén; Wibault, Johanna; Dedering, Åsa; Peterson, Gunnel

2014-05-01

The purposes of this study were to examine whether any differences in function and health exist between patients with cervical radiculopathy (CR) due to disk disease scheduled for surgery and patients with chronic whiplash-associated disorders (WADs) and to compare measures of patients' physical function with those obtained from healthy volunteers. This is a cross-sectional study of patients with CR (n = 198) and patients with chronic WAD (n = 215). Patient data were compared with raw data previously obtained from healthy people. Physical measures included cervical active range of motion, neck muscle endurance, and hand grip strength. Self-rated measures included pain intensity (visual analog scale), neck disability (Neck Disability Index), self-efficacy (Self-Efficacy Scale), and health-related quality of life (EuroQol 5-dimensional self-classifier). Patient groups exhibited significantly lower performance than the healthy group in all physical measures (P < .0005) except for neck muscle endurance in flexion for women (P > .09). There was a general trend toward worse results in the CR group than the WAD group, with significant differences in neck active range of motion, left hand strength for women, pain intensity, Neck Disability Index, EuroQol 5-dimensional self-classifier, and Self-Efficacy Scale (P < .0001). Patients had worse values than healthy individuals in almost all physical measures. There was a trend toward worse results for CR than WAD patients. Copyright © 2014 National University of Health Sciences. Published by Mosby, Inc. All rights reserved.

Study of recognizing multiple persons' complicated hand gestures from the video sequence acquired by a moving camera

NASA Astrophysics Data System (ADS)

Dan, Luo; Ohya, Jun

2010-02-01

Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.

Development of virtual reality exercise of hand motion assist robot for rehabilitation therapy by patient self-motion control.

PubMed

Ueki, Satoshi; Nishimoto, Yutaka; Abe, Motoyuki; Kawasaki, Haruhisa; Ito, Satoshi; Ishigure, Yasuhiko; Mizumoto, Jun; Ojika, Takeo

2008-01-01

This paper presents a virtual reality-enhanced hand rehabilitation support system with a symmetric master-slave motion assistant for independent rehabilitation therapies. Our aim is to provide fine motion exercise for a hand and fingers, which allows the impaired hand of a patient to be driven by his or her healthy hand on the opposite side. Since most disabilities caused by cerebral vascular accidents or bone fractures are hemiplegic, we adopted a symmetric master-slave motion assistant system in which the impaired hand is driven by the healthy hand on the opposite side. A VR environment displaying an effective exercise was created in consideration of system's characteristic. To verify the effectiveness of this system, a clinical test was executed by applying to six patients.

An Activity Recognition Framework Deploying the Random Forest Classifier and A Single Optical Heart Rate Monitoring and Triaxial AccelerometerWrist-Band.

PubMed

Mehrang, Saeed; Pietilä, Julia; Korhonen, Ilkka

2018-02-22

Wrist-worn sensors have better compliance for activity monitoring compared to hip, waist, ankle or chest positions. However, wrist-worn activity monitoring is challenging due to the wide degree of freedom for the hand movements, as well as similarity of hand movements in different activities such as varying intensities of cycling. To strengthen the ability of wrist-worn sensors in detecting human activities more accurately, motion signals can be complemented by physiological signals such as optical heart rate (HR) based on photoplethysmography. In this paper, an activity monitoring framework using an optical HR sensor and a triaxial wrist-worn accelerometer is presented. We investigated a range of daily life activities including sitting, standing, household activities and stationary cycling with two intensities. A random forest (RF) classifier was exploited to detect these activities based on the wrist motions and optical HR. The highest overall accuracy of 89.6 ± 3.9% was achieved with a forest of a size of 64 trees and 13-s signal segments with 90% overlap. Removing the HR-derived features decreased the classification accuracy of high-intensity cycling by almost 7%, but did not affect the classification accuracies of other activities. A feature reduction utilizing the feature importance scores of RF was also carried out and resulted in a shrunken feature set of only 21 features. The overall accuracy of the classification utilizing the shrunken feature set was 89.4 ± 4.2%, which is almost equivalent to the above-mentioned peak overall accuracy.

Smart Sensor-Based Motion Detection System for Hand Movement Training in Open Surgery.

PubMed

Sun, Xinyao; Byrns, Simon; Cheng, Irene; Zheng, Bin; Basu, Anup

2017-02-01

We introduce a smart sensor-based motion detection technique for objective measurement and assessment of surgical dexterity among users at different experience levels. The goal is to allow trainees to evaluate their performance based on a reference model shared through communication technology, e.g., the Internet, without the physical presence of an evaluating surgeon. While in the current implementation we used a Leap Motion Controller to obtain motion data for analysis, our technique can be applied to motion data captured by other smart sensors, e.g., OptiTrack. To differentiate motions captured from different participants, measurement and assessment in our approach are achieved using two strategies: (1) low level descriptive statistical analysis, and (2) Hidden Markov Model (HMM) classification. Based on our surgical knot tying task experiment, we can conclude that finger motions generated from users with different surgical dexterity, e.g., expert and novice performers, display differences in path length, number of movements and task completion time. In order to validate the discriminatory ability of HMM for classifying different movement patterns, a non-surgical task was included in our analysis. Experimental results demonstrate that our approach had 100 % accuracy in discriminating between expert and novice performances. Our proposed motion analysis technique applied to open surgical procedures is a promising step towards the development of objective computer-assisted assessment and training systems.

Sensing human hand motions for controlling dexterous robots

NASA Technical Reports Server (NTRS)

Marcus, Beth A.; Churchill, Philip J.; Little, Arthur D.

1988-01-01

The Dexterous Hand Master (DHM) system is designed to control dexterous robot hands such as the UTAH/MIT and Stanford/JPL hands. It is the first commercially available device which makes it possible to accurately and confortably track the complex motion of the human finger joints. The DHM is adaptable to a wide variety of human hand sizes and shapes, throughout their full range of motion.

Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method

PubMed Central

Wang, Hai-peng; Bi, Zheng-yang; Zhou, Yang; Zhou, Yu-xuan; Wang, Zhi-gong; Lv, Xiao-ying

2017-01-01

Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy. A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method. Through a series of novel design concepts, including the integration of a detecting circuit and an analog-to-digital converter, a miniaturized functional electrical stimulation circuit technique, a low-power super-regeneration chip for wireless receiving, and two wearable armbands, a prototype system has been established with reduced size, power, and overall cost. Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects, the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy. Test results showed that wrist flexion/extension, hand grasp, and finger extension could be reproduced with high accuracy and low latency. This system can build a bridge of information transmission between healthy limbs and paralyzed limbs, effectively improve voluntary participation of hemiplegic patients, and elevate efficiency of rehabilitation training. PMID:28250759

Osteosynthesis using plates and screws after removing a limited area of the periosteum in order to reduce misclassified during radiological assessment metacarpal shaft fractures

PubMed Central

Neagu, TP; Popescu, SA; Cobilinschi, C; Tincu, R; Tiglis, M; Lascar, I

2016-01-01

Hand fractures are one of the most common causes for presenting to the emergency room. Metacarpal fractures count about 18 to 44% of all hand fractures, and are most often standalone closed injuries, without misplacement, not needing operative treatment. We present a case in which osteosynthesis with plates and screws was used to reduce two metacarpal fractures in order to allow an early motion recovery, despite the fact that a small portion of the periosteum needed to be removed. The type of fractures were misclassified according to the radiological findings, therefore the correct diagnosis was established during surgery. The results according to the radiological aspects and to the DASH score were excellent with 95% function recovery at twelve months. In this case, the use of osteosynthesis with plates and screws led to a good fracture healing without any major complications. However, there are a series of complications related to this method that should be taken into consideration. Being misled by the radiological aspects of the fractures, the most certain way to classify a metacarpal shaft fracture is through exploratory surgery, even if in most of the cases the three radiological views are enough to establish the diagnosis. Abbreviations: DASH score = Disability of Arm, Shoulder and Hand score, TAM = Total Active Motion, MCP = metacarpal phalangeal joint, PIP = proximal inter phalangeal joint PMID:27974942

Multimodal 2D Brain Computer Interface.

PubMed

Almajidy, Rand K; Boudria, Yacine; Hofmann, Ulrich G; Besio, Walter; Mankodiya, Kunal

2015-08-01

In this work we used multimodal, non-invasive brain signal recording systems, namely Near Infrared Spectroscopy (NIRS), disc electrode electroencephalography (EEG) and tripolar concentric ring electrodes (TCRE) electroencephalography (tEEG). 7 healthy subjects participated in our experiments to control a 2-D Brain Computer Interface (BCI). Four motor imagery task were performed, imagery motion of the left hand, the right hand, both hands and both feet. The signal slope (SS) of the change in oxygenated hemoglobin concentration measured by NIRS was used for feature extraction while the power spectrum density (PSD) of both EEG and tEEG in the frequency band 8-30Hz was used for feature extraction. Linear Discriminant Analysis (LDA) was used to classify different combinations of the aforementioned features. The highest classification accuracy (85.2%) was achieved by using features from all the three brain signals recording modules. The improvement in classification accuracy was highly significant (p = 0.0033) when using the multimodal signals features as compared to pure EEG features.

Robust Real-Time and Rotation-Invariant American Sign Language Alphabet Recognition Using Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2012-07-01

The automatic interpretation of human gestures can be used for a natural interaction with computers without the use of mechanical devices such as keyboards and mice. The recognition of hand postures have been studied for many years. However, most of the literature in this area has considered 2D images which cannot provide a full description of the hand gestures. In addition, a rotation-invariant identification remains an unsolved problem even with the use of 2D images. The objective of the current study is to design a rotation-invariant recognition process while using a 3D signature for classifying hand postures. An heuristic and voxelbased signature has been designed and implemented. The tracking of the hand motion is achieved with the Kalman filter. A unique training image per posture is used in the supervised classification. The designed recognition process and the tracking procedure have been successfully evaluated. This study has demonstrated the efficiency of the proposed rotation invariant 3D hand posture signature which leads to 98.24% recognition rate after testing 12723 samples of 12 gestures taken from the alphabet of the American Sign Language.

The effect of concurrent hand movement on estimated time to contact in a prediction motion task.

PubMed

Zheng, Ran; Maraj, Brian K V

2018-04-27

In many activities, we need to predict the arrival of an occluded object. This action is called prediction motion or motion extrapolation. Previous researchers have found that both eye tracking and the internal clocking model are involved in the prediction motion task. Additionally, it is reported that concurrent hand movement facilitates the eye tracking of an externally generated target in a tracking task, even if the target is occluded. The present study examined the effect of concurrent hand movement on the estimated time to contact in a prediction motion task. We found different (accurate/inaccurate) concurrent hand movements had the opposite effect on the eye tracking accuracy and estimated TTC in the prediction motion task. That is, the accurate concurrent hand tracking enhanced eye tracking accuracy and had the trend to increase the precision of estimated TTC, but the inaccurate concurrent hand tracking decreased eye tracking accuracy and disrupted estimated TTC. However, eye tracking accuracy does not determine the precision of estimated TTC.

Evaluation of Hands-On Clinical Exam Performance Using Marker-less Video Tracking.

PubMed

Azari, David; Pugh, Carla; Laufer, Shlomi; Cohen, Elaine; Kwan, Calvin; Chen, Chia-Hsiung Eric; Yen, Thomas Y; Hu, Yu Hen; Radwin, Robert

2014-09-01

This study investigates the potential of using marker-less video tracking of the hands for evaluating hands-on clinical skills. Experienced family practitioners attending a national conference were recruited and asked to conduct a breast examination on a simulator that simulates different clinical presentations. Videos were made of the clinician's hands during the exam and video processing software for tracking hand motion to quantify hand motion kinematics was used. Practitioner motion patterns indicated consistent behavior of participants across multiple pathologies. Different pathologies exhibited characteristic motion patterns in the aggregate at specific parts of an exam, indicating consistent inter-participant behavior. Marker-less video kinematic tracking therefore shows promise in discriminating between different examination procedures, clinicians, and pathologies.

Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors.

PubMed

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J M

2016-03-24

The position of on-body motion sensors plays an important role in human activity recognition. Most often, mobile phone sensors at the trouser pocket or an equivalent position are used for this purpose. However, this position is not suitable for recognizing activities that involve hand gestures, such as smoking, eating, drinking coffee and giving a talk. To recognize such activities, wrist-worn motion sensors are used. However, these two positions are mainly used in isolation. To use richer context information, we evaluate three motion sensors (accelerometer, gyroscope and linear acceleration sensor) at both wrist and pocket positions. Using three classifiers, we show that the combination of these two positions outperforms the wrist position alone, mainly at smaller segmentation windows. Another problem is that less-repetitive activities, such as smoking, eating, giving a talk and drinking coffee, cannot be recognized easily at smaller segmentation windows unlike repetitive activities, like walking, jogging and biking. For this purpose, we evaluate the effect of seven window sizes (2-30 s) on thirteen activities and show how increasing window size affects these various activities in different ways. We also propose various optimizations to further improve the recognition of these activities. For reproducibility, we make our dataset publicly available.

Data trove helps pin down the shape of the Milky Way

NASA Astrophysics Data System (ADS)

Clery, Daniel

2018-04-01

On 25 April, hundreds of astronomers around the world got their hands on one of the biggest data dumps in the history of astronomy: the exact positions, motions, brightnesses, and colors of 1.3 billion stars in and around the Milky Way, gathered during the first 2 years of operation by the European Space Agency's €750 million Gaia satellite, launched in 2013. The data—Gaia's second release—will fuel an explosion of studies about the structure of the Milky Way. The trove of stellar positions from Gaia will sharpen our picture of the galaxy's spiral structures, and the data on stellar motions will allow astronomers to wind the clock backward and see how the galaxy evolved over the past 13 billion years. Gaia's color and brightness information, meanwhile, will help astronomers classify stars by composition and pin down where different types are born.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy.

PubMed

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

2014-10-01

Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images.

Motion tracking and electromyography-assisted identification of mirror hand contributions to functional near-infrared spectroscopy images acquired during a finger-tapping task performed by children with cerebral palsy

PubMed Central

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

2014-01-01

Abstract. Recent studies have demonstrated functional near-infrared spectroscopy (fNIRS) to be a viable and sensitive method for imaging sensorimotor cortex activity in children with cerebral palsy (CP). However, during unilateral finger tapping, children with CP often exhibit unintended motions in the nontapping hand, known as mirror motions, which confuse the interpretation of resulting fNIRS images. This work presents a method for separating some of the mirror motion contributions to fNIRS images and demonstrates its application to fNIRS data from four children with CP performing a finger-tapping task with mirror motions. Finger motion and arm muscle activity were measured simultaneously with fNIRS signals using motion tracking and electromyography (EMG), respectively. Subsequently, subject-specific regressors were created from the motion capture or EMG data and independent component analysis was combined with a general linear model to create an fNIRS image representing activation due to the tapping hand and one image representing activation due to the mirror hand. The proposed method can provide information on how mirror motions contribute to fNIRS images, and in some cases, it helps remove mirror motion contamination from the tapping hand activation images. PMID:26157980

Sensing and Force-Feedback Exoskeleton (SAFE) Robotic Glove.

PubMed

Ben-Tzvi, Pinhas; Ma, Zhou

2015-11-01

This paper presents the design, implementation and experimental validation of a novel robotic haptic exoskeleton device to measure the user's hand motion and assist hand motion while remaining portable and lightweight. The device consists of a five-finger mechanism actuated with miniature DC motors through antagonistically routed cables at each finger, which act as both active and passive force actuators. The SAFE Glove is a wireless and self-contained mechatronic system that mounts over the dorsum of a bare hand and provides haptic force feedback to each finger. The glove is adaptable to a wide variety of finger sizes without constraining the range of motion. This makes it possible to accurately and comfortably track the complex motion of the finger and thumb joints associated with common movements of hand functions, including grip and release patterns. The glove can be wirelessly linked to a computer for displaying and recording the hand status through 3D Graphical User Interface (GUI) in real-time. The experimental results demonstrate that the SAFE Glove is capable of reliably modeling hand kinematics, measuring finger motion and assisting hand grasping motion. Simulation and experimental results show the potential of the proposed system in rehabilitation therapy and virtual reality applications.

Hand motion modeling for psychology analysis in job interview using optical flow-history motion image: OF-HMI

NASA Astrophysics Data System (ADS)

Khalifa, Intissar; Ejbali, Ridha; Zaied, Mourad

2018-04-01

To survive the competition, companies always think about having the best employees. The selection is depended on the answers to the questions of the interviewer and the behavior of the candidate during the interview session. The study of this behavior is always based on a psychological analysis of the movements accompanying the answers and discussions. Few techniques are proposed until today to analyze automatically candidate's non verbal behavior. This paper is a part of a work psychology recognition system; it concentrates in spontaneous hand gesture which is very significant in interviews according to psychologists. We propose motion history representation of hand based on an hybrid approach that merges optical flow and history motion images. The optical flow technique is used firstly to detect hand motions in each frame of a video sequence. Secondly, we use the history motion images (HMI) to accumulate the output of the optical flow in order to have finally a good representation of the hand`s local movement in a global temporal template.

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

PubMed

Rantalainen, Timo; Chivers, Paola; Beck, Belinda R; Robertson, Sam; Hart, Nicolas H; Nimphius, Sophia; Weeks, Benjamin K; McIntyre, Fleur; Hands, Beth; Siafarikas, Aris

Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual inspection) and objective assessments of the scans. However, previously reported objective methods either cannot be applied on the reconstructed image or have not been tested for distal bone sites. Therefore, the purpose of the present study was to develop and validate motion artifact classifiers to quantify motion artifact in pQCT scans. Whether textural features could provide adequate motion artifact classification performance in 2 adolescent datasets with pQCT scans from tibial and radial diaphyses and epiphyses was tested. The first dataset was split into training (66% of sample) and validation (33% of sample) datasets. Visual classification was used as the ground truth. Moderate to substantial classification performance (J48 classifier, kappa coefficients from 0.57 to 0.80) was observed in the validation dataset with the novel texture-based classifier. In applying the same classifier to the second cross-sectional dataset, a slight-to-fair (κ = 0.01-0.39) classification performance was observed. Overall, this novel textural analysis-based classifier provided a moderate-to-substantial classification of motion artifact when the classifier was specifically trained for the measurement device and population. Classification based on textural features may be used to prescreen obviously acceptable and unacceptable scans, with a subsequent human-operated visual classification of any remaining scans. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Inertial Sensor-Based Touch and Shake Metaphor for Expressive Control of 3D Virtual Avatars

PubMed Central

Patil, Shashidhar; Chintalapalli, Harinadha Reddy; Kim, Dubeom; Chai, Youngho

2015-01-01

In this paper, we present an inertial sensor-based touch and shake metaphor for expressive control of a 3D virtual avatar in a virtual environment. An intuitive six degrees-of-freedom wireless inertial motion sensor is used as a gesture and motion control input device with a sensor fusion algorithm. The algorithm enables user hand motions to be tracked in 3D space via magnetic, angular rate, and gravity sensors. A quaternion-based complementary filter is implemented to reduce noise and drift. An algorithm based on dynamic time-warping is developed for efficient recognition of dynamic hand gestures with real-time automatic hand gesture segmentation. Our approach enables the recognition of gestures and estimates gesture variations for continuous interaction. We demonstrate the gesture expressivity using an interactive flexible gesture mapping interface for authoring and controlling a 3D virtual avatar and its motion by tracking user dynamic hand gestures. This synthesizes stylistic variations in a 3D virtual avatar, producing motions that are not present in the motion database using hand gesture sequences from a single inertial motion sensor. PMID:26094629

Contributions of muscle imbalance and impaired growth to postural and osseous shoulder deformity following brachial plexus birth palsy: a computational simulation analysis.

PubMed

Cheng, Wei; Cornwall, Roger; Crouch, Dustin L; Li, Zhongyu; Saul, Katherine R

2015-06-01

Two potential mechanisms leading to postural and osseous shoulder deformity after brachial plexus birth palsy are muscle imbalance between functioning internal rotators and paralyzed external rotators and impaired longitudinal growth of paralyzed muscles. Our goal was to evaluate the combined and isolated effects of these 2 mechanisms on transverse plane shoulder forces using a computational model of C5-6 brachial plexus injury. We modeled a C5-6 injury using a computational musculoskeletal upper limb model. Muscles expected to be denervated by C5-6 injury were classified as affected, with the remaining shoulder muscles classified as unaffected. To model muscle imbalance, affected muscles were given no resting tone whereas unaffected muscles were given resting tone at 30% of maximal activation. To model impaired growth, affected muscles were reduced in length by 30% compared with normal whereas unaffected muscles remained normal in length. Four scenarios were simulated: normal, muscle imbalance only, impaired growth only, and both muscle imbalance and impaired growth. Passive shoulder rotation range of motion and glenohumeral joint reaction forces were evaluated to assess postural and osseous deformity. All impaired scenarios exhibited restricted range of motion and increased and posteriorly directed compressive glenohumeral joint forces. Individually, impaired muscle growth caused worse restriction in range of motion and higher and more posteriorly directed glenohumeral forces than did muscle imbalance. Combined muscle imbalance and impaired growth caused the most restricted joint range of motion and the highest joint reaction force of all scenarios. Both muscle imbalance and impaired longitudinal growth contributed to range of motion and force changes consistent with clinically observed deformity, although the most substantial effects resulted from impaired muscle growth. Simulations suggest that treatment strategies emphasizing treatment of impaired longitudinal growth are warranted for reducing deformity after brachial plexus birth palsy. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

A simulation trainer for complex articular fracture surgery.

PubMed

Yehyawi, Tameem M; Thomas, Thaddeus P; Ohrt, Gary T; Marsh, J Lawrence; Karam, Matthew D; Brown, Thomas D; Anderson, Donald D

2013-07-03

The purposes of this study were (1) to develop a physical model to improve articular fracture reduction skills, (2) to develop objective assessment methods to evaluate these skills, and (3) to assess the construct validity of the simulation. A surgical simulation was staged utilizing surrogate tibial plafond fractures. Multiple three-segment radio-opacified polyurethane foam fracture models were produced from the same mold, ensuring uniform surgical complexity between trials. Using fluoroscopic guidance, five senior and seven junior orthopaedic residents reduced the fracture through a limited anterior window. The residents were assessed on the basis of time to completion, hand movements (tracked with use of a motion capture system), and quality of the obtained reduction. All but three of the residents successfully reduced and fixed the fracture fragments (one senior resident and two junior residents completed the reduction but were unsuccessful in fixating all fragments). Senior residents had an average time to completion of 13.43 minutes, an average gross articular step-off of 3.00 mm, discrete hand motions of 540 actions, and a cumulative hand motion distance of 79 m. Junior residents had an average time to completion of 14.75 minutes, an average gross articular step-off of 3.09 mm, discrete hand motions of 511 actions, and a cumulative hand motion distance of 390 m. The large difference in cumulative hand motion distance, despite comparable numbers of discrete hand motion events, indicates that senior residents were more precise in their hand motions. The present experiment establishes the basic construct validity of the simulation trainer. Further studies are required to demonstrate that this laboratory-based model for articular fracture reduction training, along with an objective assessment of performance, can be used to improve resident surgical skills.

Design of a wearable hand exoskeleton for exercising flexion/extension of the fingers.

PubMed

Jo, Inseong; Lee, Jeongsoo; Park, Yeongyu; Bae, Joonbum

2017-07-01

In this paper, design of a wearable hand exoskeleton system for exercising flexion/extension of the fingers, is proposed. The exoskeleton was designed with a simple and wearable structure to aid finger motions in 1 degree of freedom (DOF). A hand grasping experiment by fully-abled people was performed to investigate general hand flexion/extension motions and the polynomial curve of general hand motions was obtained. To customize the hand exoskeleton for the user, the polynomial curve was adjusted to the joint range of motion (ROM) of the user and the optimal design of the exoskeleton structure was obtained using the optimization algorithm. A prototype divided into two parts (one part for the thumb, the other for rest fingers) was actuated by only two linear motors for compact size and light weight.

Biological Nanomotors with a Revolution, Linear, or Rotation Motion Mechanism

PubMed Central

Noji, Hiroyuki; Yengo, Christopher M.; Zhao, Zhengyi; Grainge, Ian

2016-01-01

SUMMARY The ubiquitous biological nanomotors were classified into two categories in the past: linear and rotation motors. In 2013, a third type of biomotor, revolution without rotation (http://rnanano.osu.edu/movie.html), was discovered and found to be widespread among bacteria, eukaryotic viruses, and double-stranded DNA (dsDNA) bacteriophages. This review focuses on recent findings about various aspects of motors, including chirality, stoichiometry, channel size, entropy, conformational change, and energy usage rate, in a variety of well-studied motors, including FoF1 ATPase, helicases, viral dsDNA-packaging motors, bacterial chromosome translocases, myosin, kinesin, and dynein. In particular, dsDNA translocases are used to illustrate how these features relate to the motion mechanism and how nature elegantly evolved a revolution mechanism to avoid coiling and tangling during lengthy dsDNA genome transportation in cell division. Motor chirality and channel size are two factors that distinguish rotation motors from revolution motors. Rotation motors use right-handed channels to drive the right-handed dsDNA, similar to the way a nut drives the bolt with threads in same orientation; revolution motors use left-handed motor channels to revolve the right-handed dsDNA. Rotation motors use small channels (<2 nm in diameter) for the close contact of the channel wall with single-stranded DNA (ssDNA) or the 2-nm dsDNA bolt; revolution motors use larger channels (>3 nm) with room for the bolt to revolve. Binding and hydrolysis of ATP are linked to different conformational entropy changes in the motor that lead to altered affinity for the substrate and allow work to be done, for example, helicase unwinding of DNA or translocase directional movement of DNA. PMID:26819321

Classifiers in ASL: A Manual for Instructors. American Sign Language Community College Network.

ERIC Educational Resources Information Center

Peralta Community Coll. System, Berkeley, CA. Vista Coll.

Following a discussion of the role of classifiers (i.e., verbs of motion and location) in American Sign Language, this manual presents a six-unit program designed to teach students to produce sentences with classifiers. First, an overview is provided of the hierarchy of verbs of motion and location produced when the resources of the body are…

Multidigit movement synergies of the human hand in an unconstrained haptic exploration task.

PubMed

Thakur, Pramodsingh H; Bastian, Amy J; Hsiao, Steven S

2008-02-06

Although the human hand has a complex structure with many individual degrees of freedom, joint movements are correlated. Studies involving simple tasks (grasping) or skilled tasks (typing or finger spelling) have shown that a small number of combined joint motions (i.e., synergies) can account for most of the variance in observed hand postures. However, those paradigms evoked a limited set of hand postures and as such the reported correlation patterns of joint motions may be task-specific. Here, we used an unconstrained haptic exploration task to evoke a set of hand postures that is representative of most naturalistic postures during object manipulation. Principal component analysis on this set revealed that the first seven principal components capture >90% of the observed variance in hand postures. Further, we identified nine eigenvectors (or synergies) that are remarkably similar across multiple subjects and across manipulations of different sets of objects within a subject. We then determined that these synergies are used broadly by showing that they account for the changes in hand postures during other tasks. These include hand motions such as reach and grasp of objects that vary in width, curvature and angle, and skilled motions such as precision pinch. Our results demonstrate that the synergies reported here generalize across tasks, and suggest that they represent basic building blocks underlying natural human hand motions.

Training industrial robots with gesture recognition techniques

NASA Astrophysics Data System (ADS)

Piane, Jennifer; Raicu, Daniela; Furst, Jacob

2013-01-01

In this paper we propose to use gesture recognition approaches to track a human hand in 3D space and, without the use of special clothing or markers, be able to accurately generate code for training an industrial robot to perform the same motion. The proposed hand tracking component includes three methods: a color-thresholding model, naïve Bayes analysis and Support Vector Machine (SVM) to detect the human hand. Next, it performs stereo matching on the region where the hand was detected to find relative 3D coordinates. The list of coordinates returned is expectedly noisy due to the way the human hand can alter its apparent shape while moving, the inconsistencies in human motion and detection failures in the cluttered environment. Therefore, the system analyzes the list of coordinates to determine a path for the robot to move, by smoothing the data to reduce noise and looking for significant points used to determine the path the robot will ultimately take. The proposed system was applied to pairs of videos recording the motion of a human hand in a „real‟ environment to move the end-affector of a SCARA robot along the same path as the hand of the person in the video. The correctness of the robot motion was determined by observers indicating that motion of the robot appeared to match the motion of the video.

The Application of Leap Motion in Astronaut Virtual Training

NASA Astrophysics Data System (ADS)

Qingchao, Xie; Jiangang, Chao

2017-03-01

With the development of computer vision, virtual reality has been applied in astronaut virtual training. As an advanced optic equipment to track hand, Leap Motion can provide precise and fluid tracking of hands. Leap Motion is suitable to be used as gesture input device in astronaut virtual training. This paper built an astronaut virtual training based Leap Motion, and established the mathematics model of hands occlusion. At last the ability of Leap Motion to handle occlusion was analysed. A virtual assembly simulation platform was developed for astronaut training, and occlusion gesture would influence the recognition process. The experimental result can guide astronaut virtual training.

Complex Human Activity Recognition Using Smartphone and Wrist-Worn Motion Sensors

PubMed Central

Shoaib, Muhammad; Bosch, Stephan; Incel, Ozlem Durmaz; Scholten, Hans; Havinga, Paul J. M.

2016-01-01

The position of on-body motion sensors plays an important role in human activity recognition. Most often, mobile phone sensors at the trouser pocket or an equivalent position are used for this purpose. However, this position is not suitable for recognizing activities that involve hand gestures, such as smoking, eating, drinking coffee and giving a talk. To recognize such activities, wrist-worn motion sensors are used. However, these two positions are mainly used in isolation. To use richer context information, we evaluate three motion sensors (accelerometer, gyroscope and linear acceleration sensor) at both wrist and pocket positions. Using three classifiers, we show that the combination of these two positions outperforms the wrist position alone, mainly at smaller segmentation windows. Another problem is that less-repetitive activities, such as smoking, eating, giving a talk and drinking coffee, cannot be recognized easily at smaller segmentation windows unlike repetitive activities, like walking, jogging and biking. For this purpose, we evaluate the effect of seven window sizes (2–30 s) on thirteen activities and show how increasing window size affects these various activities in different ways. We also propose various optimizations to further improve the recognition of these activities. For reproducibility, we make our dataset publicly available. PMID:27023543

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Real-time simulation of hand motion for prosthesis control

PubMed Central

Blana, Dimitra; Chadwick, Edward K.; van den Bogert, Antonie J.; Murray, Wendy M.

2016-01-01

Individuals with hand amputation suffer substantial loss of independence. Performance of sophisticated prostheses is limited by the ability to control them. To achieve natural and simultaneous control of all wrist and hand motions, we propose to use real-time biomechanical simulation to map between residual EMG and motions of the intact hand. Here we describe a musculoskeletal model of the hand using only extrinsic muscles to determine whether real-time performance is possible. Simulation is 1.3 times faster than real time, but the model is locally unstable. Methods are discussed to increase stability and make this approach suitable for prosthesis control. PMID:27868425

Hand motion segmentation against skin colour background in breast awareness applications.

PubMed

Hu, Yuqin; Naguib, Raouf N G; Todman, Alison G; Amin, Saad A; Al-Omishy, Hassanein; Oikonomou, Andreas; Tucker, Nick

2004-01-01

Skin colour modelling and classification play significant roles in face and hand detection, recognition and tracking. A hand is an essential tool used in breast self-examination, which needs to be detected and analysed during the process of breast palpation. However, the background of a woman's moving hand is her breast that has the same or similar colour as the hand. Additionally, colour images recorded by a web camera are strongly affected by the lighting or brightness conditions. Hence, it is a challenging task to segment and track the hand against the breast without utilising any artificial markers, such as coloured nail polish. In this paper, a two-dimensional Gaussian skin colour model is employed in a particular way to identify a breast but not a hand. First, an input image is transformed to YCbCr colour space, which is less sensitive to the lighting conditions and more tolerant of skin tone. The breast, thus detected by the Gaussian skin model, is used as the baseline or framework for the hand motion. Secondly, motion cues are used to segment the hand motion against the detected baseline. Desired segmentation results have been achieved and the robustness of this algorithm is demonstrated in this paper.

Development of a parametric kinematic model of the human hand and a novel robotic exoskeleton.

PubMed

Burton, T M W; Vaidyanathan, R; Burgess, S C; Turton, A J; Melhuish, C

2011-01-01

This paper reports the integration of a kinematic model of the human hand during cylindrical grasping, with specific focus on the accurate mapping of thumb movement during grasping motions, and a novel, multi-degree-of-freedom assistive exoskeleton mechanism based on this model. The model includes thumb maximum hyper-extension for grasping large objects (~> 50 mm). The exoskeleton includes a novel four-bar mechanism designed to reproduce natural thumb opposition and a novel synchro-motion pulley mechanism for coordinated finger motion. A computer aided design environment is used to allow the exoskeleton to be rapidly customized to the hand dimensions of a specific patient. Trials comparing the kinematic model to observed data of hand movement show the model to be capable of mapping thumb and finger joint flexion angles during grasping motions. Simulations show the exoskeleton to be capable of reproducing the complex motion of the thumb to oppose the fingers during cylindrical and pinch grip motions. © 2011 IEEE

Rhythmic ictal nonclonic hand (RINCH) motions in temporal lobe epilepsy: invasive EEG findings, incidence, and lateralizing value.

PubMed

Kuba, Robert; Musilová, Klára; Vojvodič, Nikola; Tyrlíková, Ivana; Rektor, Ivan; Brázdil, Milan

2013-10-01

The main purpose of this retrospective analysis was to evaluate the incidence and lateralization value of rhythmic ictal nonclonic hand (RINCH) motions in patients with temporal lobe epilepsy (TLE), who were classified as Engel I at least 2 years after epilepsy surgery. We analyzed the distribution of ictal activity at the time of RINCH appearance in patients in whom RINCH motions were present during invasive EEG monitoring. A group of 120 patients was included in this study. In total, we reviewed 491 seizures: 277 seizures in patients with temporal lobe epilepsy (TLE) associated with hippocampal sclerosis (TLE-HS group) and 214 in TLE caused by other lesions (TLE-OTH group). We analyzed 29 patients (79 of the seizures) during invasive EEG monitoring. Fisher's exact test and binomial test were used for the statistical analysis. RINCH motions were observed in 24 out of 120 patients (20%) and in 48 out of 491 seizures (9.8%). There was no significant difference between the occurrence of RINCH motions in patients with TLE-HS and in patients with TLE-OTH, or between gender, right/left-sided TLE, and language dominant/nondominant TLE. RINCH motions were contralateral to the seizure onset in 83.3% of patients and 91.7% of seizures (p=0.0015; p<0.001, respectively). There were no differences in the lateralizing value of RINCH motions in patients with TLE-HS or TLE-OTH. We analyzed RINCH motions in 5 patients/7 seizures during invasive EEG. In all 7 seizures with RINCH motions, we observed the widespread activation of the temporal lobe (mesial and lateral, opercular and polar regions) contralateral to the side of RINCH motions. In all 7 seizures, we observed that at the time of RINCH motion onset, at least 1 explored region of the frontal lobe was affected by the ictal activity. In 3 seizures, we observed time-locked epileptic activation associated with the appearance of RINCH motions, i.e., in the orbitofrontal cortex in 2 seizures and in both the orbitofrontal cortex and anterior cingulate gyrus in 1 seizure. RINCH motions are a relatively frequent ictal sign in patients with TLE. They have a high lateralizing value in these patients, occurring contralateral to the ictal onset. RINCH motions usually occur after the spread of ictal activity beyond the temporal lobe, and their appearance is usually associated with the presence of ictal activity in various regions of the contralateral frontal lobe, mainly the orbitofrontal cortex and anterior cingulate gyrus. This is the first study analysing this phenomenon during invasive EEG recording. Copyright © 2013 Elsevier B.V. All rights reserved.

An Architecture for Measuring Joint Angles Using a Long Period Fiber Grating-Based Sensor

PubMed Central

Perez-Ramirez, Carlos A.; Almanza-Ojeda, Dora L.; Guerrero-Tavares, Jesus N.; Mendoza-Galindo, Francisco J.; Estudillo-Ayala, Julian M.; Ibarra-Manzano, Mario A.

2014-01-01

The implementation of signal filters in a real-time form requires a tradeoff between computation resources and the system performance. Therefore, taking advantage of low lag response and the reduced consumption of resources, in this article, the Recursive Least Square (RLS) algorithm is used to filter a signal acquired from a fiber-optics-based sensor. In particular, a Long-Period Fiber Grating (LPFG) sensor is used to measure the bending movement of a finger. After that, the Gaussian Mixture Model (GMM) technique allows us to classify the corresponding finger position along the motion range. For these measures to help in the development of an autonomous robotic hand, the proposed technique can be straightforwardly implemented on real time platforms such as Field Programmable Gate Array (FPGA) or Digital Signal Processors (DSP). Different angle measurements of the finger's motion are carried out by the prototype and a detailed analysis of the system performance is presented. PMID:25536002

Involvement of the ventral premotor cortex in controlling image motion of the hand during performance of a target-capturing task.

PubMed

Ochiai, Tetsuji; Mushiake, Hajime; Tanji, Jun

2005-07-01

The ventral premotor cortex (PMv) has been implicated in the visual guidance of movement. To examine whether neuronal activity in the PMv is involved in controlling the direction of motion of a visual image of the hand or the actual movement of the hand, we trained a monkey to capture a target that was presented on a video display using the same side of its hand as was displayed on the video display. We found that PMv neurons predominantly exhibited premovement activity that reflected the image motion to be controlled, rather than the physical motion of the hand. We also found that the activity of half of such direction-selective PMv neurons depended on which side (left versus right) of the video image of the hand was used to capture the target. Furthermore, this selectivity for a portion of the hand was not affected by changing the starting position of the hand movement. These findings suggest that PMv neurons play a crucial role in determining which part of the body moves in which direction, at least under conditions in which a visual image of a limb is used to guide limb movements.

Using Fuzzy Gaussian Inference and Genetic Programming to Classify 3D Human Motions

NASA Astrophysics Data System (ADS)

Khoury, Mehdi; Liu, Honghai

This research introduces and builds on the concept of Fuzzy Gaussian Inference (FGI) (Khoury and Liu in Proceedings of UKCI, 2008 and IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS 2009), 2009) as a novel way to build Fuzzy Membership Functions that map to hidden Probability Distributions underlying human motions. This method is now combined with a Genetic Programming Fuzzy rule-based system in order to classify boxing moves from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven different boxing stances simultaneously with an accuracy superior to a GMM-based classifier. Results seem to indicate that adding an evolutionary Fuzzy Inference Engine on top of FGI improves the accuracy of the classifier in a consistent way.

Quantitative biomechanical analysis of wrist motion in bone-trimming jobs in the meat packing industry.

PubMed

Marklin, R W; Monroe, J F

1998-02-01

This study was motivated by the serious impact that cumulative trauma disorders (CTDs) of the upper extremities have on the meat packing industry. To date, no quantitative data have been gathered on the kinematics of hand and wrist motion required in bone-trimming jobs in the red-meat packing industry and how these motions are related to the risk of CTDs. The wrist motion of bone-trimming workers from a medium-sized plant was measured, and the kinematic data were compared to manufacturing industry's preliminary wrist motion benchmarks from industrial workers who performed hand-intensive, repetitive work in jobs that were of low and high risk of hand/wrist CTDs. Results of this comparison show that numerous wrist motion variables in both the left and right hands of bone-trimming workers are in the high-risk category. This quantitative analysis provides biomechanical support for the high incidence of CTDs in the meat packing industry. The research reported in this paper established a preliminary database of wrist and hand kinematics required in bone-trimming jobs in the red-meat packing industry. This kinematic database could augment the industry's efforts to reduce the severity and cost of CTDs. Ergonomics practitioners in the industry could use the kinematic methods employed in this research to assess the CTD risk of jobs that require repetitious, hand-intensive work.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2001-01-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Knowledge-based approach to video content classification

NASA Astrophysics Data System (ADS)

Chen, Yu; Wong, Edward K.

2000-12-01

A framework for video content classification using a knowledge-based approach is herein proposed. This approach is motivated by the fact that videos are rich in semantic contents, which can best be interpreted and analyzed by human experts. We demonstrate the concept by implementing a prototype video classification system using the rule-based programming language CLIPS 6.05. Knowledge for video classification is encoded as a set of rules in the rule base. The left-hand-sides of rules contain high level and low level features, while the right-hand-sides of rules contain intermediate results or conclusions. Our current implementation includes features computed from motion, color, and text extracted from video frames. Our current rule set allows us to classify input video into one of five classes: news, weather, reporting, commercial, basketball and football. We use MYCIN's inexact reasoning method for combining evidences, and to handle the uncertainties in the features and in the classification results. We obtained good results in a preliminary experiment, and it demonstrated the validity of the proposed approach.

Case Report: The casting motion to mobilize stiffness technique for rehabilitation after a crush and degloving injury of the hand.

PubMed

Midgley, Robyn

2016-01-01

Case report. This case report describes the use of the casting motion to mobilize stiffness (CMMS) technique in the management of a crush and degloving injury of the hand. The patient was unable to attend multiple hand therapy sessions due to geographic constraints. The CMMS technique involved the application of a nonremovable plaster of paris cast that selectively immobilizes proximal joints in an ideal position while constraining distal joints to direct desired motion over a long period. This uses active motion only. Traditional hand therapy techniques or modalities are not used. This treatment approach was beneficial to the patient as a minimum of 2 appointments per month were needed to regain functional hand use. To document the use of the CMMS technique as an effective treatment approach in the management of a crush and degloving injury of the hand. The CMMS technique was applied to the patient's left (nondominant) hand 8 weeks after injury. The technique's aim was to improve the 30° flexion deformity of the left wrist and flexion contractures of the index, middle, and ring fingers with a total active motion of 0°. Orthotic devices and traditional therapy were applied once joint stiffness was resolved, and a normal pattern of motion was reinstated. At 6 months, substantial improvement was noted in wrist as well as metacarpophalangeal and interphalangeal joints. Total active motion exceeded 170° in all fingers excellent functional outcome resulted as measured with the upper limb functional index short form-10. The upper limb functional index increased from 0% to 55% of preinjury status (or capacity) over the 18 months of therapy. Brief immobilization through casting causes certain functional losses, but these are temporary and reversible. Finger stiffness, edema, and tissue fibrosis were successfully managed with the CMMS technique without the need for attendance at multiple hand therapy sessions. Level V. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

EMG-based pattern recognition approach in post stroke robot-aided rehabilitation: a feasibility study

PubMed Central

2013-01-01

Background Several studies investigating the use of electromyographic (EMG) signals in robot-based stroke neuro-rehabilitation to enhance functional recovery. Here we explored whether a classical EMG-based patterns recognition approach could be employed to predict patients’ intentions while attempting to generate goal-directed movements in the horizontal plane. Methods Nine right-handed healthy subjects and seven right-handed stroke survivors performed reaching movements in the horizontal plane. EMG signals were recorded and used to identify the intended motion direction of the subjects. To this aim, a standard pattern recognition algorithm (i.e., Support Vector Machine, SVM) was used. Different tests were carried out to understand the role of the inter- and intra-subjects’ variability in affecting classifier accuracy. Abnormal muscular spatial patterns generating misclassification were evaluated by means of an assessment index calculated from the results achieved with the PCA, i.e., the so-called Coefficient of Expressiveness (CoE). Results Processing the EMG signals of the healthy subjects, in most of the cases we were able to build a static functional map of the EMG activation patterns for point-to-point reaching movements on the horizontal plane. On the contrary, when processing the EMG signals of the pathological subjects a good classification was not possible. In particular, patients’ aimed movement direction was not predictable with sufficient accuracy either when using the general map extracted from data of normal subjects and when tuning the classifier on the EMG signals recorded from each patient. Conclusions The experimental findings herein reported show that the use of EMG patterns recognition approach might not be practical to decode movement intention in subjects with neurological injury such as stroke. Rather than estimate motion from EMGs, future scenarios should encourage the utilization of these signals to detect and interpret the normal and abnormal muscle patterns and provide feedback on their correct recruitment. PMID:23855907

Intermittently-visual Tracking Experiments Reveal the Roles of Error-correction and Predictive Mechanisms in the Human Visual-motor Control System

NASA Astrophysics Data System (ADS)

Hayashi, Yoshikatsu; Tamura, Yurie; Sase, Kazuya; Sugawara, Ken; Sawada, Yasuji

Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

Identification of hand motion using background subtraction method and extraction of image binary with backpropagation neural network on skeleton model

NASA Astrophysics Data System (ADS)

Fauziah; Wibowo, E. P.; Madenda, S.; Hustinawati

2018-03-01

Capturing and recording motion in human is mostly done with the aim for sports, health, animation films, criminality, and robotic applications. In this study combined background subtraction and back propagation neural network. This purpose to produce, find similarity movement. The acquisition process using 8 MP resolution camera MP4 format, duration 48 seconds, 30frame/rate. video extracted produced 1444 pieces and results hand motion identification process. Phase of image processing performed is segmentation process, feature extraction, identification. Segmentation using bakground subtraction, extracted feature basically used to distinguish between one object to another object. Feature extraction performed by using motion based morfology analysis based on 7 invariant moment producing four different classes motion: no object, hand down, hand-to-side and hands-up. Identification process used to recognize of hand movement using seven inputs. Testing and training with a variety of parameters tested, it appears that architecture provides the highest accuracy in one hundred hidden neural network. The architecture is used propagate the input value of the system implementation process into the user interface. The result of the identification of the type of the human movement has been clone to produce the highest acuracy of 98.5447%. The training process is done to get the best results.

Unreal Interactive Puppet Game Development Using Leap Motion

NASA Astrophysics Data System (ADS)

Huang, An-Pin; Huang, Fay; Jhu, Jing-Siang

2018-04-01

This paper proposed a novel puppet play method utilizing recent technology. An interactive puppet game has been developed based on the theme of a famous Chinese classical novel. This project was implemented using Unreal Engine, which is a leading software of integrated tools for developers to design and build games. On the other hand, Leap Motion Controller is a sensor device for recognizing hand movements and gestures. It is commonly used in systems which require close-range finger-based user interaction. In order to manipulate puppets’ movements, the developed program employs the Leap Motion SDK, which provides a friendly way to add motion-controlled 3D hands to an Unreal game. The novelty of our project is to replace 3D model of rigged hands by two 3D humanoid rigged characters. The challenges of this task are two folds. First, the skeleton structure of a human hand and a humanoid character (i.e., puppets) are totally different. Making the puppets to follow the hand poses of the user and yet ensuring reasonable puppets’ movements has not been discussed in the literatures nor in the developer forums. Second, there are only a limited number of built-in recognizable hand gestures. More recognizable hand gestures need to be created for the interactive game. This paper reports the proposed solutions to these challenges.

Anthropomorphic Robot Hand And Teaching Glove

NASA Technical Reports Server (NTRS)

Engler, Charles D., Jr.

1991-01-01

Robotic forearm-and-hand assembly manipulates objects by performing wrist and hand motions with nearly human grasping ability and dexterity. Imitates hand motions of human operator who controls robot in real time by programming via exoskeletal "teaching glove". Telemanipulator systems based on this robotic-hand concept useful where humanlike dexterity required. Underwater, high-radiation, vacuum, hot, cold, toxic, or inhospitable environments potential application sites. Particularly suited to assisting astronauts on space station in safely executing unexpected tasks requiring greater dexterity than standard gripper.

Manual wheelchair propulsion patterns on natural surfaces during start-up propulsion.

PubMed

Koontz, Alicia M; Roche, Bailey M; Collinger, Jennifer L; Cooper, Rory A; Boninger, Michael L

2009-11-01

To classify propulsion patterns over surfaces encountered in the natural environment during start-up and compare selected biomechanical variables between pattern types. Case series. National Veterans Wheelchair Games, Minneapolis, MN, 2005. Manual wheelchair users (N=29). Subjects pushed their wheelchairs from a resting position over high-pile carpet, over linoleum, and up a ramp with a 5 degrees incline while propulsion kinematics and kinetics were recorded with a motion capture system and an instrumented wheel. Three raters classified the first 3 strokes as 1 of 4 types on each surface: arc, semicircular (SC), single looping over propulsion (SL), and double looping over propulsion (DL). The Fisher exact test was used to assess pattern changes between strokes and surface type. A multiple analysis of variance test was used to compare peak and average resultant force and moment about the hub, average wheel velocity, stroke frequency, contact angle, and distance traveled between stroke patterns. SL was the most common pattern used during start-up propulsion (44.9%), followed by arc (35.9%), DL (14.1%), and SC (5.1%). Subjects who dropped their hands below the rim during recovery achieved faster velocities and covered greater distances (.016< or =P< or =.075) during start-up on linoleum and carpet and applied more force during start-up on the ramp compared with those who used an arc pattern (P=.066). Classifying propulsion patterns is a difficult task that should use multiple raters. In addition, propulsion patterns change during start-up, with an arc pattern most prevalent initially. The biomechanical findings in this study agree with current clinical guidelines that recommend training users to drop the hand below the pushrim during recovery.

Deducing the reachable space from fingertip positions.

PubMed

Hai-Trieu Pham; Pathirana, Pubudu N

2015-01-01

The reachable space of the hand has received significant interests in the past from relevant medical researchers and health professionals. The reachable space was often computed from the joint angles acquired from a motion capture system such as gloves or markers attached to each bone of the finger. However, the contact between the hand and device can cause difficulties particularly for hand with injuries, burns or experiencing certain dermatological conditions. This paper introduces an approach to find the reachable space of the hand in a non-contact measurement form utilizing the Leap Motion Controller. The approach is based on the analysis of each position in the motion path of the fingertip acquired by the Leap Motion Controller. For each position of the fingertip, the inverse kinematic problem was solved under the physiological multiple constraints of the human hand to find a set of all possible configurations of three finger joints. Subsequently, all the sets are unified to form a set of all possible configurations specific for that motion. Finally, a reachable space is computed from the configuration corresponding to the complete extension and the complete flexion of the finger joint angles in this set.

Human motion retrieval from hand-drawn sketch.

PubMed

Chao, Min-Wen; Lin, Chao-Hung; Assa, Jackie; Lee, Tong-Yee

2012-05-01

The rapid growth of motion capture data increases the importance of motion retrieval. The majority of the existing motion retrieval approaches are based on a labor-intensive step in which the user browses and selects a desired query motion clip from the large motion clip database. In this work, a novel sketching interface for defining the query is presented. This simple approach allows users to define the required motion by sketching several motion strokes over a drawn character, which requires less effort and extends the users’ expressiveness. To support the real-time interface, a specialized encoding of the motions and the hand-drawn query is required. Here, we introduce a novel hierarchical encoding scheme based on a set of orthonormal spherical harmonic (SH) basis functions, which provides a compact representation, and avoids the CPU/processing intensive stage of temporal alignment used by previous solutions. Experimental results show that the proposed approach can well retrieve the motions, and is capable of retrieve logically and numerically similar motions, which is superior to previous approaches. The user study shows that the proposed system can be a useful tool to input motion query if the users are familiar with it. Finally, an application of generating a 3D animation from a hand-drawn comics strip is demonstrated.

Significant body point labeling and tracking.

PubMed

Azhar, Faisal; Tjahjadi, Tardi

2014-09-01

In this paper, a method is presented to label and track anatomical landmarks (e.g., head, hand/arm, feet), which are referred to as significant body points (SBPs), using implicit body models. By considering the human body as an inverted pendulum model, ellipse fitting and contour moments are applied to classify it as being in Stand, Sit, or Lie posture. A convex hull of the silhouette contour is used to determine the locations of SBPs. The particle filter or a motion flow-based method is used to predict SBPs in occlusion. Stick figures of various activities are generated by connecting the SBPs. The qualitative and quantitative evaluation show that the proposed method robustly labels and tracks SBPs in various activities of two different (low and high) resolution data sets.

Evaluation of classifier topologies for the real-time classification of simultaneous limb motions.

PubMed

Ortiz-Catalan, Max; Branemark, Rickard; Hakansson, Bo

2013-01-01

The prediction of motion intent through the decoding of myoelectric signals has the potential to improve the functionally of limb prostheses. Considerable research on individual motion classifiers has been done to exploit this idea. A drawback with the individual prediction approach, however, is its limitation to serial control, which is slow, cumbersome, and unnatural. In this work, different classifier topologies suitable for the decoding of mixed classes, and thus capable of predicting simultaneous motions, were investigated in real-time. These topologies resulted in higher offline accuracies than previously achieved, but more importantly, positive indications of their suitability for real-time systems were found. Furthermore, in order to facilitate further development, benchmarking, and cooperation, the algorithms and data generated in this study are freely available as part of BioPatRec, an open source framework for the development of advanced prosthetic control strategies.

Evaluation of Real-Time Hand Motion Tracking Using a Range Camera and the Mean-Shift Algorithm

NASA Astrophysics Data System (ADS)

Lahamy, H.; Lichti, D.

2011-09-01

Several sensors have been tested for improving the interaction between humans and machines including traditional web cameras, special gloves, haptic devices, cameras providing stereo pairs of images and range cameras. Meanwhile, several methods are described in the literature for tracking hand motion: the Kalman filter, the mean-shift algorithm and the condensation algorithm. In this research, the combination of a range camera and the simple version of the mean-shift algorithm has been evaluated for its capability for hand motion tracking. The evaluation was assessed in terms of position accuracy of the tracking trajectory in x, y and z directions in the camera space and the time difference between image acquisition and image display. Three parameters have been analyzed regarding their influence on the tracking process: the speed of the hand movement, the distance between the camera and the hand and finally the integration time of the camera. Prior to the evaluation, the required warm-up time of the camera has been measured. This study has demonstrated the suitability of the range camera used in combination with the mean-shift algorithm for real-time hand motion tracking but for very high speed hand movement in the traverse plane with respect to the camera, the tracking accuracy is low and requires improvement.

Functional range of motion of the hand joints in activities of the International Classification of Functioning, Disability and Health.

PubMed

Gracia-Ibáñez, Verónica; Vergara, Margarita; Sancho-Bru, Joaquín L; Mora, Marta C; Piqueras, Catalina

Cross-sectional research design. Active range of motion (AROM) is used as indicator of hand function. However, functional range of motion (FROM) data are limited, and fail to represent activities of daily living (ADL). To estimate dominant hand FROM in flexion, abduction and palmar arching in people under 50 years of age performing ADL. AROMs and hand postures in 24 representative ADL of the International Classification of Functioning, Disability and Health (ICF) were recorded in 12 men and 12 women. FROM data were reported by activity and ICF area, and compared with AROMs. The relationship between ROM measures to gender and hand size was analyzed by correlation. FROM was 5° to 28° less than available AROM depending on the joint and movement performed. Joints do not necessarily move through full AROM while performing ADL which has benefits in retaining function despite loss of motion. This may also suggest that ADL alone are insufficient to retain or restore full AROM. Therapists should consider FROM requirements and normal AROM when defining hand therapy goals, interventions and evaluating the success of treatment. N/A. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

Deep learning-based artificial vision for grasp classification in myoelectric hands.

PubMed

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at [Formula: see text] intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. The classification accuracy in the offline tests reached [Formula: see text] for the seen and [Formula: see text] for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of [Formula: see text] in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb Ultra TM prosthetic hand and a motion control TM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to [Formula: see text]. In addition, we show that with training, subjects' performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Deep learning-based artificial vision for grasp classification in myoelectric hands

NASA Astrophysics Data System (ADS)

Ghazaei, Ghazal; Alameer, Ali; Degenaar, Patrick; Morgan, Graham; Nazarpour, Kianoush

2017-06-01

Objective. Computer vision-based assistive technology solutions can revolutionise the quality of care for people with sensorimotor disorders. The goal of this work was to enable trans-radial amputees to use a simple, yet efficient, computer vision system to grasp and move common household objects with a two-channel myoelectric prosthetic hand. Approach. We developed a deep learning-based artificial vision system to augment the grasp functionality of a commercial prosthesis. Our main conceptual novelty is that we classify objects with regards to the grasp pattern without explicitly identifying them or measuring their dimensions. A convolutional neural network (CNN) structure was trained with images of over 500 graspable objects. For each object, 72 images, at {{5}\\circ} intervals, were available. Objects were categorised into four grasp classes, namely: pinch, tripod, palmar wrist neutral and palmar wrist pronated. The CNN setting was first tuned and tested offline and then in realtime with objects or object views that were not included in the training set. Main results. The classification accuracy in the offline tests reached 85 % for the seen and 75 % for the novel objects; reflecting the generalisability of grasp classification. We then implemented the proposed framework in realtime on a standard laptop computer and achieved an overall score of 84 % in classifying a set of novel as well as seen but randomly-rotated objects. Finally, the system was tested with two trans-radial amputee volunteers controlling an i-limb UltraTM prosthetic hand and a motion controlTM prosthetic wrist; augmented with a webcam. After training, subjects successfully picked up and moved the target objects with an overall success of up to 88 % . In addition, we show that with training, subjects’ performance improved in terms of time required to accomplish a block of 24 trials despite a decreasing level of visual feedback. Significance. The proposed design constitutes a substantial conceptual improvement for the control of multi-functional prosthetic hands. We show for the first time that deep-learning based computer vision systems can enhance the grip functionality of myoelectric hands considerably.

Sensing And Force-Reflecting Exoskeleton

NASA Technical Reports Server (NTRS)

Eberman, Brian; Fontana, Richard; Marcus, Beth

1993-01-01

Sensing and force-reflecting exoskeleton (SAFiRE) provides control signals to robot hand and force feedback from robot hand to human operator. Operator makes robot hand touch objects gently and manipulates them finely without exerting excessive forces. Device attaches to operator's hand; comfortable and lightweight. Includes finger exoskeleton, cable mechanical transmission, two dc servomotors, partial thumb exoskeleton, harness, amplifier box, two computer circuit boards, and software. Transduces motion of index finger and thumb. Video monitor of associated computer displays image corresponding to motion.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Hand kinematics of piano playing

PubMed Central

Flanders, Martha; Soechting, John F.

2011-01-01

Dexterous use of the hand represents a sophisticated sensorimotor function. In behaviors such as playing the piano, it can involve strong temporal and spatial constraints. The purpose of this study was to determine fundamental patterns of covariation of motion across joints and digits of the human hand. Joint motion was recorded while 5 expert pianists played 30 excerpts from musical pieces, which featured ∼50 different tone sequences and fingering. Principal component analysis and cluster analysis using an expectation-maximization algorithm revealed that joint velocities could be categorized into several patterns, which help to simplify the description of the movements of the multiple degrees of freedom of the hand. For the thumb keystroke, two distinct patterns of joint movement covariation emerged and they depended on the spatiotemporal patterns of the task. For example, the thumb-under maneuver was clearly separated into two clusters based on the direction of hand translation along the keyboard. While the pattern of the thumb joint velocities differed between these clusters, the motions at the metacarpo-phalangeal and proximal-phalangeal joints of the four fingers were more consistent. For a keystroke executed with one of the fingers, there were three distinct patterns of joint rotations, across which motion at the striking finger was fairly consistent, but motion of the other fingers was more variable. Furthermore, the amount of movement spillover of the striking finger to the adjacent fingers was small irrespective of the finger used for the keystroke. These findings describe an unparalleled amount of independent motion of the fingers. PMID:21880938

Development of a new assessment tool for cervical myelopathy using hand-tracking sensor: Part 2: normative values.

PubMed

Alagha, M Abdulhadi; Alagha, Mahmoud A; Dunstan, Eleanor; Sperwer, Olaf; Timmins, Kate A; Boszczyk, Bronek M

2017-04-01

To set a baseline measurement of the number of hand flexion-extension cycles and analyse the degree of motion in young healthy individuals, measured by leap motion controller (LMC), besides describing gender and dominant hand differences. Fifty healthy participants were asked to fully grip-and-release their dominant hand as rapidly as possible for a maximum of 3 min or until subjects fatigued, while wearing a non-metal wrist splint. Participants also performed a 15-s grip-and-release test. An assessor blindly counted the frequency of grip-and-release cycles and magnitude of motion from the LMC data. The mean number of the 15-s G-R cycles recorded by LMC was: 47.7 ± 6.5 (test 1, LMC); and 50.2 ± 6.5 (test 2, LMC). In the 3-min test, the total number of hand flexion-extension cycles and the degree of motion decreased as the person fatigued. However, the decline in frequency preceded that of motion's magnitude. The mean frequency of cycles per 10-s interval decreased from 35.4 to 26.6 over the 3 min. Participants reached fatigue from 59.38 s; 43 participants were able to complete the 3-min test. Normative values of the frequency of cycles and extent of motion for young healthy individuals, aged 18-35 years, are provided. Future work is needed to establish values in a wider age range and in a clinical setting.

Haptic exploration of fingertip-sized geometric features using a multimodal tactile sensor

NASA Astrophysics Data System (ADS)

Ponce Wong, Ruben D.; Hellman, Randall B.; Santos, Veronica J.

2014-06-01

Haptic perception remains a grand challenge for artificial hands. Dexterous manipulators could be enhanced by "haptic intelligence" that enables identification of objects and their features via touch alone. Haptic perception of local shape would be useful when vision is obstructed or when proprioceptive feedback is inadequate, as observed in this study. In this work, a robot hand outfitted with a deformable, bladder-type, multimodal tactile sensor was used to replay four human-inspired haptic "exploratory procedures" on fingertip-sized geometric features. The geometric features varied by type (bump, pit), curvature (planar, conical, spherical), and footprint dimension (1.25 - 20 mm). Tactile signals generated by active fingertip motions were used to extract key parameters for use as inputs to supervised learning models. A support vector classifier estimated order of curvature while support vector regression models estimated footprint dimension once curvature had been estimated. A distal-proximal stroke (along the long axis of the finger) enabled estimation of order of curvature with an accuracy of 97%. Best-performing, curvature-specific, support vector regression models yielded R2 values of at least 0.95. While a radial-ulnar stroke (along the short axis of the finger) was most helpful for estimating feature type and size for planar features, a rolling motion was most helpful for conical and spherical features. The ability to haptically perceive local shape could be used to advance robot autonomy and provide haptic feedback to human teleoperators of devices ranging from bomb defusal robots to neuroprostheses.

Development of the bedridden person support system using hand gesture.

PubMed

Ichimura, Kouhei; Magatani, Kazushige

2015-08-01

The purpose of this study is to support the bedridden and physically handicapped person who live independently. In this study, we developed Electric appliances control system that can be used on the bed. The subject can control Electric appliances using hand motion. Infrared sensors of a Kinect are used for the hand motion detection. Our developed system was tested with some normal subjects and results of the experiment were evaluated. In this experiment, all subjects laid on the bed and tried to control our system. As results, most of subjects were able to control our developed system perfectly. However, motion tracking of some subject's hand was reset forcibly. It was difficult for these subjects to make the system recognize his opened hand. From these results, we think if this problem will be improved our support system will be useful for the bedridden and physically handicapped persons.

A video-based system for hand-driven stop-motion animation.

PubMed

Han, Xiaoguang; Fu, Hongbo; Zheng, Hanlin; Liu, Ligang; Wang, Jue

2013-01-01

Stop-motion is a well-established animation technique but is often laborious and requires craft skills. A new video-based system can animate the vast majority of everyday objects in stop-motion style, more flexibly and intuitively. Animators can perform and capture motions continuously instead of breaking them into increments and shooting one still picture per increment. More important, the system permits direct hand manipulation without resorting to rigs, achieving more natural object control for beginners. The system's key component is two-phase keyframe-based capturing and processing, assisted by computer vision techniques. With this system, even amateurs can generate high-quality stop-motion animations.

Learning Motion Features for Example-Based Finger Motion Estimation for Virtual Characters

NASA Astrophysics Data System (ADS)

Mousas, Christos; Anagnostopoulos, Christos-Nikolaos

2017-09-01

This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.

Comparing Action Gestures and Classifier Verbs of Motion: Evidence from Australian Sign Language, Taiwan Sign Language, and Nonsigners' Gestures without Speech

ERIC Educational Resources Information Center

Schembri, Adam; Jones, Caroline; Burnham, Denis

2005-01-01

Recent research into signed languages indicates that signs may share some properties with gesture, especially in the use of space in classifier constructions. A prediction of this proposal is that there will be similarities in the representation of motion events by sign-naive gesturers and by native signers of unrelated signed languages. This…

Toward attenuating the impact of arm positions on electromyography pattern-recognition based motion classification in transradial amputees

PubMed Central

2012-01-01

Background Electromyography (EMG) pattern-recognition based control strategies for multifunctional myoelectric prosthesis systems have been studied commonly in a controlled laboratory setting. Before these myoelectric prosthesis systems are clinically viable, it will be necessary to assess the effect of some disparities between the ideal laboratory setting and practical use on the control performance. One important obstacle is the impact of arm position variation that causes the changes of EMG pattern when performing identical motions in different arm positions. This study aimed to investigate the impacts of arm position variation on EMG pattern-recognition based motion classification in upper-limb amputees and the solutions for reducing these impacts. Methods With five unilateral transradial (TR) amputees, the EMG signals and tri-axial accelerometer mechanomyography (ACC-MMG) signals were simultaneously collected from both amputated and intact arms when performing six classes of arm and hand movements in each of five arm positions that were considered in the study. The effect of the arm position changes was estimated in terms of motion classification error and compared between amputated and intact arms. Then the performance of three proposed methods in attenuating the impact of arm positions was evaluated. Results With EMG signals, the average intra-position and inter-position classification errors across all five arm positions and five subjects were around 7.3% and 29.9% from amputated arms, respectively, about 1.0% and 10% low in comparison with those from intact arms. While ACC-MMG signals could yield a similar intra-position classification error (9.9%) as EMG, they had much higher inter-position classification error with an average value of 81.1% over the arm positions and the subjects. When the EMG data from all five arm positions were involved in the training set, the average classification error reached a value of around 10.8% for amputated arms. Using a two-stage cascade classifier, the average classification error was around 9.0% over all five arm positions. Reducing ACC-MMG channels from 8 to 2 only increased the average position classification error across all five arm positions from 0.7% to 1.0% in amputated arms. Conclusions The performance of EMG pattern-recognition based method in classifying movements strongly depends on arm positions. This dependency is a little stronger in intact arm than in amputated arm, which suggests that the investigations associated with practical use of a myoelectric prosthesis should use the limb amputees as subjects instead of using able-body subjects. The two-stage cascade classifier mode with ACC-MMG for limb position identification and EMG for limb motion classification may be a promising way to reduce the effect of limb position variation on classification performance. PMID:23036049

A motion-classification strategy based on sEMG-EEG signal combination for upper-limb amputees.

PubMed

Li, Xiangxin; Samuel, Oluwarotimi Williams; Zhang, Xu; Wang, Hui; Fang, Peng; Li, Guanglin

2017-01-07

Most of the modern motorized prostheses are controlled with the surface electromyography (sEMG) recorded on the residual muscles of amputated limbs. However, the residual muscles are usually limited, especially after above-elbow amputations, which would not provide enough sEMG for the control of prostheses with multiple degrees of freedom. Signal fusion is a possible approach to solve the problem of insufficient control commands, where some non-EMG signals are combined with sEMG signals to provide sufficient information for motion intension decoding. In this study, a motion-classification method that combines sEMG and electroencephalography (EEG) signals were proposed and investigated, in order to improve the control performance of upper-limb prostheses. Four transhumeral amputees without any form of neurological disease were recruited in the experiments. Five motion classes including hand-open, hand-close, wrist-pronation, wrist-supination, and no-movement were specified. During the motion performances, sEMG and EEG signals were simultaneously acquired from the skin surface and scalp of the amputees, respectively. The two types of signals were independently preprocessed and then combined as a parallel control input. Four time-domain features were extracted and fed into a classifier trained by the Linear Discriminant Analysis (LDA) algorithm for motion recognition. In addition, channel selections were performed by using the Sequential Forward Selection (SFS) algorithm to optimize the performance of the proposed method. The classification performance achieved by the fusion of sEMG and EEG signals was significantly better than that obtained by single signal source of either sEMG or EEG. An increment of more than 14% in classification accuracy was achieved when using a combination of 32-channel sEMG and 64-channel EEG. Furthermore, based on the SFS algorithm, two optimized electrode arrangements (10-channel sEMG + 10-channel EEG, 10-channel sEMG + 20-channel EEG) were obtained with classification accuracies of 84.2 and 87.0%, respectively, which were about 7.2 and 10% higher than the accuracy by using only 32-channel sEMG input. This study demonstrated the feasibility of fusing sEMG and EEG signals towards improving motion classification accuracy for above-elbow amputees, which might enhance the control performances of multifunctional myoelectric prostheses in clinical application. The study was approved by the ethics committee of Institutional Review Board of Shenzhen Institutes of Advanced Technology, and the reference number is SIAT-IRB-150515-H0077.

Method for neural network control of motion using real-time environmental feedback

NASA Technical Reports Server (NTRS)

Buckley, Theresa M. (Inventor)

1997-01-01

A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.

7 CFR 2902.18 - Hand cleaners and sanitizers.

Code of Federal Regulations, 2010 CFR

2010-01-01

... use in removing bacteria from human hands with or without the use of water. Personal care products... and bacteria from human hands with or without the use of water are classified as hand sanitizers for...

7 CFR 2902.18 - Hand cleaners and sanitizers.

Code of Federal Regulations, 2011 CFR

2011-01-01

... use in removing bacteria from human hands with or without the use of water. Personal care products... and bacteria from human hands with or without the use of water are classified as hand sanitizers for...

iHandRehab: an interactive hand exoskeleton for active and passive rehabilitation.

PubMed

Li, Jiting; Zheng, Ruoyin; Zhang, Yuru; Yao, Jianchu

2011-01-01

This paper presents an interactive exoskeleton device for hand rehabilitation, iHandRehab, which aims to satisfy the essential requirements for both active and passive rehabilitation motions. iHandRehab is comprised of exoskeletons for the thumb and index finger. These exoskeletons are driven by distant actuation modules through a cable/sheath transmission mechanism. The exoskeleton for each finger has 4 degrees of freedom (DOF), providing independent control for all finger joints. The joint motion is accomplished by a parallelogram mechanism so that the joints of the device and their corresponding finger joints have the same angular displacement when they rotate. Thanks to this design, the joint angles can be measured by sensors real time and high level motion control is therefore made very simple without the need of complicated kinematics. The paper also discusses important issues when the device is used by different patients, including its adjustable joint range of motion (ROM) and adjustable range of phalanx length (ROPL). Experimentally collected data show that the achieved ROM is close to that of a healthy hand and the ROPL covers the size of a typical hand, satisfying the size need of regular hand rehabilitation. In order to evaluate the performance when it works as a haptic device in active mode, the equivalent moment of inertia (MOI) of the device is calculated. The results prove that the device has low inertia which is critical in order to obtain good backdrivability. Experimental analysis shows that the influence of friction accounts for a large portion of the driving torque and warrants future investigation. © 2011 IEEE

User-Independent Motion State Recognition Using Smartphone Sensors

PubMed Central

Gu, Fuqiang; Kealy, Allison; Khoshelham, Kourosh; Shang, Jianga

2015-01-01

The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users’ data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people’s motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human’s motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy. PMID:26690163

User-Independent Motion State Recognition Using Smartphone Sensors.

PubMed

Gu, Fuqiang; Kealy, Allison; Khoshelham, Kourosh; Shang, Jianga

2015-12-04

The recognition of locomotion activities (e.g., walking, running, still) is important for a wide range of applications like indoor positioning, navigation, location-based services, and health monitoring. Recently, there has been a growing interest in activity recognition using accelerometer data. However, when utilizing only acceleration-based features, it is difficult to differentiate varying vertical motion states from horizontal motion states especially when conducting user-independent classification. In this paper, we also make use of the newly emerging barometer built in modern smartphones, and propose a novel feature called pressure derivative from the barometer readings for user motion state recognition, which is proven to be effective for distinguishing vertical motion states and does not depend on specific users' data. Seven types of motion states are defined and six commonly-used classifiers are compared. In addition, we utilize the motion state history and the characteristics of people's motion to improve the classification accuracies of those classifiers. Experimental results show that by using the historical information and human's motion characteristics, we can achieve user-independent motion state classification with an accuracy of up to 90.7%. In addition, we analyze the influence of the window size and smartphone pose on the accuracy.

[Study on an Exoskeleton Hand Function Training Device].

PubMed

Hu, Xin; Zhang, Ying; Li, Jicai; Yi, Jinhua; Yu, Hongliu; He, Rongrong

2016-02-01

Based on the structure and motion bionic principle of the normal adult fingers, biological characteristics of human hands were analyzed, and a wearable exoskeleton hand function training device for the rehabilitation of stroke patients or patients with hand trauma was designed. This device includes the exoskeleton mechanical structure and the electromyography (EMG) control system. With adjustable mechanism, the device was capable to fit different finger lengths, and by capturing the EMG of the users' contralateral limb, the motion state of the exoskeleton hand was controlled. Then driven by the device, the user's fingers conducting adduction/abduction rehabilitation training was carried out. Finally, the mechanical properties and training effect of the exoskeleton hand were verified through mechanism simulation and the experiments on the experimental prototype of the wearable exoskeleton hand function training device.

Vision-Based Detection and Distance Estimation of Micro Unmanned Aerial Vehicles

PubMed Central

Gökçe, Fatih; Üçoluk, Göktürk; Şahin, Erol; Kalkan, Sinan

2015-01-01

Detection and distance estimation of micro unmanned aerial vehicles (mUAVs) is crucial for (i) the detection of intruder mUAVs in protected environments; (ii) sense and avoid purposes on mUAVs or on other aerial vehicles and (iii) multi-mUAV control scenarios, such as environmental monitoring, surveillance and exploration. In this article, we evaluate vision algorithms as alternatives for detection and distance estimation of mUAVs, since other sensing modalities entail certain limitations on the environment or on the distance. For this purpose, we test Haar-like features, histogram of gradients (HOG) and local binary patterns (LBP) using cascades of boosted classifiers. Cascaded boosted classifiers allow fast processing by performing detection tests at multiple stages, where only candidates passing earlier simple stages are processed at the preceding more complex stages. We also integrate a distance estimation method with our system utilizing geometric cues with support vector regressors. We evaluated each method on indoor and outdoor videos that are collected in a systematic way and also on videos having motion blur. Our experiments show that, using boosted cascaded classifiers with LBP, near real-time detection and distance estimation of mUAVs are possible in about 60 ms indoors (1032×778 resolution) and 150 ms outdoors (1280×720 resolution) per frame, with a detection rate of 0.96 F-score. However, the cascaded classifiers using Haar-like features lead to better distance estimation since they can position the bounding boxes on mUAVs more accurately. On the other hand, our time analysis yields that the cascaded classifiers using HOG train and run faster than the other algorithms. PMID:26393599

Task-specific motor performance and musculoskeletal response in self-classified right handers.

PubMed

Kumar, Sameer; Mandal, Manas K

2003-11-01

We examined the difference between the left and right hand motor performance (in terms of erg produced) of self-classified right handers (15 men, 15 women) for power (task involving muscle force) and skilled (task involving precision and eye hand coordination) tasks. Musculoskeletal response during task performance was measured by electromyogram to test the hypothesis that performance with the nondominant hand would trigger more generalized muscle tension. The difference between the left and right hand performance of men was nonsignificant for power task; for women, right hand performance was significantly superior than left for such task. Men excelled in power and women excelled in skilled tasks relative to their counterparts. Generalized muscle tension was significantly more during the left than the right hand performance for power but not for skilled tasks.

Development of an image operation system with a motion sensor in dental radiology.

PubMed

Sato, Mitsuru; Ogura, Toshihiro; Yasumoto, Yoshiaki; Kadowaki, Yuta; Hayashi, Norio; Doi, Kunio

2015-07-01

During examinations and/or treatment, a dentist in the examination room needs to view images with a proper display system. However, they cannot operate the image display system by hands, because dentists always wear gloves to be kept their hands away from unsanitized materials. Therefore, we developed a new image operating system that uses a motion sensor. We used the Leap motion sensor technique to read the hand movements of a dentist. We programmed the system using C++ to enable various movements of the display system, i.e., click, double click, drag, and drop. Thus, dentists with their gloves on in the examination room can control dental and panoramic images on the image display system intuitively and quickly with movement of their hands only. We investigated the time required with the conventional method using a mouse and with the new method using the finger operation. The average operation time with the finger method was significantly shorter than that with the mouse method. This motion sensor method, with appropriate training for finger movements, can provide a better operating performance than the conventional mouse method.

Parallel controller construction for a multi-DOF hand rehabilitation equipment

NASA Astrophysics Data System (ADS)

Ito, Satoshi; Ueki, Satoshi; Ishihara, Koji; Miura, Masayuki; Kawasaki, Haruhisa; Ishigure, Yasuhiko; Nishimoto, Yutakai

2007-12-01

This paper describes the development of a hand rehabilitation system for stroke patients. Our aim is to provide fine motion exercise for a hand and fingers. Thus, a hand rehabilitation device that assists patients' finger movements was developed. Because this device has 18 degrees of freedom of motion, it is diffcult for disabled patients to use it by themselves. Therefore, an appropriate control strategy and control system are required to allow its safe and effective use. In light of this requirement, a control system was constructed which is comprised of four separated controllers. This paper presents the structure of the control system and introduces the control protocols used in our hand rehabilitation system.

Off-road machine controls: investigating the risk of carpal tunnel syndrome.

PubMed

Oliver, M; Rickards, J; Biden, E

2000-11-01

Occupationally induced hand and wrist repetitive strain injuries (RSI) such as carpal tunnel syndrome (CTS) are a growing problem in North America. The purpose of this investigation was to apply a modification of the wrist flexion/ extension models of Armstrong and Chaffin (1978, 1979) to determine if joystick controller use in off-road machines could contribute to the development of CTS. A construction equipment cab in the laboratory was instrumented to allow force, displacement and angle measurements from 10 operators while they completed an approximately 30-min joystick motion protocol. The investigation revealed that both the external fingertip and predicted internal wrist forces resulting from the use of these joysticks were very low, indicating that the CTS risk associated with this factor was slight. However, the results also indicated that, particularly for the 'forward' and 'left' right side motions and for all left side motions, force was exerted by other portions of the fingers and hand, thereby under-predicting the tendon tension and internal wrist forces. Wrist angles observed were highest for motions that moved the joysticks to the sides rather than front to back. Thus, the 'right' and 'left' motions for both hands posed a higher risk for CTS development. When the right hand moved into the 'right' position and the left hand moved into the 'left' position, the wrist went into extension in both cases. Results indicate that neither learning nor fatigue affected the results.

Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

PubMed

Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

2015-12-01

We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion.

Integration Head Mounted Display Device and Hand Motion Gesture Device for Virtual Reality Laboratory

NASA Astrophysics Data System (ADS)

Rengganis, Y. A.; Safrodin, M.; Sukaridhoto, S.

2018-01-01

Virtual Reality Laboratory (VR Lab) is an innovation for conventional learning media which show us whole learning process in laboratory. There are many tools and materials are needed by user for doing practical in it, so user could feel new learning atmosphere by using this innovation. Nowadays, technologies more sophisticated than before. So it would carry in education and it will be more effective, efficient. The Supported technologies are needed us for making VR Lab such as head mounted display device and hand motion gesture device. The integration among them will be used us for making this research. Head mounted display device for viewing 3D environment of virtual reality laboratory. Hand motion gesture device for catching user real hand and it will be visualized in virtual reality laboratory. Virtual Reality will show us, if using the newest technologies in learning process it could make more interesting and easy to understand.

Swarm-wavelet based extreme learning machine for finger movement classification on transradial amputees.

PubMed

Anam, Khairul; Al-Jumaily, Adel

2014-01-01

The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined finger motions on five amputees by using only two EMG channels. The optimal performance of wavelet-PSO was compared to a grid-search method and standard PSO. The experimental results show that the proposed system is the most accurate classifier among other tested classifiers. It could classify 11 finger motions with the average accuracy of about 94 % across five amputees.

The compensatory motion of wrist immobilization on thumb and index finger performance--kinematic analysis and clinical implications.

PubMed

Liu, Chien-Hsiou; Chiang, Hsin-Yu; Chen, Kun-Hung

2015-01-01

Based on the high prevalence of people with problems in the wrist and hand simultaneously, it is of its importance to clarify whether hand joints exert extra motion to compensate for wrist motion while immobilized. This study aimed to measure the compensatory movement of the thumb and index finger when people perform daily activities with an immobilized wrist. Thirty healthy volunteers were recruited in this study. A wrist splint, the Jebsen-Taylor Hand Function Test, and the OptoTrak Certus motion tracking system were used. Seven inter-digit mean joint angles of the index finger and thumb were calculated. Paired sample t-test was used. (1) The compensatory motions were noted in the Metacarpophalangeal and Carpometacarpal joints of the thumb, and the proximal interphalangeal joints of the index finger; (2) The manifestation of compensatory motion was related to type of activity performed except when picking up light and heavy cans. The compensatory motions appeared while the wrist was immobilized and were found to be disadvantageous to the progression of disease. In the future, studies need to be done to understand how to select products with correct ergonomic design to enable people to reap greater benefits from wearing wrist splints.

Asymptomatic rotator cuff tears: Patient demographics and baseline shoulder function

PubMed Central

Keener, Jay D.; Steger-May, Karen; Stobbs, Georgia; Yamaguchi, Ken

2010-01-01

Background The purpose of this study is to characterize the demographic features and physical function of subjects with asymptomatic rotator cuff tears and to compare their shoulder function to controls with an intact rotator cuff. Materials and Methods 196 subjects with an asymptomatic rotator cuff tear and 54 subjects with an intact rotator cuff presenting with a painful rotator cuff tear in the contralateral shoulder were enrolled. Various demographic features, shoulder function (ASES score and SST score), range of motion and strength were compared. Results The demographic features of the study and control groups were similar. Hand dominance was associated with the presence of shoulder pain (p < .05). Subjects with an intact rotator cuff had greater but clinically insignificant ASES (p < .05) and SST scores (p < .05) than those with an asymptomatic tear. No differences in functional scores, range of motion or strength were seen between partial (n=61) and full-thickness tears (n=135). Of the full-thickness tears, 36 (27%) were classified as small, 85 (63%) as medium and 14 (10%) as large tears. No differences were seen in functional scores between full-thickness tears of various sizes. Conclusions When asymptomatic, a rotator cuff tear is associated with a clinically insignificant loss of shoulder function compared to those with an intact rotator cuff. Therefore, a clinically detectable decline in shoulder function may indicate an “at-risk” asymptomatic tear. The presence of pain is important in cuff deficient shoulders for creating a measurable loss of shoulder function. Hand dominance appears to be an important risk factor for pain. PMID:21030274

Hand function and quality of life before and after fasciectomy for Dupuytren contracture.

PubMed

Engstrand, Christina; Krevers, Barbro; Nylander, Göran; Kvist, Joanna

2014-07-01

To describe changes in joint motion, sensibility, and scar pliability and to investigate the patients' expectations, self-reported recovery, and satisfaction with hand function, disability, and quality of life after surgery and hand therapy for Dupuytren disease. This prospective cohort study collected measurements before surgery and 3, 6, and 12 months after surgery and hand therapy. Ninety patients with total active extension deficits of 60° or more from Dupuytren contracture were included. Outcomes measures were range of motion; sensibility; scar pliability; self-reported outcomes on expectations, recovery, and satisfaction with hand function; Disabilities of the Arm, Shoulder, and Hand scores; safety and social issues of hand function; physical activity habits; and quality of life with the Euroqol. The extension deficit decreased, and there was a transient decrease in active finger flexion during the first year after surgery. Sensibility remained unaffected. Generally, patients with surgery on multiple fingers had worse scar pliability. The majority of the patients had their expectations met, and at 6 months, 32% considered hand function as fully recovered, and 73% were satisfied with their hand function. Fear of hurting the hand and worry about not trusting the hand function were of greatest concern among safety and social issues. The Disability of the Arm, Shoulder, and Hand score and the Euroqol improved over time. After surgery and hand therapy, disability decreased independent of single or multiple operated fingers. The total active finger extension improved enough for the patients to reach a functional range of motion despite an impairment of active finger flexion still present 12 months after treatment. Therapeutic IV. Copyright © 2014 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

A mechatronics platform to study prosthetic hand control using EMG signals.

PubMed

Geethanjali, P

2016-09-01

In this paper, a low-cost mechatronics platform for the design and development of robotic hands as well as a surface electromyogram (EMG) pattern recognition system is proposed. This paper also explores various EMG classification techniques using a low-cost electronics system in prosthetic hand applications. The proposed platform involves the development of a four channel EMG signal acquisition system; pattern recognition of acquired EMG signals; and development of a digital controller for a robotic hand. Four-channel surface EMG signals, acquired from ten healthy subjects for six different movements of the hand, were used to analyse pattern recognition in prosthetic hand control. Various time domain features were extracted and grouped into five ensembles to compare the influence of features in feature-selective classifiers (SLR) with widely considered non-feature-selective classifiers, such as neural networks (NN), linear discriminant analysis (LDA) and support vector machines (SVM) applied with different kernels. The results divulged that the average classification accuracy of the SVM, with a linear kernel function, outperforms other classifiers with feature ensembles, Hudgin's feature set and auto regression (AR) coefficients. However, the slight improvement in classification accuracy of SVM incurs more processing time and memory space in the low-level controller. The Kruskal-Wallis (KW) test also shows that there is no significant difference in the classification performance of SLR with Hudgin's feature set to that of SVM with Hudgin's features along with AR coefficients. In addition, the KW test shows that SLR was found to be better in respect to computation time and memory space, which is vital in a low-level controller. Similar to SVM, with a linear kernel function, other non-feature selective LDA and NN classifiers also show a slight improvement in performance using twice the features but with the drawback of increased memory space requirement and time. This prototype facilitated the study of various issues of pattern recognition and identified an efficient classifier, along with a feature ensemble, in the implementation of EMG controlled prosthetic hands in a laboratory setting at low-cost. This platform may help to motivate and facilitate prosthetic hand research in developing countries.

Site classification of Indian strong motion network using response spectra ratios

NASA Astrophysics Data System (ADS)

Chopra, Sumer; Kumar, Vikas; Choudhury, Pallabee; Yadav, R. B. S.

2018-03-01

In the present study, we tried to classify the Indian strong motion sites spread all over Himalaya and adjoining region, located on varied geological formations, based on response spectral ratio. A total of 90 sites were classified based on 395 strong motion records from 94 earthquakes recorded at these sites. The magnitude of these earthquakes are between 2.3 and 7.7 and the hypocentral distance for most of the cases is less than 50 km. The predominant period obtained from response spectral ratios is used to classify these sites. It was found that the shape and predominant peaks of the spectra at these sites match with those in Japan, Italy, Iran, and at some of the sites in Europe and the same classification scheme can be applied to Indian strong motion network. We found that the earlier schemes based on description of near-surface geology, geomorphology, and topography were not able to capture the effect of sediment thickness. The sites are classified into seven classes (CL-I to CL-VII) with varying predominant periods and ranges as proposed by Alessandro et al. (Bull Seismol Soc Am 102:680-695 2012). The effect of magnitudes and hypocentral distances on the shape and predominant peaks were also studied and found to be very small. The classification scheme is robust and cost-effective and can be used in region-specific attenuation relationships for accounting local site effect.

Grounding grammatical categories: attention bias in hand space influences grammatical congruency judgment of Chinese nominal classifiers.

PubMed

Lobben, Marit; D'Ascenzo, Stefania

2015-01-01

Embodied cognitive theories predict that linguistic conceptual representations are grounded and continually represented in real world, sensorimotor experiences. However, there is an on-going debate on whether this also holds for abstract concepts. Grammar is the archetype of abstract knowledge, and therefore constitutes a test case against embodied theories of language representation. Former studies have largely focussed on lexical-level embodied representations. In the present study we take the grounding-by-modality idea a step further by using reaction time (RT) data from the linguistic processing of nominal classifiers in Chinese. We take advantage of an independent body of research, which shows that attention in hand space is biased. Specifically, objects near the hand consistently yield shorter RTs as a function of readiness for action on graspable objects within reaching space, and the same biased attention inhibits attentional disengagement. We predicted that this attention bias would equally apply to the graspable object classifier but not to the big object classifier. Chinese speakers (N = 22) judged grammatical congruency of classifier-noun combinations in two conditions: graspable object classifier and big object classifier. We found that RTs for the graspable object classifier were significantly faster in congruent combinations, and significantly slower in incongruent combinations, than the big object classifier. There was no main effect on grammatical violations, but rather an interaction effect of classifier type. Thus, we demonstrate here grammatical category-specific effects pertaining to the semantic content and by extension the visual and tactile modality of acquisition underlying the acquisition of these categories. We conclude that abstract grammatical categories are subjected to the same mechanisms as general cognitive and neurophysiological processes and may therefore be grounded.

Grounding grammatical categories: attention bias in hand space influences grammatical congruency judgment of Chinese nominal classifiers

PubMed Central

Lobben, Marit; D’Ascenzo, Stefania

2015-01-01

Embodied cognitive theories predict that linguistic conceptual representations are grounded and continually represented in real world, sensorimotor experiences. However, there is an on-going debate on whether this also holds for abstract concepts. Grammar is the archetype of abstract knowledge, and therefore constitutes a test case against embodied theories of language representation. Former studies have largely focussed on lexical-level embodied representations. In the present study we take the grounding-by-modality idea a step further by using reaction time (RT) data from the linguistic processing of nominal classifiers in Chinese. We take advantage of an independent body of research, which shows that attention in hand space is biased. Specifically, objects near the hand consistently yield shorter RTs as a function of readiness for action on graspable objects within reaching space, and the same biased attention inhibits attentional disengagement. We predicted that this attention bias would equally apply to the graspable object classifier but not to the big object classifier. Chinese speakers (N = 22) judged grammatical congruency of classifier-noun combinations in two conditions: graspable object classifier and big object classifier. We found that RTs for the graspable object classifier were significantly faster in congruent combinations, and significantly slower in incongruent combinations, than the big object classifier. There was no main effect on grammatical violations, but rather an interaction effect of classifier type. Thus, we demonstrate here grammatical category-specific effects pertaining to the semantic content and by extension the visual and tactile modality of acquisition underlying the acquisition of these categories. We conclude that abstract grammatical categories are subjected to the same mechanisms as general cognitive and neurophysiological processes and may therefore be grounded. PMID:26379611

Quantitative underwater 3D motion analysis using submerged video cameras: accuracy analysis and trajectory reconstruction.

PubMed

Silvatti, Amanda P; Cerveri, Pietro; Telles, Thiago; Dias, Fábio A S; Baroni, Guido; Barros, Ricardo M L

2013-01-01

In this study we aim at investigating the applicability of underwater 3D motion capture based on submerged video cameras in terms of 3D accuracy analysis and trajectory reconstruction. Static points with classical direct linear transform (DLT) solution, a moving wand with bundle adjustment and a moving 2D plate with Zhang's method were considered for camera calibration. As an example of the final application, we reconstructed the hand motion trajectories in different swimming styles and qualitatively compared this with Maglischo's model. Four highly trained male swimmers performed butterfly, breaststroke and freestyle tasks. The middle fingertip trajectories of both hands in the underwater phase were considered. The accuracy (mean absolute error) of the two calibration approaches (wand: 0.96 mm - 2D plate: 0.73 mm) was comparable to out of water results and highly superior to the classical DLT results (9.74 mm). Among all the swimmers, the hands' trajectories of the expert swimmer in the style were almost symmetric and in good agreement with Maglischo's model. The kinematic results highlight symmetry or asymmetry between the two hand sides, intra- and inter-subject variability in terms of the motion patterns and agreement or disagreement with the model. The two outcomes, calibration results and trajectory reconstruction, both move towards the quantitative 3D underwater motion analysis.

34 CFR 81.11 - Motions.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) Except for a request for an extension of time, a motion must be made in writing unless the parties appear... oral motion to writing. (c) If a party files a motion, the party shall serve a copy of the motion on the other party on the filing date by hand-delivery or by mail. If agreed upon by the parties, service...

Kinesthetic information disambiguates visual motion signals.

PubMed

Hu, Bo; Knill, David C

2010-05-25

Numerous studies have shown that extra-retinal signals can disambiguate motion information created by movements of the eye or head. We report a new form of cross-modal sensory integration in which the kinesthetic information generated by active hand movements essentially captures ambiguous visual motion information. Several previous studies have shown that active movement can bias observers' percepts of bi-stable stimuli; however, these effects seem to be best explained by attentional mechanisms. We show that kinesthetic information can change an otherwise stable perception of motion, providing evidence of genuine fusion between visual and kinesthetic information. The experiments take advantage of the aperture problem, in which the motion of a one-dimensional grating pattern behind an aperture, while geometrically ambiguous, appears to move stably in the grating normal direction. When actively moving the pattern, however, the observer sees the motion to be in the hand movement direction. Copyright 2010 Elsevier Ltd. All rights reserved.

Teaching Motion with the Global Positioning System

ERIC Educational Resources Information Center

Budisa, Marko; Planinsic, Gorazd

2003-01-01

We have used the GPS receiver and a PC interface to track different types of motion. Various hands-on experiments that enlighten the physics of motion at the secondary school level are suggested (visualization of 2D and 3D motion, measuring car drag coefficient and fuel consumption). (Contains 8 figures.)

Entropic Movement Complexity Reflects Subjective Creativity Rankings of Visualized Hand Motion Trajectories

PubMed Central

Peng, Zhen; Braun, Daniel A.

2015-01-01

In a previous study we have shown that human motion trajectories can be characterized by translating continuous trajectories into symbol sequences with well-defined complexity measures. Here we test the hypothesis that the motion complexity individuals generate in their movements might be correlated to the degree of creativity assigned by a human observer to the visualized motion trajectories. We asked participants to generate 55 novel hand movement patterns in virtual reality, where each pattern had to be repeated 10 times in a row to ensure reproducibility. This allowed us to estimate a probability distribution over trajectories for each pattern. We assessed motion complexity not only by the previously proposed complexity measures on symbolic sequences, but we also propose two novel complexity measures that can be directly applied to the distributions over trajectories based on the frameworks of Gaussian Processes and Probabilistic Movement Primitives. In contrast to previous studies, these new methods allow computing complexities of individual motion patterns from very few sample trajectories. We compared the different complexity measures to how a group of independent jurors rank ordered the recorded motion trajectories according to their personal creativity judgment. We found three entropic complexity measures that correlate significantly with human creativity judgment and discuss differences between the measures. We also test whether these complexity measures correlate with individual creativity in divergent thinking tasks, but do not find any consistent correlation. Our results suggest that entropic complexity measures of hand motion may reveal domain-specific individual differences in kinesthetic creativity. PMID:26733896

Rotating bouncing disks, tossing pizza dough, and the behavior of ultrasonic motors

NASA Astrophysics Data System (ADS)

Liu, Kuang-Chen; Friend, James; Yeo, Leslie

2009-10-01

Pizza tossing and certain forms of standing-wave ultrasonic motors (SWUMs) share a similar process for converting reciprocating input into continuous rotary motion. We show that the key features of this motion conversion process such as collision, separation and friction coupling are captured by the dynamics of a disk bouncing on a vibrating platform. The model shows that the linear or helical hand motions commonly used by pizza chefs and dough-toss performers for single tosses maximize energy efficiency and the dough’s airborne rotational speed; on the other hand, the semielliptical hand motions used for multiple tosses make it easier to maintain dough rotation at the maximum speed. The system’s bifurcation diagram and basins of attraction also provide a physical basis for understanding the peculiar behavior of SWUMs and provide a means to design them. The model is able to explain the apparently chaotic oscillations that occur in SWUMs and predict the observed trends in steady-state speed and stall torque as preload is increased.

Rotating bouncing disks, tossing pizza dough, and the behavior of ultrasonic motors.

PubMed

Liu, Kuang-Chen; Friend, James; Yeo, Leslie

2009-10-01

Pizza tossing and certain forms of standing-wave ultrasonic motors (SWUMs) share a similar process for converting reciprocating input into continuous rotary motion. We show that the key features of this motion conversion process such as collision, separation and friction coupling are captured by the dynamics of a disk bouncing on a vibrating platform. The model shows that the linear or helical hand motions commonly used by pizza chefs and dough-toss performers for single tosses maximize energy efficiency and the dough's airborne rotational speed; on the other hand, the semielliptical hand motions used for multiple tosses make it easier to maintain dough rotation at the maximum speed. The system's bifurcation diagram and basins of attraction also provide a physical basis for understanding the peculiar behavior of SWUMs and provide a means to design them. The model is able to explain the apparently chaotic oscillations that occur in SWUMs and predict the observed trends in steady-state speed and stall torque as preload is increased.

Motion tracking and electromyography assist the removal of mirror hand contributions to fNIRS images acquired during a finger tapping task performed by children with cerebral palsy

NASA Astrophysics Data System (ADS)

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

2013-03-01

Functional neurological imaging has been shown to be valuable in evaluating brain plasticity in children with cerebral palsy (CP). In recent studies it has been demonstrated that functional near-infrared spectroscopy (fNIRS) is a viable and sensitive method for imaging motor cortex activities in children with CP. However, during unilateral finger tapping tasks children with CP often exhibit mirror motions (unintended motions in the non-tapping hand), and current fNIRS image formation techniques do not account for this. Therefore, the resulting fNIRS images contain activation from intended and unintended motions. In this study, cortical activity was mapped with fNIRS on four children with CP and five controls during a finger tapping task. Finger motion and arm muscle activation were concurrently measured using motion tracking cameras and electromyography (EMG). Subject-specific regressors were created from motion capture and EMG data and used in a general linear model (GLM) analysis in an attempt to create fNIRS images representative of different motions. The analysis provided an fNIRS image representing activation due to motion and muscle activity for each hand. This method could prove to be valuable in monitoring brain plasticity in children with CP by providing more consistent images between measurements. Additionally, muscle effort versus cortical effort was compared between control and CP subjects. More cortical effort was required to produce similar muscle effort in children with CP. It is possible this metric could be a valuable diagnostic tool in determining response to treatment.

Humanlike robot hands controlled by brain activity arouse illusion of ownership in operators

PubMed Central

Alimardani, Maryam; Nishio, Shuichi; Ishiguro, Hiroshi

2013-01-01

Operators of a pair of robotic hands report ownership for those hands when they hold image of a grasp motion and watch the robot perform it. We present a novel body ownership illusion that is induced by merely watching and controlling robot's motions through a brain machine interface. In past studies, body ownership illusions were induced by correlation of such sensory inputs as vision, touch and proprioception. However, in the presented illusion none of the mentioned sensations are integrated except vision. Our results show that during BMI-operation of robotic hands, the interaction between motor commands and visual feedback of the intended motions is adequate to incorporate the non-body limbs into one's own body. Our discussion focuses on the role of proprioceptive information in the mechanism of agency-driven illusions. We believe that our findings will contribute to improvement of tele-presence systems in which operators incorporate BMI-operated robots into their body representations. PMID:23928891

Simulating the dynamics of the mechanochemical cycle of myosin-V

PubMed Central

Mukherjee, Shayantani; Alhadeff, Raphael; Warshel, Arieh

2017-01-01

The detailed dynamics of the cycle of myosin-V are explored by simulation approaches, examining the nature of the energy-driven motion. Our study started with Langevin dynamics (LD) simulations on a very coarse landscape with a single rate-limiting barrier and reproduced the stall force and the hand-over-hand dynamics. We then considered a more realistic landscape and used time-dependent Monte Carlo (MC) simulations that allowed trajectories long enough to reproduce the force/velocity characteristic sigmoidal correlation, while also reproducing the hand-over-hand motion. Overall, our study indicated that the notion of a downhill lever-up to lever-down process (popularly known as the powerstroke mechanism) is the result of the energetics of the complete myosin-V cycle and is not the source of directional motion or force generation on its own. The present work further emphasizes the need to use well-defined energy landscapes in studying molecular motors in general and myosin in particular. PMID:28193897

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation.

PubMed

Lin, Bor-Shing; Lee, I-Jung; Yang, Shu-Yu; Lo, Yi-Chiang; Lee, Junghsi; Chen, Jean-Lon

2018-05-13

Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.

Double-Windows-Based Motion Recognition in Multi-Floor Buildings Assisted by a Built-In Barometer.

PubMed

Liu, Maolin; Li, Huaiyu; Wang, Yuan; Li, Fei; Chen, Xiuwan

2018-04-01

Accelerometers, gyroscopes and magnetometers in smartphones are often used to recognize human motions. Since it is difficult to distinguish between vertical motions and horizontal motions in the data provided by these built-in sensors, the vertical motion recognition accuracy is relatively low. The emergence of a built-in barometer in smartphones improves the accuracy of motion recognition in the vertical direction. However, there is a lack of quantitative analysis and modelling of the barometer signals, which is the basis of barometer's application to motion recognition, and a problem of imbalanced data also exists. This work focuses on using the barometers inside smartphones for vertical motion recognition in multi-floor buildings through modelling and feature extraction of pressure signals. A novel double-windows pressure feature extraction method, which adopts two sliding time windows of different length, is proposed to balance recognition accuracy and response time. Then, a random forest classifier correlation rule is further designed to weaken the impact of imbalanced data on recognition accuracy. The results demonstrate that the recognition accuracy can reach 95.05% when pressure features and the improved random forest classifier are adopted. Specifically, the recognition accuracy of the stair and elevator motions is significantly improved with enhanced response time. The proposed approach proves effective and accurate, providing a robust strategy for increasing accuracy of vertical motions.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

Personalization algorithm for real-time activity recognition using PDA, wireless motion bands, and binary decision tree.

PubMed

Pärkkä, Juha; Cluitmans, Luc; Ermes, Miikka

2010-09-01

Inactive and sedentary lifestyle is a major problem in many industrialized countries today. Automatic recognition of type of physical activity can be used to show the user the distribution of his daily activities and to motivate him into more active lifestyle. In this study, an automatic activity-recognition system consisting of wireless motion bands and a PDA is evaluated. The system classifies raw sensor data into activity types online. It uses a decision tree classifier, which has low computational cost and low battery consumption. The classifier parameters can be personalized online by performing a short bout of an activity and by telling the system which activity is being performed. Data were collected with seven volunteers during five everyday activities: lying, sitting/standing, walking, running, and cycling. The online system can detect these activities with overall 86.6% accuracy and with 94.0% accuracy after classifier personalization.

Local feature saliency classifier for real-time intrusion monitoring

NASA Astrophysics Data System (ADS)

Buch, Norbert; Velastin, Sergio A.

2014-07-01

We propose a texture saliency classifier to detect people in a video frame by identifying salient texture regions. The image is classified into foreground and background in real time. No temporal image information is used during the classification. The system is used for the task of detecting people entering a sterile zone, which is a common scenario for visual surveillance. Testing is performed on the Imagery Library for Intelligent Detection Systems sterile zone benchmark dataset of the United Kingdom's Home Office. The basic classifier is extended by fusing its output with simple motion information, which significantly outperforms standard motion tracking. A lower detection time can be achieved by combining texture classification with Kalman filtering. The fusion approach running at 10 fps gives the highest result of F1=0.92 for the 24-h test dataset. The paper concludes with a detailed analysis of the computation time required for the different parts of the algorithm.

A pilot study to assess use of passive extension bias to facilitate finger movement for repetitive task practice after stroke.

PubMed

Iwamuro, B T; Fischer, H C; Kamper, D G

2011-01-01

The purpose of this study was to investigate whether active range of finger motion could be increased through the introduction of passive, external extension joint torques in stroke survivors. Five chronic stroke survivors with severe hand impairment resulting from hemiparesis took part in the study. Participants completed 2 experimental sessions in which hand movement and function were assessed. In one session, they wore a custom orthotic glove (X-Glove) that passively supplied extension torques to the joints of the fingers. In the second session, they performed the same tasks as in the other session, but without the glove. Outcome measures consisted of active range of motion, distance of the fingertip from the hand, selected tasks from the Graded Wolf Motor Function Test (GWMFT), and the Box and Blocks (BB) test. Primary results with and without the glove were compared using paired t tests with a Bonferroni correction. Active range of motion improved significantly by over 50%, from 4.4 cm to 6.7 cm, when the X-Glove was worn (P = .011). The distance of the fingertip from the metacarpophalangeal joint increased by an average of 2.2 cm for 4 of the subjects, although this change was not significant across all 5 subjects (P = .123). No significant differences were observed in the BB or GWMFT whether the X-Glove was worn or not. Introduction of passive extension torque can improve active range of motion for the fingers, even in chronic stroke survivors with substantial hand impairment. The increased range of motion would facilitate therapeutic training of the hand, potentially even in the home environment, although the bulk of the orthosis should be minimized to facilitate interactions with real objects.

Brain-machine interface control of a manipulator using small-world neural network and shared control strategy.

PubMed

Li, Ting; Hong, Jun; Zhang, Jinhua; Guo, Feng

2014-03-15

The improvement of the resolution of brain signal and the ability to control external device has been the most important goal in BMI research field. This paper describes a non-invasive brain-actuated manipulator experiment, which defined a paradigm for the motion control of a serial manipulator based on motor imagery and shared control. The techniques of component selection, spatial filtering and classification of motor imagery were involved. Small-world neural network (SWNN) was used to classify five brain states. To verify the effectiveness of the proposed classifier, we replace the SWNN classifier by a radial basis function (RBF) networks neural network, a standard multi-layered feed-forward backpropagation network (SMN) and a multi-SVM classifier, with the same features for the classification. The results also indicate that the proposed classifier achieves a 3.83% improvement over the best results of other classifiers. We proposed a shared control method consisting of two control patterns to expand the control of BMI from the software angle. The job of path building for reaching the 'end' point was designated as an assessment task. We recorded all paths contributed by subjects and picked up relevant parameters as evaluation coefficients. With the assistance of two control patterns and series of machine learning algorithms, the proposed BMI originally achieved the motion control of a manipulator in the whole workspace. According to experimental results, we confirmed the feasibility of the proposed BMI method for 3D motion control of a manipulator using EEG during motor imagery. Copyright © 2013 Elsevier B.V. All rights reserved.

Adaptive temporal compressive sensing for video with motion estimation

NASA Astrophysics Data System (ADS)

Wang, Yeru; Tang, Chaoying; Chen, Yueting; Feng, Huajun; Xu, Zhihai; Li, Qi

2018-04-01

In this paper, we present an adaptive reconstruction method for temporal compressive imaging with pixel-wise exposure. The motion of objects is first estimated from interpolated images with a designed coding mask. With the help of motion estimation, image blocks are classified according to the degree of motion and reconstructed with the corresponding dictionary, which was trained beforehand. Both the simulation and experiment results show that the proposed method can obtain accurate motion information before reconstruction and efficiently reconstruct compressive video.

A Method for the Control of Multigrasp Myoelectric Prosthetic Hands

PubMed Central

Dalley, Skyler Ashton; Varol, Huseyin Atakan; Goldfarb, Michael

2012-01-01

This paper presents the design and preliminary experimental validation of a multigrasp myoelectric controller. The described method enables direct and proportional control of multigrasp prosthetic hand motion among nine characteristic postures using two surface electromyography electrodes. To assess the efficacy of the control method, five nonamputee subjects utilized the multigrasp myoelectric controller to command the motion of a virtual prosthesis between random sequences of target hand postures in a series of experimental trials. For comparison, the same subjects also utilized a data glove, worn on their native hand, to command the motion of the virtual prosthesis for similar sequences of target postures during each trial. The time required to transition from posture to posture and the percentage of correctly completed transitions were evaluated to characterize the ability to control the virtual prosthesis using each method. The average overall transition times across all subjects were found to be 1.49 and 0.81 s for the multigrasp myoelectric controller and the native hand, respectively. The average transition completion rates for both were found to be the same (99.2%). Supplemental videos demonstrate the virtual prosthesis experiments, as well as a preliminary hardware implementation. PMID:22180515

Modeling Attitude Dynamics in Simulink: A Study of the Rotational and Translational Motion of a Spacecraft Given Torques and Impulses Generated by RMS Hand Controllers

NASA Technical Reports Server (NTRS)

Mauldin, Rebecca H.

2010-01-01

In order to study and control the attitude of a spacecraft, it is necessary to understand the natural motion of a body in orbit. Assuming a spacecraft to be a rigid body, dynamics describes the complete motion of the vehicle by the translational and rotational motion of the body. The Simulink Attitude Analysis Model applies the equations of rigid body motion to the study of a spacecraft?s attitude in orbit. Using a TCP/IP connection, Matlab reads the values of the Remote Manipulator System (RMS) hand controllers and passes them to Simulink as specified torque and impulse profiles. Simulink then uses the governing kinematic and dynamic equations of a rigid body in low earth orbit (LE0) to plot the attitude response of a spacecraft for five seconds given known applied torques and impulses, and constant principal moments of inertia.

Sensitive and Flexible Polymeric Strain Sensor for Accurate Human Motion Monitoring

PubMed Central

Khan, Hassan; Kottapalli, Ajay; Asadnia, Mohsen

2018-01-01

Flexible electronic devices offer the capability to integrate and adapt with human body. These devices are mountable on surfaces with various shapes, which allow us to attach them to clothes or directly onto the body. This paper suggests a facile fabrication strategy via electrospinning to develop a stretchable, and sensitive poly (vinylidene fluoride) nanofibrous strain sensor for human motion monitoring. A complete characterization on the single PVDF nano fiber has been performed. The charge generated by PVDF electrospun strain sensor changes was employed as a parameter to control the finger motion of the robotic arm. As a proof of concept, we developed a smart glove with five sensors integrated into it to detect the fingers motion and transfer it to a robotic hand. Our results shows that the proposed strain sensors are able to detect tiny motion of fingers and successfully run the robotic hand. PMID:29389851

Metaphors are Embodied, and so are Their Literal Counterparts

PubMed Central

Santana, Eduardo; de Vega, Manuel

2011-01-01

This study investigates whether understanding up/down metaphors as well as semantically homologous literal sentences activates embodied representations online. Participants read orientational literal sentences (e.g., she climbed up the hill), metaphors (e.g., she climbed up in the company), and abstract sentences with similar meaning to the metaphors (e.g., she succeeded in the company). In Experiments 1 and 2, participants were asked to perform a speeded upward or downward hand motion while they were reading the sentence verb. The hand motion either matched or mismatched the direction connoted by the sentence. The results showed a meaning-action effect for metaphors and literals, that is, faster hand motion responses in the matching conditions. Notably, the matching advantage was also found for homologous abstract sentences, indicating that some abstract ideas are conceptually organized in the vertical dimension, even when they are expressed by means of literal sentences. In Experiment 3, participants responded to an upward or downward visual motion associated with the sentence verb by pressing a single key. In this case, the facilitation effect for matching visual motion-sentence meaning faded, indicating that the visual motion component is less important than the action component in conceptual metaphors. Most up and down metaphors convey emotionally positive and negative information, respectively. We suggest that metaphorical meaning elicits upward/downward movements because they are grounded on the bodily expression of the corresponding emotions. PMID:21687459

Smart Prosthetic Hand Technology - Phase 2

DTIC Science & Technology

2011-05-01

identification and estimation, hand motion estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The...Smart Prosthetics, Bio- Robotics , Intelligent EMG Signal Processing, Embedded Systems and Intelligent Control, Inflammatory Responses of Cells, Toxicity...estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The developed identification algorithm using a new

Understanding the EF-hand closing pathway using non-biased interatomic potentials.

PubMed

Dupuis, L; Mousseau, Normand

2012-01-21

The EF-hand superfamily of proteins is characterized by the presence of calcium binding helix-loop-helix structures. Many of these proteins undergo considerable motion responsible for a wide range of properties upon binding but the exact mechanism at the root of this motion is not fully understood. Here, we use an unbiased accelerated multiscale simulation scheme, coupled with two force fields - CHARMM-EEF1 and the extended OPEP - to explore in details the closing pathway, from the unbound holo state to the closed apo state, of two EF-hand proteins, the Calmodulin and Troponin C N-terminal nodules. Based on a number of closing simulations for these two sequences, we show that the EF-hand β-scaffold, identified as crucial by Grabarek for the EF-hand opening driven by calcium binding, is also important in closing the EF-hand. We also show the crucial importance of the phenylalanine situated at the end of first EF-hand helix, and identify an intermediate state modulating its behavior, providing a detailed picture of the closing mechanism for these two representatives of EF-hand proteins. © 2012 American Institute of Physics

Classifying prosthetic use via accelerometry in persons with transtibial amputations.

PubMed

Redfield, Morgan T; Cagle, John C; Hafner, Brian J; Sanders, Joan E

2013-01-01

Knowledge of how persons with amputation use their prostheses and how this use changes over time may facilitate effective rehabilitation practices and enhance understanding of prosthesis functionality. Perpetual monitoring and classification of prosthesis use may also increase the health and quality of life for prosthetic users. Existing monitoring and classification systems are often limited in that they require the subject to manipulate the sensor (e.g., attach, remove, or reset a sensor), record data over relatively short time periods, and/or classify a limited number of activities and body postures of interest. In this study, a commercially available three-axis accelerometer (ActiLife ActiGraph GT3X+) was used to characterize the activities and body postures of individuals with transtibial amputation. Accelerometers were mounted on prosthetic pylons of 10 persons with transtibial amputation as they performed a preset routine of actions. Accelerometer data was postprocessed using a binary decision tree to identify when the prosthesis was being worn and to classify periods of use as movement (i.e., leg motion such as walking or stair climbing), standing (i.e., standing upright with limited leg motion), or sitting (i.e., seated with limited leg motion). Classifications were compared to visual observation by study researchers. The classifier achieved a mean +/- standard deviation accuracy of 96.6% +/- 3.0%.

Classifying Prosthetic Use via Accelerometry in Persons with Trans-Tibial Amputations

PubMed Central

Redfield, Morgan T.; Cagle, John C.; Hafner, Brian J.; Sanders, Joan E.

2014-01-01

Knowledge of how persons with amputation use their prostheses and how this use changes over time may facilitate effective rehabilitation practices and enhance understanding of prosthesis functionality. Perpetual monitoring and classification of prosthesis use may also increase the health and quality of life for prosthetic users. Existing monitoring and classification systems are often limited in that they require the subject to manipulate the sensor (e.g., attach, remove, or reset a sensor), record data over relatively short time periods, and/or classify a limited number of activities and body postures of interest. In this study, a commercially-available three-axis accelerometer (ActiLife ActiGraph GT3X+) was used to characterize the activities and body postures of individuals with trans-tibial amputation. Accelerometers were mounted on prosthetic pylons of ten persons with trans-tibial amputation as they performed a preset routine of actions. Accelerometer data was post-processed using a Binary Decision Tree to identify when the prosthesis was being worn and to classify periods of use as movement (i.e., leg motion like walking or stair climbing), standing (i.e., standing upright with limited leg motion), or sitting (i.e., seated with limited leg motion). Classifications were compared to visual observation by study researchers. The classifier achieved a mean accuracy of 96.6% (SD=3.0%). PMID:24458961

Bayesian Decision Tree for the Classification of the Mode of Motion in Single-Molecule Trajectories

PubMed Central

Türkcan, Silvan; Masson, Jean-Baptiste

2013-01-01

Membrane proteins move in heterogeneous environments with spatially (sometimes temporally) varying friction and with biochemical interactions with various partners. It is important to reliably distinguish different modes of motion to improve our knowledge of the membrane architecture and to understand the nature of interactions between membrane proteins and their environments. Here, we present an analysis technique for single molecule tracking (SMT) trajectories that can determine the preferred model of motion that best matches observed trajectories. The method is based on Bayesian inference to calculate the posteriori probability of an observed trajectory according to a certain model. Information theory criteria, such as the Bayesian information criterion (BIC), the Akaike information criterion (AIC), and modified AIC (AICc), are used to select the preferred model. The considered group of models includes free Brownian motion, and confined motion in 2nd or 4th order potentials. We determine the best information criteria for classifying trajectories. We tested its limits through simulations matching large sets of experimental conditions and we built a decision tree. This decision tree first uses the BIC to distinguish between free Brownian motion and confined motion. In a second step, it classifies the confining potential further using the AIC. We apply the method to experimental Clostridium Perfingens -toxin (CPT) receptor trajectories to show that these receptors are confined by a spring-like potential. An adaptation of this technique was applied on a sliding window in the temporal dimension along the trajectory. We applied this adaptation to experimental CPT trajectories that lose confinement due to disaggregation of confining domains. This new technique adds another dimension to the discussion of SMT data. The mode of motion of a receptor might hold more biologically relevant information than the diffusion coefficient or domain size and may be a better tool to classify and compare different SMT experiments. PMID:24376584

A new method for recognizing hand configurations of Brazilian gesture language.

PubMed

Costa Filho, C F F; Dos Santos, B L; de Souza, R S; Dos Santos, J R; Costa, M G F

2016-08-01

This paper describes a new method for recognizing hand configurations of the Brazilian Gesture Language - LIBRAS - using depth maps obtained with a Kinect® camera. The proposed method comprised three phases: hand segmentation, feature extraction, and classification. The segmentation phase is independent from the background and depends only on pixel depth information. Using geometric operations and numerical normalization, the feature extraction process was done independent from rotation and translation. The features are extracted employing two techniques: (2D)2LDA and (2D)2PCA. The classification is made with a novelty classifier. A robust database was constructed for classifier evaluation, with 12,200 images of LIBRAS and 200 gestures of each hand configuration. The best accuracy obtained was 95.41%, which was greater than previous values obtained in the literature.

Discrimination of Human Forearm Motions on the Basis of Myoelectric Signals by Using Adaptive Fuzzy Inference System

NASA Astrophysics Data System (ADS)

Kiso, Atsushi; Seki, Hirokazu

This paper describes a method for discriminating of the human forearm motions based on the myoelectric signals using an adaptive fuzzy inference system. In conventional studies, the neural network is often used to estimate motion intention by the myoelectric signals and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signals. This study designs the membership function and the fuzzy rules using the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. In addition, the characteristics of the myoelectric potential gradually change as a result of the muscle fatigue. Therefore, the motion discrimination should be performed by taking muscle fatigue into consideration. This study proposes a method to redesign the fuzzy inference system such that dynamic change of the myoelectric potential because of the muscle fatigue will be taken into account. Some experiments carried out using a myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.

Electrogoniometer measurement and directional analysis of wrist angles and movements during the Sollerman hand function test.

PubMed

Dauncey, Thomas; Singh, Harvinder P; Dias, Joseph J

Clinical measurement. To investigate the characteristics of wrist motion (area, axis, and location) during activities of daily living (ADL) using electrogoniometry. A sample of 83 normal volunteers performed the Sollerman hand function test (SHFT) with a flexible biaxial electrogoniometer applied to their wrists. This technique is accurate and reliable and has been used before for assessment of wrist circumduction in normal volunteers. A software package was used to overlay an ellipse of best fit around the 2-dimensional trace of the electrogoniometer mathematically computing the area, location, and axis angle of the ellipse. Most ADL could be completed within 20% of the total area of circumduction (3686°° ± 1575°°) of a normal wrist. An oblique plane in radial extension and ulnar flexion (dart-throwing motion plane) was used for rotation (-14° ± 32°) and power grip tasks (-29° ± 25°) during ADL; however, precision tasks (4° ± 28°), like writing, were performed more often in the flexion extension plane. In the dominant hand, only 2 power tasks were located in flexion region (cutting play dough [ulnar] and pouring carton [radial]), precision tasks were located centrally, and rotation and other power tasks were located in extension region. This study has identified that wrist motion during the ADL requires varying degrees of movement in oblique planes. Using electrogoniometry, we could visualize the area, location, and plane of motion during ADL. This could assist future researchers to compare procedures leading to loss of motion in specific quadrants of wrist motion and its impact on patient's ability in performing particular ADL. It could guide hand therapists to specifically focus on retraining the ADL that may be affected when wrist range of motion is lost after injury. Diagnostic level III. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

Typical use of inverse dynamics in perceiving motion in autistic adults: Exploring computational principles of perception and action.

PubMed

Takamuku, Shinya; Forbes, Paul A G; Hamilton, Antonia F de C; Gomi, Hiroaki

2018-05-07

There is increasing evidence for motor difficulties in many people with autism spectrum condition (ASC). These difficulties could be linked to differences in the use of internal models which represent relations between motions and forces/efforts. The use of these internal models may be dependent on the cerebellum which has been shown to be abnormal in autism. Several studies have examined internal computations of forward dynamics (motion from force information) in autism, but few have tested the inverse dynamics computation, that is, the determination of force-related information from motion information. Here, we examined this ability in autistic adults by measuring two perceptual biases which depend on the inverse computation. First, we asked participants whether they experienced a feeling of resistance when moving a delayed cursor, which corresponds to the inertial force of the cursor implied by its motion-both typical and ASC participants reported similar feelings of resistance. Second, participants completed a psychophysical task in which they judged the velocity of a moving hand with or without a visual cue implying inertial force. Both typical and ASC participants perceived the hand moving with the inertial cue to be slower than the hand without it. In both cases, the magnitude of the effects did not differ between the two groups. Our results suggest that the neural systems engaged in the inverse dynamics computation are preserved in ASC, at least in the observed conditions. Autism Res 2018. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. We tested the ability to estimate force information from motion information, which arises from a specific "inverse dynamics" computation. Autistic adults and a matched control group reported feeling a resistive sensation when moving a delayed cursor and also judged a moving hand to be slower when it was pulling a load. These findings both suggest that the ability to estimate force information from motion information is intact in autism. © 2018 International Society for Autism Research, Wiley Periodicals, Inc.

Clinical effectiveness of combined virtual reality and robot assisted fine hand motion rehabilitation in subacute stroke patients.

PubMed

Huang, Xianwei; Naghdy, Fazel; Naghdy, Golshah; Du, Haiping

2017-07-01

Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive rehabilitation training in restoring motor skills after a stroke. This study focuses on the rehabilitation of fine hand motion skills due to their vital role in performing delicate activities of daily living (ADL) tasks. The proposed rehabilitation system combines an adaptive assist-as-needed (AAN) control algorithm and a Virtual Reality (VR) based rehabilitation gaming system (RGS). The developed system is described and its effectiveness is validated through clinical trials on a group of eight subacute stroke patients for a period of six weeks. The impact of the training is verified through standard clinical evaluation methods and measuring key kinematic parameters. A comparison of the pre- and post-training results indicates that the method proposed in this study can improve fine hand motion rehabilitation training effectiveness.

Data Fusion Based on Optical Technology for Observation of Human Manipulation

NASA Astrophysics Data System (ADS)

Falco, Pietro; De Maria, Giuseppe; Natale, Ciro; Pirozzi, Salvatore

2012-01-01

The adoption of human observation is becoming more and more frequent within imitation learning and programming by demonstration approaches (PbD) to robot programming. For robotic systems equipped with anthropomorphic hands, the observation phase is very challenging and no ultimate solution exists. This work proposes a novel mechatronic approach to the observation of human hand motion during manipulation tasks. The strategy is based on the combined use of an optical motion capture system and a low-cost data glove equipped with novel joint angle sensors, based on optoelectronic technology. The combination of the two information sources is obtained through a sensor fusion algorithm based on the extended Kalman filter (EKF) suitably modified to tackle the problem of marker occlusions, typical of optical motion capture systems. This approach requires a kinematic model of the human hand. Another key contribution of this work is a new method to calibrate this model.

The adaptation of GDL motion recognition system to sport and rehabilitation techniques analysis.

PubMed

Hachaj, Tomasz; Ogiela, Marek R

2016-06-01

The main novelty of this paper is presenting the adaptation of Gesture Description Language (GDL) methodology to sport and rehabilitation data analysis and classification. In this paper we showed that Lua language can be successfully used for adaptation of the GDL classifier to those tasks. The newly applied scripting language allows easily extension and integration of classifier with other software technologies and applications. The obtained execution speed allows using the methodology in the real-time motion capture data processing where capturing frequency differs from 100 Hz to even 500 Hz depending on number of features or classes to be calculated and recognized. Due to this fact the proposed methodology can be used to the high-end motion capture system. We anticipate that using novel, efficient and effective method will highly help both sport trainers and physiotherapist in they practice. The proposed approach can be directly applied to motion capture data kinematics analysis (evaluation of motion without regard to the forces that cause that motion). The ability to apply pattern recognition methods for GDL description can be utilized in virtual reality environment and used for sport training or rehabilitation treatment.

Online myoelectric control of a dexterous hand prosthesis by transradial amputees.

PubMed

Cipriani, Christian; Antfolk, Christian; Controzzi, Marco; Lundborg, Göran; Rosen, Birgitta; Carrozza, Maria Chiara; Sebelius, Fredrik

2011-06-01

A real-time pattern recognition algorithm based on k-nearest neighbors and lazy learning was used to classify, voluntary electromyography (EMG) signals and to simultaneously control movements of a dexterous artificial hand. EMG signals were superficially recorded by eight pairs of electrodes from the stumps of five transradial amputees and forearms of five able-bodied participants and used online to control a robot hand. Seven finger movements (not involving the wrist) were investigated in this study. The first objective was to understand whether and to which extent it is possible to control continuously and in real-time, the finger postures of a prosthetic hand, using superficial EMG, and a practical classifier, also taking advantage of the direct visual feedback of the moving hand. The second objective was to calculate statistical differences in the performance between participants and groups, thereby assessing the general applicability of the proposed method. The average accuracy of the classifier was 79% for amputees and 89% for able-bodied participants. Statistical analysis of the data revealed a difference in control accuracy based on the aetiology of amputation, type of prostheses regularly used and also between able-bodied participants and amputees. These results are encouraging for the development of noninvasive EMG interfaces for the control of dexterous prostheses.

Track Everything: Limiting Prior Knowledge in Online Multi-Object Recognition.

PubMed

Wong, Sebastien C; Stamatescu, Victor; Gatt, Adam; Kearney, David; Lee, Ivan; McDonnell, Mark D

2017-10-01

This paper addresses the problem of online tracking and classification of multiple objects in an image sequence. Our proposed solution is to first track all objects in the scene without relying on object-specific prior knowledge, which in other systems can take the form of hand-crafted features or user-based track initialization. We then classify the tracked objects with a fast-learning image classifier, that is based on a shallow convolutional neural network architecture and demonstrate that object recognition improves when this is combined with object state information from the tracking algorithm. We argue that by transferring the use of prior knowledge from the detection and tracking stages to the classification stage, we can design a robust, general purpose object recognition system with the ability to detect and track a variety of object types. We describe our biologically inspired implementation, which adaptively learns the shape and motion of tracked objects, and apply it to the Neovision2 Tower benchmark data set, which contains multiple object types. An experimental evaluation demonstrates that our approach is competitive with the state-of-the-art video object recognition systems that do make use of object-specific prior knowledge in detection and tracking, while providing additional practical advantages by virtue of its generality.

Clinical Assessment and Diagnostics of Patients With Hand Disorders: A Case Study Approach.

PubMed

Leow, Mabel Qi He; Lim, Rebecca Qian Ru; Tay, Shian Chao

Clinical assessment of the hand is important for diagnosing underlying hand disorders. Using a case study approach, the clinical assessment for three disorders of the hands is presented: trigger finger (stenosing tenosynovitis), carpal tunnel syndrome, and ulnar-sided wrist injury (styloid impingement). We assess the annular one pulley and finger range of motion for patients with trigger finger. To diagnose for carpal tunnel syndrome, assessment for Tinel's sign, Phalen's sign, abductor pollicis brevis muscle bulk, two-point discrimination, and obtaining a nerve conduction study are performed. Assessment for ulnar-sided wrist injury includes wrist range of motion, assessment of distal radial ulnar joint stability, provocation tests, grip strength, x-ray, and magnetic resonance imaging. This article begins with a description of the hand and wrist anatomy. For each case study, the clinical history is described, followed by a discussion of the pathophysiology, clinical assessments, and diagnostic tests.

The exploded hand syndrome: a report of five industrial injury cases.

PubMed

Al-Qattan, M M

2013-10-01

The term 'exploded hand syndrome' refers to a specific type of crush injury to the hand in which a high compressive force excessively flattens the hand leading to thenar muscle extrusion through burst lacerations. Out of 89 crushed hands seen over a period of seven years, only five had exploded hand syndrome. They were all male industrial workers ranging in age between 24 and 55 years. All patients had thenar muscle extrusion. Other concurrent injuries included fractures/dislocations, compartment syndrome, and ischaemia. All patients were treated by excision of the extruded intrinsic muscles, as well as primary management of concurrent injuries. All patients had functional assessment including: motor power and sensory testing, range of motion of hand joints, and the quick DASH score. Objective testing showed reduced sensibility in the thumb, reduced grip strength (mean 52% of contralateral hand), reduced pinch strength (mean of 27% of contralateral hand), reduced thumb opposition (the mean Kapandji Score was 5 out of 10), and deficits in the range of motion of the metacarpophalangeal and interphalangeal joints of the thumb. The quick DASH score ranged from 11 to 49 and only two patients were able to go back to regular manual work.

Compact Telerobot Hand

NASA Technical Reports Server (NTRS)

Rosheim, Mark; Trechsel, Hans

1993-01-01

Anthropomorphic telerobotic hand contains actuators, joints, sensors, and complex wiring harnesses. Glove protects interior components of hand from dirt and damage. Imitates motions of human fingers and wrist in lifelike and dexterous way. Incorporates pitch/yaw joints in wrist and head knuckles. Hand modular; so fingers removable, interchangeable units. Feature simplifies servicing and maintenance, which must be done frequently in such complex mechanism.

Decoding conjunctions of direction-of-motion and binocular disparity from human visual cortex.

PubMed

Seymour, Kiley J; Clifford, Colin W G

2012-05-01

Motion and binocular disparity are two features in our environment that share a common correspondence problem. Decades of psychophysical research dedicated to understanding stereopsis suggest that these features interact early in human visual processing to disambiguate depth. Single-unit recordings in the monkey also provide evidence for the joint encoding of motion and disparity across much of the dorsal visual stream. Here, we used functional MRI and multivariate pattern analysis to examine where in the human brain conjunctions of motion and disparity are encoded. Subjects sequentially viewed two stimuli that could be distinguished only by their conjunctions of motion and disparity. Specifically, each stimulus contained the same feature information (leftward and rightward motion and crossed and uncrossed disparity) but differed exclusively in the way these features were paired. Our results revealed that a linear classifier could accurately decode which stimulus a subject was viewing based on voxel activation patterns throughout the dorsal visual areas and as early as V2. This decoding success was conditional on some voxels being individually sensitive to the unique conjunctions comprising each stimulus, thus a classifier could not rely on independent information about motion and binocular disparity to distinguish these conjunctions. This study expands on evidence that disparity and motion interact at many levels of human visual processing, particularly within the dorsal stream. It also lends support to the idea that stereopsis is subserved by early mechanisms also tuned to direction of motion.

Using a virtual reality temporal bone simulator to assess otolaryngology trainees.

PubMed

Zirkle, Molly; Roberson, David W; Leuwer, Rudolf; Dubrowski, Adam

2007-02-01

The objective of this study is to determine the feasibility of computerized evaluation of resident performance using hand motion analysis on a virtual reality temporal bone (VR TB) simulator. We hypothesized that both computerized analysis and expert ratings would discriminate the performance of novices from experienced trainees. We also hypothesized that performance on the virtual reality temporal bone simulator (VR TB) would differentiate based on previous drilling experience. The authors conducted a randomized, blind assessment study. Nineteen volunteers from the Otolaryngology-Head and Neck Surgery training program at the University of Toronto drilled both a cadaveric TB and a simulated VR TB. Expert reviewers were asked to assess operative readiness of the trainee based on a blind video review of their performance. Computerized hand motion analysis of each participant's performance was conducted. Expert raters were able to discriminate novices from experienced trainees (P < .05) on cadaveric temporal bones, and there was a trend toward discrimination on VR TB performance. Hand motion analysis showed that experienced trainees had better movement economy than novices (P < .05) on the VR TB. Performance, as measured by hand motion analysis on the VR TB simulator, reflects trainees' previous drilling experience. This study suggests that otolaryngology trainees could accomplish initial temporal bone training on a VR TB simulator, which can provide feedback to the trainee, and may reduce the need for constant faculty supervision and evaluation.

Types of diaphragmatic motion during hepatic angiography.

PubMed

Katsuda, T; Kuroda, C; Fujita, M

1997-01-01

To determine the types and causes of diaphragmatic motion during hepatic angiography, the authors used transarterial cut-film portography (TAP) to study movement of the diaphragm during breath-holding. Thirty-three TAP sequences were studied, and the patients' diaphragmatic motions were classified into four categories according to the distance their diaphragms moved. Results showed that the diaphragm was stationary in 33% of the TAP studies, while perpetual motion occurred in 15% of the studies, early-phase motion occurred in 12% and late-phase motion occurred in 40%. Ten sequences showed diaphragmatic motion of more than 10 mm, with eight sequences showing caudal motion and two showing cranial motion. This article discusses the cause of diaphragmatic motion during breath-holding for hepatic angiography and presents suggestions to reduce motion artifacts during the exam.

Hand Grasping Synergies As Biometrics.

PubMed

Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana

2017-01-01

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.

Real-Time Control of an Exoskeleton Hand Robot with Myoelectric Pattern Recognition.

PubMed

Lu, Zhiyuan; Chen, Xiang; Zhang, Xu; Tong, Kay-Yu; Zhou, Ping

2017-08-01

Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

Precision manipulation with a dextrous robot hand

NASA Astrophysics Data System (ADS)

Michelman, Paul

1994-01-01

In this thesis, we discuss a framework for describing and synthesizing precision manipulation tasks with a robot hand. Precision manipulations are those in which the motions of grasped objects are caused by finger motions alone (as distinct from arm or wrist motion). Experiments demonstrating the capabilities of the Utah-MIT hand are presented. This work begins by examining current research on biological motor control to raise a number of questions. For example, is the control centralized and organized by a central processor? Or is the control distributed throughout the nervous system? Motor control research on manipulation has focused on developing classifications of hand motions, concentrating solely on finger motions, while neglecting grasp stability and interaction forces that occur in manipulation. In addition, these taxonomies have not been explicitly functional. This thesis defines and analyzes a basic set of manipulation strategies that includes both position and force trajectories. The fundamental purposes of the manipulations are: (1) rectilinear and rotational motion of grasped objects of different geometries; and (2) the application of forces and moments against the environment by the grasped objects. First, task partitioning is described to allocate the fingers their roles in the task. Second, for each strategy, the mechanics and workspace of the tasks are analyzed geometrically to determine the gross finger trajectories required to achieve the tasks. Techniques illustrating the combination of simple manipulations into complex, multiple degree-of-freedom tasks are presented. There is a discussion of several tasks that use multiple elementary strategies. The tasks described are removing the top of a childproof medicine bottle, putting the top back on, rotating and regrasping a block and a cylinder within the grasp. Finally, experimental results are presented. The experimental setup at Columbia University's Center for Research in Intelligent Systems and experiments with a Utah-MIT hand is discussed. First, the overall system design is described. Two hybrid position/force controllers were designed and built. After a discussion of the entire system, experimental results are presented describing each of the basic manipulation and complex manipulation strategies.

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.

Motion correction in MRI of the brain

PubMed Central

Godenschweger, F; Kägebein, U; Stucht, D; Yarach, U; Sciarra, A; Yakupov, R; Lüsebrink, F; Schulze, P; Speck, O

2016-01-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed. PMID:26864183

Motion correction in MRI of the brain

NASA Astrophysics Data System (ADS)

Godenschweger, F.; Kägebein, U.; Stucht, D.; Yarach, U.; Sciarra, A.; Yakupov, R.; Lüsebrink, F.; Schulze, P.; Speck, O.

2016-03-01

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.

Carrying Position Independent User Heading Estimation for Indoor Pedestrian Navigation with Smartphones

PubMed Central

Deng, Zhi-An; Wang, Guofeng; Hu, Ying; Cui, Yang

2016-01-01

This paper proposes a novel heading estimation approach for indoor pedestrian navigation using the built-in inertial sensors on a smartphone. Unlike previous approaches constraining the carrying position of a smartphone on the user’s body, our approach gives the user a larger freedom by implementing automatic recognition of the device carrying position and subsequent selection of an optimal strategy for heading estimation. We firstly predetermine the motion state by a decision tree using an accelerometer and a barometer. Then, to enable accurate and computational lightweight carrying position recognition, we combine a position classifier with a novel position transition detection algorithm, which may also be used to avoid the confusion between position transition and user turn during pedestrian walking. For a device placed in the trouser pockets or held in a swinging hand, the heading estimation is achieved by deploying a principal component analysis (PCA)-based approach. For a device held in the hand or against the ear during a phone call, user heading is directly estimated by adding the yaw angle of the device to the related heading offset. Experimental results show that our approach can automatically detect carrying positions with high accuracy, and outperforms previous heading estimation approaches in terms of accuracy and applicability. PMID:27187391

High-density force myography: A possible alternative for upper-limb prosthetic control.

PubMed

Radmand, Ashkan; Scheme, Erik; Englehart, Kevin

2016-01-01

Several multiple degree-of-freedom upper-limb prostheses that have the promise of highly dexterous control have recently been developed. Inadequate controllability, however, has limited adoption of these devices. Introducing more robust control methods will likely result in higher acceptance rates. This work investigates the suitability of using high-density force myography (HD-FMG) for prosthetic control. HD-FMG uses a high-density array of pressure sensors to detect changes in the pressure patterns between the residual limb and socket caused by the contraction of the forearm muscles. In this work, HD-FMG outperforms the standard electromyography (EMG)-based system in detecting different wrist and hand gestures. With the arm in a fixed, static position, eight hand and wrist motions were classified with 0.33% error using the HD-FMG technique. Comparatively, classification errors in the range of 2.2%-11.3% have been reported in the literature for multichannel EMG-based approaches. As with EMG, position variation in HD-FMG can introduce classification error, but incorporating position variation into the training protocol reduces this effect. Channel reduction was also applied to the HD-FMG technique to decrease the dimensionality of the problem as well as the size of the sensorized area. We found that with informed, symmetric channel reduction, classification error could be decreased to 0.02%.

Effect of biased feedback on motor imagery learning in BCI-teleoperation system.

PubMed

Alimardani, Maryam; Nishio, Shuichi; Ishiguro, Hiroshi

2014-01-01

Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users' BCI performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects' performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects' BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects' online performance, evaluation of brain activity patterns revealed that subjects' self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects' motor imagery skills.

A Tool for Creating Regionally Calibrated High-Resolution Land Cover Data Sets for the West African Sahel: Using Machine Learning to Scale Up Hand-Classified Maps in a Data-Sparse Environment

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Van Gordon, S.; Min, A.; Sullivan, J.; Weiner, Z.; Tappan, G. G.

2017-12-01

Using support vector machine (SVM) learning and high-accuracy hand-classified maps, we have developed a publicly available land cover classification tool for the West African Sahel. Our classifier produces high-resolution and regionally calibrated land cover maps for the Sahel, representing a significant contribution to the data available for this region. Global land cover products are unreliable for the Sahel, and accurate land cover data for the region are sparse. To address this gap, the U.S. Geological Survey and the Regional Center for Agriculture, Hydrology and Meteorology (AGRHYMET) in Niger produced high-quality land cover maps for the region via hand-classification of Landsat images. This method produces highly accurate maps, but the time and labor required constrain the spatial and temporal resolution of the data products. By using these hand-classified maps alongside SVM techniques, we successfully increase the resolution of the land cover maps by 1-2 orders of magnitude, from 2km-decadal resolution to 30m-annual resolution. These high-resolution regionally calibrated land cover datasets, along with the classifier we developed to produce them, lay the foundation for major advances in studies of land surface processes in the region. These datasets will provide more accurate inputs for food security modeling, hydrologic modeling, analyses of land cover change and climate change adaptation efforts. The land cover classification tool we have developed will be publicly available for use in creating additional West Africa land cover datasets with future remote sensing data and can be adapted for use in other parts of the world.

Efficiencies for parts and wholes in biological-motion perception.

PubMed

Bromfield, W Drew; Gold, Jason M

2017-10-01

People can reliably infer the actions, intentions, and mental states of fellow humans from body movements (Blake & Shiffrar, 2007). Previous research on such biological-motion perception has suggested that the movements of the feet may play a particularly important role in making certain judgments about locomotion (Chang & Troje, 2009; Troje & Westhoff, 2006). One account of this effect is that the human visual system may have evolved specialized processes that are efficient for extracting information carried by the feet (Troje & Westhoff, 2006). Alternatively, the motion of the feet may simply be more discriminable than that of other parts of the body. To dissociate these two possibilities, we measured people's ability to discriminate the walking direction of stimuli in which individual body parts (feet, hands) were removed or shown in isolation. We then compared human performance to that of a statistically optimal observer (Gold, Tadin, Cook, & Blake, 2008), giving us a measure of humans' discriminative ability independent of the information available (a quantity known as efficiency). We found that efficiency was highest when the hands and the feet were shown in isolation. A series of follow-up experiments suggested that observers were relying on a form-based cue with the isolated hands (specifically, the orientation of their path through space) and a motion-based cue with the isolated feet to achieve such high efficiencies. We relate our findings to previous proposals of a distinction between form-based and motion-based mechanisms in biological-motion perception.

Enchondromas of the hand: factors affecting recurrence, healing, motion, and malignant transformation.

PubMed

Sassoon, Adam A; Fitz-Gibbon, Patrick D; Harmsen, William S; Moran, Steven L

2012-06-01

Enchondromas represent the most common primary bone tumor in the hand. Despite their frequency, a standardized treatment protocol is lacking. This study examines the outcome of surgically treated enchondromas of the hand with regard to tumor location, graft choice, and presence or absence of fracture. We retrospectively reviewed 102 enchondromas in 80 patients, identified between 1991 and 2008, with a mean clinical follow-up of 38 months. We assessed the effects of age, tumor location, and graft choice on outcomes for all lesions. Patients presenting with Ollier disease, Maffucci syndrome, pathologic fractures, or recurrent disease were separated for additional analysis. Of the 102 lesions, 62 (61%) achieved complete radiographic healing in a median time of 6 months. Full range of motion was achieved following treatment of 68 lesions (67%) in a median time of 3 months. A total of 95 lesions (93%) remained recurrence free following surgery. One case of malignant transformation occurred in a patient with Maffucci syndrome. Tumor location and graft choice did not affect healing grade, time to healing, range of motion, or recurrence rate. Age at presentation greater than 30 was associated with more rapid healing. Monocentric, nonexpanding lesions were associated with improved postoperative range of motion. Patients with a diagnosis of multiple enchondromas had a higher rate of recurrence following surgery, and patients presenting with a recurrent lesion had a higher rate of complications. Following pathologic fracture, no differences in outcomes were observed when enchondromas were treated primarily or following fracture healing. Following surgical treatment of enchondromas in the hand, the majority of patients achieve complete bony healing and full range of motion, regardless of the graft material used. Malignant transformation is rare, and aggressive follow-up measures should be reserved for patients with a diagnosis of multiple enchondromas. Therapeutic IV. Copyright © 2012 American Society for Surgery of the Hand. All rights reserved.

Pisiform excision for pisotriquetral instability and arthritis.

PubMed

Campion, Heather; Goad, Andrea; Rayan, Ghazi; Porembski, Margaret

2014-07-01

To evaluate wrist strength and kinematics after pisiform excision and preservation of its soft tissue confluence for pisotriquetral instability and arthritis. We evaluated 12 patients, (14 wrists) subjectively and objectively an average of 7.5 years after pisiform excision. Three additional patients were interviewed by phone. Subjective evaluation included inquiry about pain and satisfaction with the treatment. Objective testing included measuring wrist flexion and extension range of motion, grip strength, and static and dynamic flexion and ulnar deviation strengths of the operative hand compared with the nonsurgical normal hand. Four patients had concomitant ulnar nerve decompression at the wrist. All patients were satisfied with the outcome. Wrist flexion averaged 99% and wrist extension averaged 95% of the nonsurgical hand. Mean grip strength of the operative hand was 90% of the nonsurgical hand. Mean static flexion strength of the operative hand was 94% of the nonsurgical hand, whereas mean dynamic flexion strength was 113%. Mean static ulnar deviation strength of the operative hand was 87% of the nonsurgical hand. The mean dynamic ulnar deviation strength of the operative hand was 103% of the nonsurgical hand. Soft tissue confluence-preserving pisiform excision relieved pain and retained wrist motion and static and dynamic strength. Associated ulnar nerve compression was a confounding factor that may have affected outcomes. Therapeutic IV. Copyright © 2014 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

[An Introduction to A Newly-developed "Acupuncture Needle Manipulation Training-evaluation System" Based on Optical Motion Capture Technique].

PubMed

Zhang, Ao; Yan, Xing-Ke; Liu, An-Guo

2016-12-25

In the present paper, the authors introduce a newly-developed "Acupuncture Needle Manipulation Training-evaluation System" based on optical motion capture technique. It is composed of two parts, sensor and software, and overcomes some shortages of mechanical motion capture technique. This device is able to analyze the data of operations of the pressing-hand and needle-insertion hand during acupuncture performance and its software contains personal computer (PC) version, Android version, and Internetwork Operating System (IOS) Apple version. It is competent in recording and analyzing information of any ope-rator's needling manipulations, and is quite helpful for teachers in teaching, training and examining students in clinical practice.

Three-Dimensional Motion Estimation Using Shading Information in Multiple Frames

DTIC Science & Technology

1989-09-01

j. Threle-D.imensionai GO Motion Estimation U sing, Shadin g Ilnformation in Multiple Frames- IJean-Pierre Schotf MIT Artifi -cial intelligence...vision 3-D structure 3-D vision- shape from shading multiple frames 20. ABSTRACT (Cofrn11,00 an reysrf* OWd Of Rssss00n7 Ad 4111111& F~ block f)nseq See...motion and shading have been treated as two disjoint problems. On the one hand, researchers studying motion or structure from motion often assume

Improving the Robustness of Real-Time Myoelectric Pattern Recognition against Arm Position Changes in Transradial Amputees

PubMed Central

Geng, Yanjuan; Wei, Yue

2017-01-01

Previous studies have showed that arm position variations would significantly degrade the classification performance of myoelectric pattern-recognition-based prosthetic control, and the cascade classifier (CC) and multiposition classifier (MPC) have been proposed to minimize such degradation in offline scenarios. However, it remains unknown whether these proposed approaches could also perform well in the clinical use of a multifunctional prosthesis control. In this study, the online effect of arm position variation on motion identification was evaluated by using a motion-test environment (MTE) developed to mimic the real-time control of myoelectric prostheses. The performance of different classifier configurations in reducing the impact of arm position variation was investigated using four real-time metrics based on dataset obtained from transradial amputees. The results of this study showed that, compared to the commonly used motion classification method, the CC and MPC configurations improved the real-time performance across seven classes of movements in five different arm positions (8.7% and 12.7% increments of motion completion rate, resp.). The results also indicated that high offline classification accuracy might not ensure good real-time performance under variable arm positions, which necessitated the investigation of the real-time control performance to gain proper insight on the clinical implementation of EMG-pattern-recognition-based controllers for limb amputees. PMID:28523276

Human Actions Analysis: Templates Generation, Matching and Visualization Applied to Motion Capture of Highly-Skilled Karate Athletes

PubMed Central

Piekarczyk, Marcin; Ogiela, Marek R.

2017-01-01

The aim of this paper is to propose and evaluate the novel method of template generation, matching, comparing and visualization applied to motion capture (kinematic) analysis. To evaluate our approach, we have used motion capture recordings (MoCap) of two highly-skilled black belt karate athletes consisting of 560 recordings of various karate techniques acquired with wearable sensors. We have evaluated the quality of generated templates; we have validated the matching algorithm that calculates similarities and differences between various MoCap data; and we have examined visualizations of important differences and similarities between MoCap data. We have concluded that our algorithms works the best when we are dealing with relatively short (2–4 s) actions that might be averaged and aligned with the dynamic time warping framework. In practice, the methodology is designed to optimize the performance of some full body techniques performed in various sport disciplines, for example combat sports and martial arts. We can also use this approach to generate templates or to compare the correct performance of techniques between various top sportsmen in order to generate a knowledge base of reference MoCap videos. The motion template generated by our method can be used for action recognition purposes. We have used the DTW classifier with angle-based features to classify various karate kicks. We have performed leave-one-out action recognition for the Shorin-ryu and Oyama karate master separately. In this case, 100% actions were correctly classified. In another experiment, we used templates generated from Oyama master recordings to classify Shorin-ryu master recordings and vice versa. In this experiment, the overall recognition rate was 94.2%, which is a very good result for this type of complex action. PMID:29125560

The Combined Effects of Adaptive Control and Virtual Reality on Robot-Assisted Fine Hand Motion Rehabilitation in Chronic Stroke Patients: A Case Study.

PubMed

Huang, Xianwei; Naghdy, Fazel; Naghdy, Golshah; Du, Haiping; Todd, Catherine

2018-01-01

Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive training that is needed to trigger neuroplasticity following a stroke. However, the lack of fully adaptive assist-as-needed control of the robotic devices and an inadequate immersive virtual environment that can promote active participation during training are obstacles hindering the achievement of better training results with fewer training sessions required. This study thus focuses on these research gaps by combining these 2 key components into a rehabilitation system, with special attention on the rehabilitation of fine hand motion skills. The effectiveness of the proposed system is tested by conducting clinical trials on a chronic stroke patient and verified through clinical evaluation methods by measuring the key kinematic features such as active range of motion (ROM), finger strength, and velocity. By comparing the pretraining and post-training results, the study demonstrates that the proposed method can further enhance the effectiveness of fine hand motion rehabilitation training by improving finger ROM, strength, and coordination. Copyright © 2018 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Pick a Hand, Any Hand: Mixed-Handedness and Night-Sky Watching in a College Student Sample

ERIC Educational Resources Information Center

Kelly, William E.

2009-01-01

This study explored the relationship between handedness and interest in night-sky watching. University students (N= 128) completed the Edinburgh Handedness Inventory (Oldfield, 1971) and the Noctcaelador Inventory (Kelly, 2004). The findings indicated that mixed-handed participants scored highest on noctcaelador relative to those classified as…

Predicting motion sickness during parabolic flight

NASA Technical Reports Server (NTRS)

Harm, Deborah L.; Schlegel, Todd T.

2002-01-01

BACKGROUND: There are large individual differences in susceptibility to motion sickness. Attempts to predict who will become motion sick have had limited success. In the present study, we examined gender differences in resting levels of salivary amylase and total protein, cardiac interbeat intervals (R-R intervals), and a sympathovagal index and evaluated their potential to correctly classify individuals into two motion sickness severity groups. METHODS: Sixteen subjects (10 men and 6 women) flew four sets of 10 parabolas aboard NASA's KC-135 aircraft. Saliva samples for amylase and total protein were collected preflight on the day of the flight and motion sickness symptoms were recorded during each parabola. Cardiovascular parameters were collected in the supine position 1-5 days before the flight. RESULTS: There were no significant gender differences in sickness severity or any of the other variables mentioned above. Discriminant analysis using salivary amylase, R-R intervals and the sympathovagal index produced a significant Wilks' lambda coefficient of 0.36, p=0.006. The analysis correctly classified 87% of the subjects into the none-mild sickness or the moderate-severe sickness group. CONCLUSIONS: The linear combination of resting levels of salivary amylase, high-frequency R-R interval levels, and a sympathovagal index may be useful in predicting motion sickness severity.

Predicting Motion Sickness During Parabolic Flight

NASA Technical Reports Server (NTRS)

Harm, Deborah L.; Schlegel, Todd T.

2002-01-01

Background: There are large individual differences in susceptibility to motion sickness. Attempts to predict who will become motion sick have had limited success. In the present study we examined gender differences in resting levels of salivary amylase and total protein, cardiac interbeat intervals (R-R intervals), and a sympathovagal index and evaluated their potential to correctly classify individuals into two motion sickness severity groups. Methods: Sixteen subjects (10 men and 6 women) flew 4 sets of 10 parabolas aboard NASA's KC-135 aircraft. Saliva samples for amylase and total protein were collected preflight on the day of the flight and motion sickness symptoms were recorded during each parabola. Cardiovascular parameters were collected in the supine position 1-5 days prior to the flight. Results: There were no significant gender differences in sickness severity or any of the other variables mentioned above. Discriminant analysis using salivary amylase, R-R intervals and the sympathovagal index produced a significant Wilks' lambda coefficient of 0.36, p= 0.006. The analysis correctly classified 87% of the subjects into the none-mild sickness or the moderate-severe sickness group. Conclusions: The linear combination of resting levels of salivary amylase, high frequency R-R interval levels, and a sympathovagal index may be useful in predicting motion sickness severity.

Mapping surface disturbance of energy-related infrastructure in southwest Wyoming--An assessment of methods

USGS Publications Warehouse

Germaine, Stephen S.; O'Donnell, Michael S.; Aldridge, Cameron L.; Baer, Lori; Fancher, Tammy; McBeth, Jamie; McDougal, Robert R.; Waltermire, Robert; Bowen, Zachary H.; Diffendorfer, James; Garman, Steven; Hanson, Leanne

2012-01-01

We evaluated how well three leading information-extraction software programs (eCognition, Feature Analyst, Feature Extraction) and manual hand digitization interpreted information from remotely sensed imagery of a visually complex gas field in Wyoming. Specifically, we compared how each mapped the area of and classified the disturbance features present on each of three remotely sensed images, including 30-meter-resolution Landsat, 10-meter-resolution SPOT (Satellite Pour l'Observation de la Terre), and 0.6-meter resolution pan-sharpened QuickBird scenes. Feature Extraction mapped the spatial area of disturbance features most accurately on the Landsat and QuickBird imagery, while hand digitization was most accurate on the SPOT imagery. Footprint non-overlap error was smallest on the Feature Analyst map of the Landsat imagery, the hand digitization map of the SPOT imagery, and the Feature Extraction map of the QuickBird imagery. When evaluating feature classification success against a set of ground-truthed control points, Feature Analyst, Feature Extraction, and hand digitization classified features with similar success on the QuickBird and SPOT imagery, while eCognition classified features poorly relative to the other methods. All maps derived from Landsat imagery classified disturbance features poorly. Using the hand digitized QuickBird data as a reference and making pixel-by-pixel comparisons, Feature Extraction classified features best overall on the QuickBird imagery, and Feature Analyst classified features best overall on the SPOT and Landsat imagery. Based on the entire suite of tasks we evaluated, Feature Extraction performed best overall on the Landsat and QuickBird imagery, while hand digitization performed best overall on the SPOT imagery, and eCognition performed worst overall on all three images. Error rates for both area measurements and feature classification were prohibitively high on Landsat imagery, while QuickBird was time and cost prohibitive for mapping large spatial extents. The SPOT imagery produced map products that were far more accurate than Landsat and did so at a far lower cost than QuickBird imagery. Consideration of degree of map accuracy required, costs associated with image acquisition, software, operator and computation time, and tradeoffs in the form of spatial extent versus resolution should all be considered when evaluating which combination of imagery and information-extraction method might best serve any given land use mapping project. When resources permit, attaining imagery that supports the highest classification and measurement accuracy possible is recommended.

Motion sickness susceptibility related to ACTH, ADH and TSH

NASA Technical Reports Server (NTRS)

Kohl, R. L.; Leach, C.; Homick, J. L.; Larochelle, F. T.

1983-01-01

The hypothesis that endogenous levels of certain hormones might be indicative of an individual's susceptibility to stressful motion is tested in a comparison of subjects classified as less prone to motion sickness with those of higher susceptibility. The levels of ACTH and vasopressin measured before exposure to stressful motion were twice as high in the less-suceptible group. No significant differences were noted in the levels of angiotensin, aldosterone, or TSH. The differences between the two groups were greater for a given hormone than for any of the changes induced by exposure to stressful motion.

Learning robotic eye-arm-hand coordination from human demonstration: a coupled dynamical systems approach.

PubMed

Lukic, Luka; Santos-Victor, José; Billard, Aude

2014-04-01

We investigate the role of obstacle avoidance in visually guided reaching and grasping movements. We report on a human study in which subjects performed prehensile motion with obstacle avoidance where the position of the obstacle was systematically varied across trials. These experiments suggest that reaching with obstacle avoidance is organized in a sequential manner, where the obstacle acts as an intermediary target. Furthermore, we demonstrate that the notion of workspace travelled by the hand is embedded explicitly in a forward planning scheme, which is actively involved in detecting obstacles on the way when performing reaching. We find that the gaze proactively coordinates the pattern of eye-arm motion during obstacle avoidance. This study provides also a quantitative assessment of the coupling between the eye-arm-hand motion. We show that the coupling follows regular phase dependencies and is unaltered during obstacle avoidance. These observations provide a basis for the design of a computational model. Our controller extends the coupled dynamical systems framework and provides fast and synchronous control of the eyes, the arm and the hand within a single and compact framework, mimicking similar control system found in humans. We validate our model for visuomotor control of a humanoid robot.

Topological Analyses of Symmetric Eruptive Prominences

NASA Astrophysics Data System (ADS)

Panasenco, O.; Martin, S. F.

Erupting prominences (filaments) that we have analyzed from Hα Doppler data at Helio Research and from SOHO/EIT 304 Å, show strong coherency between their chirality, the direction of the vertical and lateral motions of the top of the prominences, and the directions of twisting of their legs. These coherent properties in erupting prominences occur in two patterns of opposite helicity; they constitute a form of dynamic chirality called the ``roll effect." Viewed from the positive network side as they erupt, many symmetrically-erupting dextral prominences develop rolling motion toward the observer along with right-hand helicity in the left leg and left-hand helicity in the right leg. Many symmetricaly-erupting sinistral prominences, also viewed from the positive network field side, have the opposite pattern: rolling motion at the top away from the observer, left-hand helical twist in the left leg, and right-hand twist in the right leg. We have analysed the motions seen in the famous movie of the ``Grand Daddy" erupting prominence and found that it has all the motions that define the roll effect. From our analyses of this and other symmetric erupting prominences, we show that the roll effect is an alternative to the popular hypothetical configuration of an eruptive prominence as a twisted flux rope or flux tube. Instead we find that a simple flat ribbon can be bent such that it reproduces nearly all of the observed forms. The flat ribbon is the most logical beginning topology because observed prominence spines already have this topology prior to eruption and an initial long magnetic ribbon with parallel, non-twisted threads, as a basic form, can be bent into many more and different geometrical forms than a flux rope.

"Dentinal microcracks after root canal preparation" a comparative evaluation with hand, rotary and reciprocating instrumentation.

PubMed

Priya, N Tulasi; Chandrasekhar, Veeramachaneni; Anita, S; Tummala, Muralidhar; Raj, T B Phanindhar; Badami, Vijetha; Kumar, Pradeep; Soujanya, E

2014-12-01

The purpose of this study was to compare the incidence of dentinal micro cracks after instrumentation with various types of NiTi files in rotary and reciprocating motion. One hundred human extracted mandibular central incisors were taken and divided into 10 groups (n=10 teeth per group). Group 1- No preparation, Group 2 - Hand instrumentation, Groups 3,4 - ProTaper files in rotary and reciprocating motion, Groups 5,6 - ProTaper Next files in rotary and reciprocating motion, Groups 7,8 - Oneshape files in rotary and reciprocating motion, Groups 9,10 - Reciproc files in rotary and reciprocating motion. Specimens were sectioned horizontally at 3,6 and 9 mm from the apex and dentinal micro cracks were observed under a stereomicroscope. There was a statistically significant difference between the groups (p<0.05). There were no significant differences in crack formation between the groups (Protaper Next - Rot, Protaper Next - Rec, Reciproc - Rec); (ProTaper - Rot, ProTaper - Rec, Oneshape - Rot), (Oneshape - Rot, Reciproc - Rot), (One shape Reciproc, Reciproc - Rec); (p >.05). Least cracks were seen in canals instrumented with Pro Taper Next files both in rotary and reciprocating motion. Full sequence rotary systems showed less cracks than single file systems and full sequence rotary systems showed less cracks in reciprocating motion than in rotary motion.

Store-and-feedforward adaptive gaming system for hand-finger motion tracking in telerehabilitation.

PubMed

Lockery, Daniel; Peters, James F; Ramanna, Sheela; Shay, Barbara L; Szturm, Tony

2011-05-01

This paper presents a telerehabilitation system that encompasses a webcam and store-and-feedforward adaptive gaming system for tracking finger-hand movement of patients during local and remote therapy sessions. Gaming-event signals and webcam images are recorded as part of a gaming session and then forwarded to an online healthcare content management system (CMS) that separates incoming information into individual patient records. The CMS makes it possible for clinicians to log in remotely and review gathered data using online reports that are provided to help with signal and image analysis using various numerical measures and plotting functions. Signals from a 6 degree-of-freedom magnetic motion tracking system provide a basis for video-game sprite control. The MMT provides a path for motion signals between common objects manipulated by a patient and a computer game. During a therapy session, a webcam that captures images of the hand together with a number of performance metrics provides insight into the quality, efficiency, and skill of a patient.

3D pose estimation and motion analysis of the articulated human hand-forearm limb in an industrial production environment

NASA Astrophysics Data System (ADS)

Hahn, Markus; Barrois, Björn; Krüger, Lars; Wöhler, Christian; Sagerer, Gerhard; Kummert, Franz

2010-09-01

This study introduces an approach to model-based 3D pose estimation and instantaneous motion analysis of the human hand-forearm limb in the application context of safe human-robot interaction. 3D pose estimation is performed using two approaches: The Multiocular Contracting Curve Density (MOCCD) algorithm is a top-down technique based on pixel statistics around a contour model projected into the images from several cameras. The Iterative Closest Point (ICP) algorithm is a bottom-up approach which uses a motion-attributed 3D point cloud to estimate the object pose. Due to their orthogonal properties, a fusion of these algorithms is shown to be favorable. The fusion is performed by a weighted combination of the extracted pose parameters in an iterative manner. The analysis of object motion is based on the pose estimation result and the motion-attributed 3D points belonging to the hand-forearm limb using an extended constraint-line approach which does not rely on any temporal filtering. A further refinement is obtained using the Shape Flow algorithm, a temporal extension of the MOCCD approach, which estimates the temporal pose derivative based on the current and the two preceding images, corresponding to temporal filtering with a short response time of two or at most three frames. Combining the results of the two motion estimation stages provides information about the instantaneous motion properties of the object. Experimental investigations are performed on real-world image sequences displaying several test persons performing different working actions typically occurring in an industrial production scenario. In all example scenes, the background is cluttered, and the test persons wear various kinds of clothes. For evaluation, independently obtained ground truth data are used. [Figure not available: see fulltext.

Bilayer segmentation of webcam videos using tree-based classifiers.

PubMed

Yin, Pei; Criminisi, Antonio; Winn, John; Essa, Irfan

2011-01-01

This paper presents an automatic segmentation algorithm for video frames captured by a (monocular) webcam that closely approximates depth segmentation from a stereo camera. The frames are segmented into foreground and background layers that comprise a subject (participant) and other objects and individuals. The algorithm produces correct segmentations even in the presence of large background motion with a nearly stationary foreground. This research makes three key contributions: First, we introduce a novel motion representation, referred to as "motons," inspired by research in object recognition. Second, we propose estimating the segmentation likelihood from the spatial context of motion. The estimation is efficiently learned by random forests. Third, we introduce a general taxonomy of tree-based classifiers that facilitates both theoretical and experimental comparisons of several known classification algorithms and generates new ones. In our bilayer segmentation algorithm, diverse visual cues such as motion, motion context, color, contrast, and spatial priors are fused by means of a conditional random field (CRF) model. Segmentation is then achieved by binary min-cut. Experiments on many sequences of our videochat application demonstrate that our algorithm, which requires no initialization, is effective in a variety of scenes, and the segmentation results are comparable to those obtained by stereo systems.

Multisensory visual servoing by a neural network.

PubMed

Wei, G Q; Hirzinger, G

1999-01-01

Conventional computer vision methods for determining a robot's end-effector motion based on sensory data needs sensor calibration (e.g., camera calibration) and sensor-to-hand calibration (e.g., hand-eye calibration). This involves many computations and even some difficulties, especially when different kinds of sensors are involved. In this correspondence, we present a neural network approach to the motion determination problem without any calibration. Two kinds of sensory data, namely, camera images and laser range data, are used as the input to a multilayer feedforward network to associate the direct transformation from the sensory data to the required motions. This provides a practical sensor fusion method. Using a recursive motion strategy and in terms of a network correction, we relax the requirement for the exactness of the learned transformation. Another important feature of our work is that the goal position can be changed without having to do network retraining. Experimental results show the effectiveness of our method.

"Digit Anatomy": A New Technique for Learning Anatomy Using Motor Memory

ERIC Educational Resources Information Center

Oh, Chang-Seok; Won, Hyung-Sun; Kim, Kyong-Jee; Jang, Dong-Su

2011-01-01

Gestural motions of the hands and fingers are powerful tools for expressing meanings and concepts, and the nervous system has the capacity to retain multiple long-term motor memories, especially including movements of the hands. We developed many sets of successive movements of both hands, referred to as "digit anatomy," and made…

Categorization of compensatory motions in transradial myoelectric prosthesis users.

PubMed

Hussaini, Ali; Zinck, Arthur; Kyberd, Peter

2017-06-01

Prosthesis users perform various compensatory motions to accommodate for the loss of the hand and wrist as well as the reduced functionality of a prosthetic hand. Investigate different compensation strategies that are performed by prosthesis users. Comparative analysis. A total of 20 able-bodied subjects and 4 prosthesis users performed a set of bimanual activities. Movements of the trunk and head were recorded using a motion capture system and a digital video recorder. Clinical motion angles were calculated to assess the compensatory motions made by the prosthesis users. The video recording also assisted in visually identifying the compensations. Compensatory motions by the prosthesis users were evident in the tasks performed (slicing and stirring activities) as compared to the benchmark of able-bodied subjects. Compensations took the form of a measured increase in range of motion, an observed adoption of a new posture during task execution, and prepositioning of items in the workspace prior to initiating a given task. Compensatory motions were performed by prosthesis users during the selected tasks. These can be categorized into three different types of compensations. Clinical relevance Proper identification and classification of compensatory motions performed by prosthesis users into three distinct forms allows clinicians and researchers to accurately identify and quantify movement. It will assist in evaluating new prosthetic interventions by providing distinct terminology that is easily understood and can be shared between research institutions.

Preliminary evaluation of SensHand V1 in assessing motor skills performance in Parkinson disease.

PubMed

Cavallo, Filippo; Esposito, Dario; Rovini, Erika; Aquilano, Michela; Carrozza, Maria Chiara; Dario, Paolo; Maremmani, Carlo; Bongioanni, Paolo

2013-06-01

Nowadays, the increasing old population 65+ as well as the pace imposed by work activities lead to a high number of people that have particular injuries for limbs. In addition to persistent or temporary disabilities related to accidental injuries we must take into account that part of the population suffers from motor deficits of the hands due to stroke or diseases of various clinical nature. The most recurrent technological solutions to measure the rehabilitation or skill motor performance of the hand are glove-based devices, able to faithfully capture the movements of the hand and fingers. This paper presents a system for hand motion analysis based on 9-axis complete inertial modules and dedicated microcontroller which are fixed on fingers and forearm. The technological solution presented is able to track the patients' hand motions in real-time and then to send data through wireless communication reducing the clutter and the disadvantages of a glove equipped with sensors through a different technological structure. The device proposed has been tested in the study of Parkinson's disease.

Active range of motion outcomes after reconstruction of burned wrist and hand deformities.

PubMed

Afifi, Ahmed M; Mahboub, Tarek A; Ibrahim Fouad, Amr; Azari, Kodi; Khalil, Haitham H; McCarthy, James E

2016-06-01

This works aim is to evaluate the efficacy of skin grafts and flaps in reconstruction of post-burn hand and wrist deformities. A prospective study of 57 burn contractures of the wrist and dorsum of the hand was performed. Flaps were used only if there was a non-vascularized structure after contracture release, otherwise a skin graft was used. Active range of motion (ROM) was used to assess hand function. The extension deformity cohort uniformly underwent skin graft following contracture release with a mean improvement of 71 degrees (p<0.0001). The flexion deformity cohort was treated with either skin grafts (8 patients) or flaps (9 patients) with a mean improvement of 44 degrees (p<0.0001). Skin grafts suffice for dorsal hand contractures to restore functional wrist ROM. For flexion contractures, flaps were more likely for contractures >6 months. Early release of burn contracture is advisable to avoid deep structure contracture. Copyright © 2016 Elsevier Ltd and ISBI. All rights reserved.

All about Motion & Balance. Physical Science for Children[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

Walking on a balance beam or riding a bike both require motion and balance. This program will reveal how unbalanced forces create motion, while balanced forces keep things still. Students also learn how concepts like velocity, acceleration, and momentum fit into this puzzle. A unique hands-on activity combined with vivid imagery and graphics…

Reach-to-grasp movement as a minimization process.

PubMed

Yang, Fang; Feldman, Anatol G

2010-02-01

It is known that hand transport and grasping are functionally different but spatially coordinated components of reach-to-grasp (RTG) movements. As an extension of this notion, we suggested that body segments involved in RTG movements are controlled as a coherent ensemble by a global minimization process associated with the necessity for the hand to reach the motor goal. Different RTG components emerge following this process without pre-programming. Specifically, the minimization process may result from the tendency of neuromuscular elements to diminish the spatial gap between the actual arm-hand configuration and its virtual (referent) configuration specified by the brain. The referent configuration is specified depending on the object shape, localization, and orientation. Since the minimization process is gradual, it can be interrupted and resumed following mechanical perturbations, at any phase during RTG movements, including hand closure. To test this prediction of the minimization hypothesis, we asked subjects to reach and grasp a cube placed within the reach of the arm. Vision was prevented during movement until the hand returned to its initial position. As predicted, by arresting wrist motion at different points of hand transport in randomly selected trials, it was possible to halt changes in hand aperture at any phase, not only during hand opening but also during hand closure. Aperture changes resumed soon after the wrist was released. Another test of the minimization hypothesis was made in RTG movements to an object placed beyond the reach of the arm. It has previously been shown (Rossi et al. in J Physiol 538:659-671, 2002) that in such movements, the trunk motion begins to contribute to hand transport only after a critical phase when the shifts in the referent arm configuration have finished (at about the time when hand velocity is maximal). The minimization rule suggests that when the virtual contribution of the arm to hand transport is completed, guidance of hand aperture switches from the arm to the trunk control system. As a consequence, hand aperture changes can be halted by trunk arrests but only if they are prolonged beyond a critical phase. As predicted, hand transport and hand aperture in RTG movements beyond the reach of the arm were halted by trunk arrests only if they were prolonged beyond the time of peak hand velocity. Hand motion and aperture changes resumed only when the trunk was released. While supporting the minimization hypothesis, our findings imply that not only spatial but also temporal characteristics of each component, including the shortest, hand closure component of RTG movements, are controlled in a flexible, task-specific way.

Quantitative Tester And Reconditioner For Hand And Arm

NASA Technical Reports Server (NTRS)

Engle, Gary; Bond, Malcolm; Naumann, Theodore

1993-01-01

Apparatus measures torques, forces, and motions of hand, wrist, forearm, elbow, and shoulder and aids in reconditioning muscles involved. Used to determine strengths and endurances of muscles, ranges of motion of joints, and reaction times. Provides quantitative data used to assess extent to which disuse, disease, or injury causes deterioration of muscles and of motor-coordination skills. Same apparatus serves as exercise machine to restore muscle performance by imposing electronically controlled, gradually increasing loads on muscles. Suitable for training and evaluating astronauts, field testing for workers' compensation claims, and physical therapy in hospitals. With aid of various attachments, system adapted to measure such special motions as pinching, rotation of wrist, and supination and pronation of the forearm. Attachments are gloves, wristlets, and sleeves.

Clinical effects of using HEXORR (Hand Exoskeleton Rehabilitation Robot) for movement therapy in stroke rehabilitation.

PubMed

Godfrey, Sasha Blue; Holley, Rahsaan J; Lum, Peter S

2013-11-01

The goals of this pilot study were to quantify the clinical benefits of using the Hand Exoskeleton Rehabilitation Robot for hand rehabilitation after stroke and to determine the population best served by this intervention. Nine subjects with chronic stroke (one excluded from analysis) completed 18 sessions of training with the Hand Exoskeleton Rehabilitation Robot and a preevaluation, a postevaluation, and a 90-day clinical evaluation. Overall, the subjects improved in both range of motion and clinical measures. Compared with the preevaluation, the subjects showed significant improvements in range of motion, grip strength, and the hand component of the Fugl-Meyer (mean changes, 6.60 degrees, 8.84 percentage points, and 1.86 points, respectively). A subgroup of six subjects exhibited lower tone and received a higher dosage of training. These subjects had significant gains in grip strength, the hand component of the Fugl-Meyer, and the Action Research Arm Test (mean changes, 8.42 percentage points, 2.17 points, and 2.33 points, respectively). Future work is needed to better manage higher levels of hypertonia and provide more support to subjects with higher impairment levels; however, the current results support further study into the Hand Exoskeleton Rehabilitation Robot treatment.

Hand Grasping Synergies As Biometrics

PubMed Central

Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K.; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana

2017-01-01

Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies—postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security. PMID:28512630

Comparison of dominant hand range of motion among throwing types in baseball pitchers.

PubMed

Wang, Lin-Hwa; Kuo, Li-Chieh; Shih, Sheng-Wen; Lo, Kuo-Cheng; Su, Fong-Chin

2013-08-01

Previous research on baseball pitchers' wrists, elbows, and should joints contributes to our understanding of pitchers' control over delicate joint motion and ball release. However, limited research on forearm, wrist, and hand joints prevents full comprehension of the throwing mechanism. The present descriptive laboratory study quantifies angular performances of hand and wrist joints while pitching breaking balls, including fastballs, curveballs and sliders, among pitchers with different skill levels. Nineteen baseball pitchers performed required pitching tasks (10 from university and 9 from high school). A three-dimensional motion analysis system collected pitching motion data. The range of joint motion in the wrist and proximal interphalangeal (PIP) and metacarpophalangeal (MP) joints of the index and middle fingers were compared among fastballs, curveballs and sliders. Thirteen reflective markers were placed on selected anatomic landmarks of the wrist, middle and index fingers of the hand. Wrist flexion angle in the pitching acceleration phase was larger in fastballs (20.58±4.07°) and sliders (22.48±5.45°) than in curveballs (9.08±3.03°) (p = .001). The flexion angle of the PIP joint was significantly larger in curveballs (38.5±3.8°) than in fastballs (30.3±4.8°) and sliders (30.2±4.5°) (p=.004) of the middle finger. Abduction angle of MP joint on the middle finger was significantly larger in curveballs (15.4 ±3.6°) than in fastballs (8.9±1.2°) and sliders (6.9±2.9°) (p=.001) of the middle finger, and the abduction angle of index finger was significantly larger in sliders (13.5±15.0°) than in fastballs (7.2 ±2.8°) (p=.007). Hand and wrist motion and grip types affect the relative position between fingers and ball, which produces different types of baseball pitches. A larger extension angle of the wrist joint and the coordination of middle and index fingers are crucial when pitching a fastball. Abduction and flexion movement on the MP joint of the middle finger are important for a curveball. MP joint abduction and flexion movement of the index finger produce sliders. Understanding the control mechanism in a throwing hand can help improve training protocols in either injury prevention or performance improvement for baseball pitchers. Copyright © 2013 Elsevier B.V. All rights reserved.

Adapted cuing technique: facilitating sequential phoneme production.

PubMed

Klick, S L

1994-09-01

ACT is a visual cuing technique designed to facilitate dyspraxic speech by highlighting the sequential production of phonemes. In using ACT, cues are presented in such a way as to suggest sequential, coarticulatory movement in an overall pattern of motion. While using ACT, the facilitator's hand moves forward and back along the side of her (or his) own face. Finger movements signal specific speech sounds in formations loosely based on the manual alphabet for the hearing impaired. The best movements suggest the flowing, interactive nature of coarticulated phonemes. The synergistic nature of speech is suggested by coordinated hand motions which tighten and relax, move quickly or slowly, reflecting the motions of the vocal tract at various points during production of phonemic sequences. General principles involved in using ACT include a primary focus on speech-in-motion, the monitoring and fading of cues, and the presentation of stimuli based on motor-task analysis of phonemic sequences. Phonemic sequences are cued along three dimensions: place, manner, and vowel-related mandibular motion. Cuing vowels is a central feature of ACT. Two parameters of vowel production, focal point of resonance and mandibular closure, are cued. The facilitator's hand motions reflect the changing shape of the vocal tract and the trajectory of the tongue that result from the coarticulation of vowels and consonants. Rigid presentation of the phonemes is secondary to the facilitator's primary focus on presenting the overall sequential movement. The facilitator's goal is to self-tailor ACT in response to the changing needs and abilities of the client.(ABSTRACT TRUNCATED AT 250 WORDS)

Hazardous materials emergency response mobile robot

NASA Technical Reports Server (NTRS)

Stone, Henry W. (Inventor); Lloyd, James (Inventor); Alahuzos, George (Inventor)

1992-01-01

A simple or unsophisticated robot incapable of effecting straight-line motion at the end of its arm inserts a key held in its end effector or hand into a door lock with nearly straight-line motion by gently thrusting its back heels downwardly so that it pivots forwardly on its front toes while holding its arm stationary. The relatively slight arc traveled by the robot's hand is compensated by a complaint tool with which the robot hand grips the door key. A visible beam is projected through the axis of the hand or gripper on the robot arm end at an angle to the general direction in which the robot thrusts the gripper forward. As the robot hand approaches a target surface, a video camera on the robot wrist watches the beam spot on the target surface fall from a height proportional to the distance between the robot hand and the target surface until the beam spot is nearly aligned with the top of the robot hand. Holes in the front face of the hand are connected through internal passages inside the arm to an on-board chemical sensor. Full rotation of the hand or gripper about the robot arm's wrist is made possible by slip rings in the wrist which permit passage of the gases taken in through the nose holes in the front of the hand through the wrist regardless of the rotational orientation of the wrist.

Spatial Alignment and Response Hand in Geometric and Motion Illusions

PubMed Central

Scocchia, Lisa; Paroli, Michela; Stucchi, Natale A.; Sedda, Anna

2017-01-01

Perception of visual illusions is susceptible to manipulation of their spatial properties. Further, illusions can sometimes affect visually guided actions, especially the movement planning phase. Remarkably, visual properties of objects related to actions, such as affordances, can prime more accurate perceptual judgements. In spite of the amount of knowledge available on affordances and on the influence of illusions on actions (or lack of thereof), virtually nothing is known about the reverse: the influence of action-related parameters on the perception of visual illusions. Here, we tested a hypothesis that the response mode (that can be linked to action-relevant features) can affect perception of the Poggendorff (geometric) and of the Vanishing Point (motion) illusion. We explored the role of hand dominance (right dominant versus left non-dominant hand) and its interaction with stimulus spatial alignment (i.e., congruency between visual stimulus and the hand used for responses). Seventeen right-handed participants performed our tasks with their right and left hands, and the stimuli were presented in regular and mirror-reversed views. It turned out that the regular version of the Poggendorff display generates a stronger illusion compared to the mirror version, and that participants are less accurate and show more variability when they use their left hand in responding to the Vanishing Point. In summary, our results show that there is a marginal effect of hand precision in motion related illusions, which is absent for geometrical illusions. In the latter, attentional anisometry seems to play a greater role in generating the illusory effect. Taken together, our findings suggest that changes in the response mode (here: manual action-related parameters) do not necessarily affect illusion perception. Therefore, although intuitively speaking there should be at least unidirectional effects of perception on action, and possible interactions between the two systems, this simple study still suggests their relative independence, except for the case when the less skilled (non-dominant) hand and arguably more deliberate responses are used. PMID:28769830

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Grasp posture alters visual processing biases near the hands

PubMed Central

Thomas, Laura E.

2015-01-01

Observers experience biases in visual processing for objects within easy reach of their hands that may assist them in evaluating items that are candidates for action. I investigated the hypothesis that hand postures affording different types of actions differentially bias vision. Across three experiments, participants performed global motion detection and global form perception tasks while their hands were positioned a) near the display in a posture affording a power grasp, b) near the display in a posture affording a precision grasp, or c) in their laps. Although the power grasp posture facilitated performance on the motion task, the precision grasp posture instead facilitated performance on the form task. These results suggest that the visual system weights processing based on an observer’s current affordances for specific actions: fast and forceful power grasps enhance temporal sensitivity, while detail-oriented precision grasps enhance spatial sensitivity. PMID:25862545

Development of Kinematic Graphs of Median Nerve during Active Finger Motion: Implications of Smartphone Use

PubMed Central

2016-01-01

Background Certain hand activities cause deformation and displacement of the median nerve at the carpal tunnel due to the gliding motion of tendons surrounding it. As smartphone usage escalates, this raises the public’s concern whether hand activities while using smartphones can lead to median nerve problems. Objective The aims of this study were to 1) develop kinematic graphs and 2) investigate the associated deformation and rotational information of median nerve in the carpal tunnel during hand activities. Methods Dominant wrists of 30 young adults were examined with ultrasonography by placing a transducer transversely on their wrist crease. Ultrasound video clips were recorded when the subject performing 1) thumb opposition with the wrist in neutral position, 2) thumb opposition with the wrist in ulnar deviation and 3) pinch grip with the wrist in neutral position. Six still images that were separated by 0.2-second intervals were then captured from the ultrasound video for the determination of 1) cross-sectional area (CSA), 2) flattening ratio (FR), 3) rotational displacement (RD) and 4) translational displacement (TD) of median nerve in the carpal tunnel, and these collected information of deformation, rotational and displacement of median nerve were compared between 1) two successive time points during a single hand activity and 2) different hand motions at the same time point. Finally, kinematic graphs were constructed to demonstrate the mobility of median nerve during different hand activities. Results Performing different hand activities during this study led to a gradual reduction in CSA of the median nerve, with thumb opposition together with the wrist in ulnar deviation causing the greatest extent of deformation of the median nerve. Thumb opposition with the wrist in ulnar deviation also led to the largest extent of TD when compared to the other two hand activities of this study. Kinematic graphs showed that the motion pathways of median nerve during different hand activities were complex. Conclusion We observed that the median nerve in the carpal tunnel was rotated, deformed and displaced during the hand activities that people may be performed when using a smartphone, suggesting an increased risk of carpal tunnel syndrome (CTS). In addition, the kinematic graphs of median nerve developed in the present study provide new clues for further studies on the pathophysiology of CTS, and alerting smartphone users to establish proper postural habits when using handheld electronic devices. PMID:27367447

Spacetime-bridge solutions in vacuum gravity

NASA Astrophysics Data System (ADS)

Sengupta, Sandipan

2017-11-01

Vacuum spacetime solutions, which are representations of a bridgelike geometry, are constructed as purely geometric sources of curvature in gravity theory. These configurations satisfy the first-order equations of motion everywhere. Each of them consists of two identical sheets of asymptotically flat geometry, connected by a region of finite extension where the tetrad is noninvertible. The solutions can be classified into nonstatic and static spacetimes. The first class represents a single causal universe equipped (locally) with a timelike coordinate everywhere. The latter, on the other hand, could be interpreted as a sum of two self-contained universes which are causally disconnected. These geometries, even though they have different metrical dimensions in the regions within and away from the bridge, are regular. This is reflected through the associated gauge-covariant fields, which are continuous across the hypersurfaces connecting the invertible and noninvertible phases of the tetrad and are finite everywhere. These vacuum bridge solutions have no analogue in the Einsteinian theory of gravity.

Registration-based segmentation with articulated model from multipostural magnetic resonance images for hand bone motion animation.

PubMed

Chen, Hsin-Chen; Jou, I-Ming; Wang, Chien-Kuo; Su, Fong-Chin; Sun, Yung-Nien

2010-06-01

The quantitative measurements of hand bones, including volume, surface, orientation, and position are essential in investigating hand kinematics. Moreover, within the measurement stage, bone segmentation is the most important step due to its certain influences on measuring accuracy. Since hand bones are small and tubular in shape, magnetic resonance (MR) imaging is prone to artifacts such as nonuniform intensity and fuzzy boundaries. Thus, greater detail is required for improving segmentation accuracy. The authors then propose using a novel registration-based method on an articulated hand model to segment hand bones from multipostural MR images. The proposed method consists of the model construction and registration-based segmentation stages. Given a reference postural image, the first stage requires construction of a drivable reference model characterized by hand bone shapes, intensity patterns, and articulated joint mechanism. By applying the reference model to the second stage, the authors initially design a model-based registration pursuant to intensity distribution similarity, MR bone intensity properties, and constraints of model geometry to align the reference model to target bone regions of the given postural image. The authors then refine the resulting surface to improve the superimposition between the registered reference model and target bone boundaries. For each subject, given a reference postural image, the proposed method can automatically segment all hand bones from all other postural images. Compared to the ground truth from two experts, the resulting surface image had an average margin of error within 1 mm (mm) only. In addition, the proposed method showed good agreement on the overlap of bone segmentations by dice similarity coefficient and also demonstrated better segmentation results than conventional methods. The proposed registration-based segmentation method can successfully overcome drawbacks caused by inherent artifacts in MR images and obtain more accurate segmentation results automatically. Moreover, realistic hand motion animations can be generated based on the bone segmentation results. The proposed method is found helpful for understanding hand bone geometries in dynamic postures that can be used in simulating 3D hand motion through multipostural MR images.

Effects of rehabilitative interventions on pain, function and physical impairments in people with hand osteoarthritis: a systematic review

PubMed Central

2011-01-01

Introduction Hand osteoarthritis (OA) is associated with pain, reduced grip strength, loss of range of motion and joint stiffness leading to impaired hand function and difficulty with daily activities. The effectiveness of different rehabilitation interventions on specific treatment goals has not yet been fully explored. The objective of this systematic review is to provide evidence based knowledge on the treatment effects of different rehabilitation interventions for specific treatment goals for hand OA. Methods A computerized literature search of Medline, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ISI Web of Science, the Physiotherapy Evidence Database (PEDro) and SCOPUS was performed. Studies that had an evidence level of 2b or higher and that compared a rehabilitation intervention with a control group and assessed at least one of the following outcome measures - pain, physical hand function or other measures of hand impairment - were included. The eligibility and methodological quality of trials were systematically assessed by two independent reviewers using the PEDro scale. Treatment effects were calculated using standardized mean difference and 95% confidence intervals. Results Ten studies, of which six were of higher quality (PEDro score >6), were included. The rehabilitation techniques reviewed included three studies on exercise, two studies each on laser and heat, and one study each on splints, massage and acupuncture. One higher quality trial showed a large positive effect of 12-month use of a night splint on hand pain, function, strength and range of motion. Exercise had no effect on hand pain or function although it may be able to improve hand strength. Low level laser therapy may be useful for improving range of motion. No rehabilitation interventions were found to improve stiffness. Conclusions There is emerging high quality evidence to support that rehabilitation interventions can offer significant benefits to individuals with hand OA. A summary of the higher quality evidence is provided to assist with clinical decision making based on current evidence. Further high-quality research is needed concerning the effects of rehabilitation interventions on specific treatment goals for hand OA. PMID:21332991

The right inhibition? Callosal correlates of hand performance in healthy children and adolescents callosal correlates of hand performance.

PubMed

Kurth, Florian; Mayer, Emeran A; Toga, Arthur W; Thompson, Paul M; Luders, Eileen

2013-09-01

Numerous studies suggest that interhemispheric inhibition-relayed via the corpus callosum-plays an important role in unilateral hand motions. Interestingly, transcallosal inhibition appears to be indicative of a strong laterality effect, where generally the dominant hemisphere exerts inhibition on the nondominant one. These effects have been largely identified through functional studies in adult populations, but links between motor performance and callosal structure (especially during sensitive periods of neurodevelopment) remain largely unknown. We therefore investigated correlations between Purdue Pegboard performance (a test of motor function) and local callosal thickness in 170 right-handed children and adolescents (mean age: 11.5 ± 3.4 years; range, 6-17 years). Better task performance with the right (dominant) hand was associated with greater callosal thickness in isthmus and posterior midbody. Task performance using both hands yielded smaller and less significant correlations in the same regions, while task performance using the left (nondominant) hand showed no significant correlations with callosal thickness. There were no significant interactions with age and sex. These links between motor performance and callosal structure may constitute the neural correlate of interhemispheric inhibition, which is thought to be necessary for fast and complex unilateral motions and to be biased towards the dominant hand. Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.

Visuokinesthetic Perception of Hand Movement is Mediated by Cerebro–Cerebellar Interaction between the Left Cerebellum and Right Parietal Cortex

PubMed Central

Hagura, Nobuhiro; Oouchida, Yutaka; Aramaki, Yu; Okada, Tomohisa; Matsumura, Michikazu; Sadato, Norihiro

2009-01-01

Combination of visual and kinesthetic information is essential to perceive bodily movements. We conducted behavioral and functional magnetic resonance imaging experiments to investigate the neuronal correlates of visuokinesthetic combination in perception of hand movement. Participants experienced illusory flexion movement of their hand elicited by tendon vibration while they viewed video-recorded flexion (congruent: CONG) or extension (incongruent: INCONG) motions of their hand. The amount of illusory experience was graded by the visual velocities only when visual information regarding hand motion was concordant with kinesthetic information (CONG). The left posterolateral cerebellum was specifically recruited under the CONG, and this left cerebellar activation was consistent for both left and right hands. The left cerebellar activity reflected the participants' intensity of illusory hand movement under the CONG, and we further showed that coupling of activity between the left cerebellum and the “right” parietal cortex emerges during this visuokinesthetic combination/perception. The “left” cerebellum, working with the anatomically connected high-order bodily region of the “right” parietal cortex, participates in online combination of exteroceptive (vision) and interoceptive (kinesthesia) information to perceive hand movement. The cerebro–cerebellar interaction may underlie updating of one's “body image,” when perceiving bodily movement from visual and kinesthetic information. PMID:18453537

Automatic detection of a hand-held needle in ultrasound via phased-based analysis of the tremor motion

NASA Astrophysics Data System (ADS)

Beigi, Parmida; Salcudean, Septimiu E.; Rohling, Robert; Ng, Gary C.

2016-03-01

This paper presents an automatic localization method for a standard hand-held needle in ultrasound based on temporal motion analysis of spatially decomposed data. Subtle displacement arising from tremor motion has a periodic pattern which is usually imperceptible in the intensity image but may convey information in the phase image. Our method aims to detect such periodic motion of a hand-held needle and distinguish it from intrinsic tissue motion, using a technique inspired by video magnification. Complex steerable pyramids allow specific design of the wavelets' orientations according to the insertion angle as well as the measurement of the local phase. We therefore use steerable pairs of even and odd Gabor wavelets to decompose the ultrasound B-mode sequence into various spatial frequency bands. Variations of the local phase measurements in the spatially decomposed input data is then temporally analyzed using a finite impulse response bandpass filter to detect regions with a tremor motion pattern. Results obtained from different pyramid levels are then combined and thresholded to generate the binary mask input for the Hough transform, which determines an estimate of the direction angle and discards some of the outliers. Polynomial fitting is used at the final stage to remove any remaining outliers and improve the trajectory detection. The detected needle is finally added back to the input sequence as an overlay of a cloud of points. We demonstrate the efficiency of our approach to detect the needle using subtle tremor motion in an agar phantom and in-vivo porcine cases where intrinsic motion is also present. The localization accuracy was calculated by comparing to expert manual segmentation, and presented in (mean, standard deviation and root-mean-square error) of (0.93°, 1.26° and 0.87°) and (1.53 mm, 1.02 mm and 1.82 mm) for the trajectory and the tip, respectively.

Quantifying technical skills during open operations using video-based motion analysis.

PubMed

Glarner, Carly E; Hu, Yue-Yung; Chen, Chia-Hsiung; Radwin, Robert G; Zhao, Qianqian; Craven, Mark W; Wiegmann, Douglas A; Pugh, Carla M; Carty, Matthew J; Greenberg, Caprice C

2014-09-01

Objective quantification of technical operative skills in surgery remains poorly defined, although the delivery of and training in these skills is essential to the profession of surgery. Attempts to measure hand kinematics to quantify operative performance primarily have relied on electromagnetic sensors attached to the surgeon's hand or instrument. We sought to determine whether a similar motion analysis could be performed with a marker-less, video-based review, allowing for a scalable approach to performance evaluation. We recorded six reduction mammoplasty operations-a plastic surgery procedure in which the attending and resident surgeons operate in parallel. Segments representative of surgical tasks were identified with Multimedia Video Task Analysis software. Video digital processing was used to extract and analyze the spatiotemporal characteristics of hand movement. Attending plastic surgeons appear to use their nondominant hand more than residents when cutting with the scalpel, suggesting more use of countertraction. While suturing, attendings were more ambidextrous, with smaller differences in movement between their dominant and nondominant hands than residents. Attendings also seem to have more conservation of movement when performing instrument tying than residents, as demonstrated by less nondominant hand displacement. These observations were consistent within procedures and between the different attending plastic surgeons evaluated in this fashion. Video motion analysis can be used to provide objective measurement of technical skills without the need for sensors or markers. Such data could be valuable in better understanding the acquisition and degradation of operative skills, providing enhanced feedback to shorten the learning curve. Copyright © 2014 Mosby, Inc. All rights reserved.

Rehabilitation of flexor and extensor tendon injuries in the hand: current updates.

PubMed

Howell, Julianne W; Peck, Fiona

2013-03-01

In recent years, a significant amount of research in the field of tendon injury in the hand has contributed to advances in both surgical and rehabilitation techniques. The introduction of early motion has improved tendon healing, reduced complications, and enhanced final outcomes. There is overwhelming evidence to show that carefully devised rehabilitation programs are critical to achieving favourable outcomes. Whatever the type, or level, of flexor or extensor injury, the ultimate goal of both the surgeon and therapist is to protect the repair, modify peritendinous adhesions, promote optimal tendon excursion and preserve joint motion. Early tendon motion regimens are initiated at surgery or within 5 days post repair. Intra-operative information from the surgeon to the therapist is vital to the choice of splint protected position to reduce repair rupture/gap forces, and to commencement of active, or splint controlled, motion for tendon excursion. Decisions should align with the phases of healing, the clinician's observations, frequent range of motion measurements and patient input. Clinical concepts pertinent to early motion rehabilitation decisions are presented by zone of injury for both flexor and extensor tendons during the early phases of healing. Copyright © 2013. Published by Elsevier Ltd.

Event Recognition for Contactless Activity Monitoring Using Phase-Modulated Continuous Wave Radar.

PubMed

Forouzanfar, Mohamad; Mabrouk, Mohamed; Rajan, Sreeraman; Bolic, Miodrag; Dajani, Hilmi R; Groza, Voicu Z

2017-02-01

The use of remote sensing technologies such as radar is gaining popularity as a technique for contactless detection of physiological signals and analysis of human motion. This paper presents a methodology for classifying different events in a collection of phase modulated continuous wave radar returns. The primary application of interest is to monitor inmates where the presence of human vital signs amidst different, interferences needs to be identified. A comprehensive set of features is derived through time and frequency domain analyses of the radar returns. The Bhattacharyya distance is used to preselect the features with highest class separability as the possible candidate features for use in the classification process. The uncorrelated linear discriminant analysis is performed to decorrelate, denoise, and reduce the dimension of the candidate feature set. Linear and quadratic Bayesian classifiers are designed to distinguish breathing, different human motions, and nonhuman motions. The performance of these classifiers is evaluated on a pilot dataset of radar returns that contained different events including breathing, stopped breathing, simple human motions, and movement of fan and water. Our proposed pattern classification system achieved accuracies of up to 93% in stationary subject detection, 90% in stop-breathing detection, and 86% in interference detection. Our proposed radar pattern recognition system was able to accurately distinguish the predefined events amidst interferences. Besides inmate monitoring and suicide attempt detection, this paper can be extended to other radar applications such as home-based monitoring of elderly people, apnea detection, and home occupancy detection.

A new approach to hand-based authentication

NASA Astrophysics Data System (ADS)

Amayeh, G.; Bebis, G.; Erol, A.; Nicolescu, M.

2007-04-01

Hand-based authentication is a key biometric technology with a wide range of potential applications both in industry and government. Traditionally, hand-based authentication is performed by extracting information from the whole hand. To account for hand and finger motion, guidance pegs are employed to fix the position and orientation of the hand. In this paper, we consider a component-based approach to hand-based verification. Our objective is to investigate the discrimination power of different parts of the hand in order to develop a simpler, faster, and possibly more accurate and robust verification system. Specifically, we propose a new approach which decomposes the hand in different regions, corresponding to the fingers and the back of the palm, and performs verification using information from certain parts of the hand only. Our approach operates on 2D images acquired by placing the hand on a flat lighting table. Using a part-based representation of the hand allows the system to compensate for hand and finger motion without using any guidance pegs. To decompose the hand in different regions, we use a robust methodology based on morphological operators which does not require detecting any landmark points on the hand. To capture the geometry of the back of the palm and the fingers in suffcient detail, we employ high-order Zernike moments which are computed using an effcient methodology. The proposed approach has been evaluated on a database of 100 subjects with 10 images per subject, illustrating promising performance. Comparisons with related approaches using the whole hand for verification illustrate the superiority of the proposed approach. Moreover, qualitative comparisons with state-of-the-art approaches indicate that the proposed approach has comparable or better performance.

Advanced dexterous manipulation for IED defeat : report on the feasibility of using the ShadowHand for remote operations.

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

Anderson, Robert J.

2011-01-01

Improvised Explosive Device (IED) defeat (IEDD) operations can involve intricate operations that exceed the current capabilities of the grippers on board current bombsquad robots. The Shadow Dexterous Hand from the Shadow Robot Company or 'ShadowHand' for short (www.shadowrobot.com) is the first commercially available robot hand that realistically replicates the motion, degrees-of-freedom and dimensions of a human hand (Figure 1). In this study we evaluate the potential for the ShadowHand to perform potential IED defeat tasks on a mobile platform.

Small Business Innovations (Exoskeletons)

NASA Technical Reports Server (NTRS)

1992-01-01

The Dexterous Hand Master (DHM), a 1989 winner of an R&D 100 Award, is an exoskeleton device for measuring the joints of the human hand with extreme precision. It was originally developed for NASA by Arthur D. Little, and is sold commercially by EXOS, Inc. The DHM is worn on the hand and connected to a computer that records hand motions. The resulting data is transmitted as control signals to robots and other computers, enabling robotic hands to emulate human hand actions. Two additional spinoff products were also inspired by the DHM.

Bayesian approach to MSD-based analysis of particle motion in live cells.

PubMed

Monnier, Nilah; Guo, Syuan-Ming; Mori, Masashi; He, Jun; Lénárt, Péter; Bathe, Mark

2012-08-08

Quantitative tracking of particle motion using live-cell imaging is a powerful approach to understanding the mechanism of transport of biological molecules, organelles, and cells. However, inferring complex stochastic motion models from single-particle trajectories in an objective manner is nontrivial due to noise from sampling limitations and biological heterogeneity. Here, we present a systematic Bayesian approach to multiple-hypothesis testing of a general set of competing motion models based on particle mean-square displacements that automatically classifies particle motion, properly accounting for sampling limitations and correlated noise while appropriately penalizing model complexity according to Occam's Razor to avoid over-fitting. We test the procedure rigorously using simulated trajectories for which the underlying physical process is known, demonstrating that it chooses the simplest physical model that explains the observed data. Further, we show that computed model probabilities provide a reliability test for the downstream biological interpretation of associated parameter values. We subsequently illustrate the broad utility of the approach by applying it to disparate biological systems including experimental particle trajectories from chromosomes, kinetochores, and membrane receptors undergoing a variety of complex motions. This automated and objective Bayesian framework easily scales to large numbers of particle trajectories, making it ideal for classifying the complex motion of large numbers of single molecules and cells from high-throughput screens, as well as single-cell-, tissue-, and organism-level studies. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Targeted Muscle Reinnervation for Real-Time Myoelectric Control of Multifunction Artificial Arms

PubMed Central

Kuiken, Todd A.; Li, Guanglin; Lock, Blair A.; Lipschutz, Robert D.; Miller, Laura A.; Stubblefield, Kathy A.; Englehart, Kevin

2011-01-01

Context Improving the function of prosthetic arms remains a challenge, as access to the neural control information for the arm is lost during amputation. We have developed a surgical technique called targeted muscle reinnervation (TMR) which transfers residual arm nerves to alternative muscle sites. After reinnervation, these target muscles produce an electromyogram (EMG) on the surface of the skin that can be measured and used to control prosthetic arms. Objective Assess the performance of TMR upper-limb amputee patients using a pattern-recognition algorithm to decode EMG signals and control prosthetic arm motions. Design Surface EMG signals were recorded on participants and decoded using a pattern-recognition algorithm. The decoding program controlled the movement of a virtual prosthetic arm. Participants were instructed to perform various arm movements, and their abilities to control the virtual prosthetic arm were measured. In addition, TMR patients used the same control system to operate advanced arm prosthesis prototypes. Setting This study was conducted between January 2007 and January 2008 at the Rehabilitation Institute of Chicago. Participants This study included five patients with shoulder disarticulation or transhumeral amputations who received TMR surgery between February 2002 and October 2006. It also included five non-amputee (control) participants. Main Outcome Measure Performance metrics measured during virtual arm movements included motion-selection time, motion-completion time, and motion-completion (or `success') rate. Three of the TMR patients were also able to test advanced arm prostheses. Results TMR patients were able to repeatedly perform 10 different elbow, wrist and hand motions with the virtual prosthetic arm. For TMR patients, the average (standard deviation (SD)) motion-selection and motion-completion times for elbow and wrist movements were 0.22 s (0.06) and 1.29 s (0.15), respectively. These times were 0.06 s and 0.21 s longer than the average times of control participants. For TMR patients, the average (SD) motion-selection and motion-completion times for hand-grasp patterns were 0.38 s (0.12) and 1.54 s (0.27), respectively. TMR patients successfully completed an average (SD) of 96.3% (3.8) of elbow and wrist movements and 86.9% (13.9) of hand movements within 5 s, compared to 100% (0) and 96.7% (4.7) completed by controls. Three of the patients were able to demonstrate the use of this control system in advanced prostheses including motorized shoulders, elbows, wrists and hands. Conclusion These results suggest that reinnervated muscles can produce sufficient EMG information to control advanced artificial arms. PMID:19211469

Generating Complaint Motion of Objects with an Articulated Hand

DTIC Science & Technology

1985-06-01

we consider the motions of rigid objects as the solhtions to a con- straint problem. We will examine the task of manipulation in the context of...describe the motion of a rigid object is equivalent to specifying sufficient constraint equations on these unknowns such that they are uniquely...assumption of rigidity . When a rigid object is constrained by a set of contacts, its motion must be consistent with those of the contacts, i.e. its

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics

PubMed Central

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. PMID:27806075

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

PubMed

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

PubMed

Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

2016-01-01

Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned.

Evaluation of the maximum-likelihood adaptive neural system (MLANS) applications to noncooperative IFF

NASA Astrophysics Data System (ADS)

Chernick, Julian A.; Perlovsky, Leonid I.; Tye, David M.

1994-06-01

This paper describes applications of maximum likelihood adaptive neural system (MLANS) to the characterization of clutter in IR images and to the identification of targets. The characterization of image clutter is needed to improve target detection and to enhance the ability to compare performance of different algorithms using diverse imagery data. Enhanced unambiguous IFF is important for fratricide reduction while automatic cueing and targeting is becoming an ever increasing part of operations. We utilized MLANS which is a parametric neural network that combines optimal statistical techniques with a model-based approach. This paper shows that MLANS outperforms classical classifiers, the quadratic classifier and the nearest neighbor classifier, because on the one hand it is not limited to the usual Gaussian distribution assumption and can adapt in real time to the image clutter distribution; on the other hand MLANS learns from fewer samples and is more robust than the nearest neighbor classifiers. Future research will address uncooperative IFF using fused IR and MMW data.

A qualitative motion analysis study of voluntary hand movement induced by music in patients with Rett syndrome

PubMed Central

Go, Tohshin; Mitani, Asako

2009-01-01

Patients with Rett syndrome are known to respond well to music irrespective of their physical and verbal disabilities. Therefore, the relationship between auditory rhythm and their behavior was investigated employing a two-dimensional motion analysis system. Ten female patients aged from three to 17 years were included. When music with a simple regular rhythm started, body rocking appeared automatically in a back and forth direction in all four patients who showed the same rocking motion as their stereotyped movement. Through this body rocking, voluntary movement of the hand increased gradually, and finally became sufficient to beat a tambourine. However, the induction of body rocking by music was not observed in the other six patients who did not show stereotyped body rocking in a back and forth direction. When the music stopped suddenly, voluntary movement of the hand disappeared. When the music changed from a simple regular rhythm to a continuous tone without an auditory rhythm, the periodic movement of both the hand and body prolonged. Auditory rhythm shows a close relationship with body movement and facilitates synchronized body movement. This mechanism was demonstrated to be preserved in some patients with Rett syndrome, and stimulation with music could be utilized for their rehabilitation. PMID:19851517

A qualitative motion analysis study of voluntary hand movement induced by music in patients with Rett syndrome.

PubMed

Go, Tohshin; Mitani, Asako

2009-01-01

Patients with Rett syndrome are known to respond well to music irrespective of their physical and verbal disabilities. Therefore, the relationship between auditory rhythm and their behavior was investigated employing a two-dimensional motion analysis system. Ten female patients aged from three to 17 years were included. When music with a simple regular rhythm started, body rocking appeared automatically in a back and forth direction in all four patients who showed the same rocking motion as their stereotyped movement. Through this body rocking, voluntary movement of the hand increased gradually, and finally became sufficient to beat a tambourine. However, the induction of body rocking by music was not observed in the other six patients who did not show stereotyped body rocking in a back and forth direction. When the music stopped suddenly, voluntary movement of the hand disappeared. When the music changed from a simple regular rhythm to a continuous tone without an auditory rhythm, the periodic movement of both the hand and body prolonged. Auditory rhythm shows a close relationship with body movement and facilitates synchronized body movement. This mechanism was demonstrated to be preserved in some patients with Rett syndrome, and stimulation with music could be utilized for their rehabilitation.

Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors.

PubMed

Onorati, Francesco; Regalia, Giulia; Caborni, Chiara; Migliorini, Matteo; Bender, Daniel; Poh, Ming-Zher; Frazier, Cherise; Kovitch Thropp, Eliana; Mynatt, Elizabeth D; Bidwell, Jonathan; Mai, Roberto; LaFrance, W Curt; Blum, Andrew S; Friedman, Daniel; Loddenkemper, Tobias; Mohammadpour-Touserkani, Fatemeh; Reinsberger, Claus; Tognetti, Simone; Picard, Rosalind W

2017-11-01

New devices are needed for monitoring seizures, especially those associated with sudden unexpected death in epilepsy (SUDEP). They must be unobtrusive and automated, and provide false alarm rates (FARs) bearable in everyday life. This study quantifies the performance of new multimodal wrist-worn convulsive seizure detectors. Hand-annotated video-electroencephalographic seizure events were collected from 69 patients at six clinical sites. Three different wristbands were used to record electrodermal activity (EDA) and accelerometer (ACM) signals, obtaining 5,928 h of data, including 55 convulsive epileptic seizures (six focal tonic-clonic seizures and 49 focal to bilateral tonic-clonic seizures) from 22 patients. Recordings were analyzed offline to train and test two new machine learning classifiers and a published classifier based on EDA and ACM. Moreover, wristband data were analyzed to estimate seizure-motion duration and autonomic responses. The two novel classifiers consistently outperformed the previous detector. The most efficient (Classifier III) yielded sensitivity of 94.55%, and an FAR of 0.2 events/day. No nocturnal seizures were missed. Most patients had <1 false alarm every 4 days, with an FAR below their seizure frequency. When increasing the sensitivity to 100% (no missed seizures), the FAR is up to 13 times lower than with the previous detector. Furthermore, all detections occurred before the seizure ended, providing reasonable latency (median = 29.3 s, range = 14.8-151 s). Automatically estimated seizure durations were correlated with true durations, enabling reliable annotations. Finally, EDA measurements confirmed the presence of postictal autonomic dysfunction, exhibiting a significant rise in 73% of the convulsive seizures. The proposed multimodal wrist-worn convulsive seizure detectors provide seizure counts that are more accurate than previous automated detectors and typical patient self-reports, while maintaining a tolerable FAR for ambulatory monitoring. Furthermore, the multimodal system provides an objective description of motor behavior and autonomic dysfunction, aimed at enriching seizure characterization, with potential utility for SUDEP warning. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Kinematic Parameters of Signed Verbs

ERIC Educational Resources Information Center

Malaia, Evie; Wilbur, Ronnie B.; Milkovic, Marina

2013-01-01

Purpose: Sign language users recruit physical properties of visual motion to convey linguistic information. Research on American Sign Language (ASL) indicates that signers systematically use kinematic features (e.g., velocity, deceleration) of dominant hand motion for distinguishing specific semantic properties of verb classes in production…

Early diagnosis of osteoporosis using radiogrammetry and texture analysis from hand and wrist radiographs in Indian population.

PubMed

Areeckal, A S; Jayasheelan, N; Kamath, J; Zawadynski, S; Kocher, M; David S, S

2018-03-01

We propose an automated low cost tool for early diagnosis of onset of osteoporosis using cortical radiogrammetry and cancellous texture analysis from hand and wrist radiographs. The trained classifier model gives a good performance accuracy in classifying between healthy and low bone mass subjects. We propose a low cost automated diagnostic tool for early diagnosis of reduction in bone mass using cortical radiogrammetry and cancellous texture analysis of hand and wrist radiographs. Reduction in bone mass could lead to osteoporosis, a disease observed to be increasingly occurring at a younger age in recent times. Dual X-ray absorptiometry (DXA), currently used in clinical practice, is expensive and available only in urban areas in India. Therefore, there is a need to develop a low cost diagnostic tool in order to facilitate large-scale screening of people for early diagnosis of osteoporosis at primary health centers. Cortical radiogrammetry from third metacarpal bone shaft and cancellous texture analysis from distal radius are used to detect low bone mass. Cortical bone indices and cancellous features using Gray Level Run Length Matrices and Laws' masks are extracted. A neural network classifier is trained using these features to classify healthy subjects and subjects having low bone mass. In our pilot study, the proposed segmentation method shows 89.9 and 93.5% accuracy in detecting third metacarpal bone shaft and distal radius ROI, respectively. The trained classifier shows training accuracy of 94.3% and test accuracy of 88.5%. An automated diagnostic technique for early diagnosis of onset of osteoporosis is developed using cortical radiogrammetric measurements and cancellous texture analysis of hand and wrist radiographs. The work shows that a combination of cortical and cancellous features improves the diagnostic ability and is a promising low cost tool for early diagnosis of increased risk of osteoporosis.

Leap motion controlled videogame-based therapy for rehabilitation of elderly patients with subacute stroke: a feasibility pilot study.

PubMed

Iosa, Marco; Morone, Giovanni; Fusco, Augusto; Castagnoli, Marcello; Fusco, Francesca Romana; Pratesi, Luca; Paolucci, Stefano

2015-08-01

The leap motion controller (LMC) is a new optoelectronic system for capturing motion of both hands and controlling a virtual environment. Differently from previous devices, it optoelectronically tracks the fine movements of fingers neither using glows nor markers. This pilot study explored the feasibility of adapting the LMC, developed for videogames, to neurorehabilitation of elderly with subacute stroke. Four elderly patients (71.50 ± 4.51 years old) affected by stroke in subacute phase were enrolled and tested in a cross-over pilot trial in which six sessions of 30 minutes of LMC videogame-based therapy were added on conventional therapy. Measurements involved participation to the sessions, evaluated by means of the Pittsburgh Rehabilitation Participation Scale, hand ability and grasp force evaluated respectively by means of the Abilhand Scale and by means of the dynamometer. Neither adverse effects nor spasticity increments were observed during LMC training. Participation to the sessions was excellent in three patients and very good in one patient during the LMC trial. In this period, patients showed a significantly higher improvement in hand abilities (P = 0.028) and grasp force (P = 0.006). This feasibility pilot study was the first one using leap motion controller for conducting a videogame-based therapy. This study provided a proof of concept that LMC can be a suitable tool even for elderly patients with subacute stroke. LMC training was in fact performed with a high level of active participation, without adverse effects, and contributed to increase the recovery of hand abilities.

An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging

PubMed Central

Mukherjee, Joyeeta Mitra; Hutton, Brian F; Johnson, Karen L; Pretorius, P Hendrik; King, Michael A

2014-01-01

Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference (MSD), mutual information (MI), normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation (NCC) and entropy of the difference (EDI). Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in 1 of the 5 patient studies, and with external-surrogate based correction in 3 out of 5 patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality. PMID:24107647

Physiological and subjective evaluation of a human-robot object hand-over task.

PubMed

Dehais, Frédéric; Sisbot, Emrah Akin; Alami, Rachid; Causse, Mickaël

2011-11-01

In the context of task sharing between a robot companion and its human partners, the notions of safe and compliant hardware are not enough. It is necessary to guarantee ergonomic robot motions. Therefore, we have developed Human Aware Manipulation Planner (Sisbot et al., 2010), a motion planner specifically designed for human-robot object transfer by explicitly taking into account the legibility, the safety and the physical comfort of robot motions. The main objective of this research was to define precise subjective metrics to assess our planner when a human interacts with a robot in an object hand-over task. A second objective was to obtain quantitative data to evaluate the effect of this interaction. Given the short duration, the "relative ease" of the object hand-over task and its qualitative component, classical behavioral measures based on accuracy or reaction time were unsuitable to compare our gestures. In this perspective, we selected three measurements based on the galvanic skin conductance response, the deltoid muscle activity and the ocular activity. To test our assumptions and validate our planner, an experimental set-up involving Jido, a mobile manipulator robot, and a seated human was proposed. For the purpose of the experiment, we have defined three motions that combine different levels of legibility, safety and physical comfort values. After each robot gesture the participants were asked to rate them on a three dimensional subjective scale. It has appeared that the subjective data were in favor of our reference motion. Eventually the three motions elicited different physiological and ocular responses that could be used to partially discriminate them. Copyright © 2011 Elsevier Ltd and the Ergonomics Society. All rights reserved.

Hazardous materials emergency response mobile robot

NASA Technical Reports Server (NTRS)

Stone, Henry W. (Inventor); Lloyd, James W. (Inventor); Alahuzos, George A. (Inventor)

1995-01-01

A simple or unsophisticated robot incapable of effecting straight-line motion at the end of its arm is presented. This robot inserts a key held in its end effector or hand into a door lock with nearly straight-line motion by gently thrusting its back heels downwardly so that it pivots forwardly on its front toes while holding its arm stationary. The relatively slight arc traveled by the robot's hand is compensated by a complaint tool with which the robot hand grips the door key. A visible beam is projected through the axis of the hand or gripper on the robot arm end at an angle to the general direction in which the robot thrusts the gripper forward. As the robot hand approaches a target surface, a video camera on the robot wrist watches the beam spot on the target surface fall from a height proportional to the distance between the robot hand and the target surface until the beam spot is nearly aligned with the top of the robot hand. Holes in the front face of the hand are connected through internal passages inside the arm to an on-board chemical sensor. Full rotation of the hand or gripper about the robot arm's wrist is made possible by slip rings in the wrist which permit passage of the gases taken in through the nose holes in the front of the hand through the wrist regardless of the rotational orientation of the wrist.

Remote Control and Children's Understanding of Robots

ERIC Educational Resources Information Center

Somanader, Mark C.; Saylor, Megan M.; Levin, Daniel T.

2011-01-01

Children use goal-directed motion to classify agents as living things from early in infancy. In the current study, we asked whether preschoolers are flexible in their application of this criterion by introducing them to robots that engaged in goal-directed motion. In one case the robot appeared to move fully autonomously, and in the other case it…

Rehabilitation of patient with brachial plexus lesion and break in axillary artery. Case study.

PubMed

Bajuk, S; Jelnikar, T; Ortar, M

1996-01-01

This paper describes the physiotherapy and occupational therapy used in treating a 74-year-old woman with a left brachial plexus lesion, a break in the axillary artery, dislocation of the acromioclavicular joint, a broken scapula and clavicula, serial left rib fractures, and lacerations on the upper and lower arm. After testing the patient, the following goals were set: reduce pain, soften scar tissue, and improve joint motion, muscle strength, and functionality of the hand. A 12-month outpatient program was used. Various analgesics were used to reduce pain, and a special aid was made to unweight the shoulder and elbow joints. Physiotherapy included kinesiotherapy, audiovisual biofeedback, electrical stimulation, friction massage, and lymph drainage. Occupational therapy included active functional exercises and re-education. As a result of this program, the patient no longer had pain, passive range of motion was close to normal, active motion where present was improved, swelling was reduced, and the hand became functional again. Complex physiotherapy, occupational therapy, and the patient's motivation resulted in the rehabilitation of severe trauma of the hand.

Atypical activation of the mirror neuron system during perception of hand motion in autism.

PubMed

Martineau, Joëlle; Andersson, Frédéric; Barthélémy, Catherine; Cottier, Jean-Philippe; Destrieux, Christophe

2010-03-12

Disorders in the autism spectrum are characterized by deficits in social and communication skills such as imitation, pragmatic language, theory of mind, and empathy. The discovery of the "mirror neuron system" (MNS) in macaque monkeys may provide a basis from which to explain some of the behavioral dysfunctions seen in individuals with autism spectrum disorders (ASD).We studied seven right-handed high-functioning male autistic and eight normal subjects (TD group) using functional magnetic resonance imaging during observation and execution of hand movements compared to a control condition (rest). The between group comparison of the contrast [observation versus rest] provided evidence of a bilateral greater activation of inferior frontal gyrus during observation of human motion than during rest for the ASD group than for the TD group. This hyperactivation of the pars opercularis (belonging to the MNS) during observation of human motion in autistic subjects provides strong support for the hypothesis of atypical activity of the MNS that may be at the core of the social deficits in autism. Copyright 2010 Elsevier B.V. All rights reserved.

Compact and low-cost humanoid hand powered by nylon artificial muscles.

PubMed

Wu, Lianjun; Jung de Andrade, Monica; Saharan, Lokesh Kumar; Rome, Richard Steven; Baughman, Ray H; Tadesse, Yonas

2017-02-03

This paper focuses on design, fabrication and characterization of a biomimetic, compact, low-cost and lightweight 3D printed humanoid hand (TCP Hand) that is actuated by twisted and coiled polymeric (TCP) artificial muscles. The TCP muscles were recently introduced and provided unprecedented strain, mechanical work, and lifecycle (Haines et al 2014 Science 343 868-72). The five-fingered humanoid hand is under-actuated and has 16 degrees of freedom (DOF) in total (15 for fingers and 1 at the palm). In the under-actuated hand designs, a single actuator provides coupled motions at the phalanges of each finger. Two different designs are presented along with the essential elements consisting of actuators, springs, tendons and guide systems. Experiments were conducted to investigate the performance of the TCP muscles in response to the power input (power magnitude, type of wave form such as pulsed or square wave, and pulse duration) and the resulting actuation stroke and force generation. A kinematic model of the flexor tendons was developed to simulate the flexion motion and compare with experimental results. For fast finger movements, short high-power pulses were employed. Finally, we demonstrated the grasping of various objects using the humanoid TCP hand showing an array of functions similar to a natural hand.

Finger Interdependence: Linking the Kinetic and Kinematic Variables

PubMed Central

Kim, Sun Wook; Shim, Jae Kun; Zatsiorsky, Vladimir M.; Latash, Mark L.

2008-01-01

We studied the dependence between voluntary motion of a finger and pressing forces produced by the tips of other fingers of the hand. Subjects moved one of the fingers (task finger) of the right hand trying to follow a cyclic, ramp-like flexion-extension template at different frequencies. The other fingers (slave fingers) were restricted from moving; their flexion forces were recorded and analyzed. Index finger motion caused the smallest force production by the slave fingers. Larger forces were produced by the neighbors of the task finger; these forces showed strong modulation over the range of motion of the task finger. The enslaved forces were higher during the flexion phase of the movement cycle as compared to the extension phase. The index of enslaving expressed in N/rad was higher when the task finger moved through the more flexed postures. The dependence of enslaving on both range and direction of task finger motion poses problems for methods of analysis of finger coordination based on an assumption of universal matrices of finger inter-dependence. PMID:18255182

The swimming of a perfect deforming helix

NASA Astrophysics Data System (ADS)

Koens, Lyndon; Zhang, Hang; Mourran, Ahmed; Lauga, Eric

2017-11-01

Many bacteria rotate helical flagellar filaments in order to swim. When at rest or rotated counter-clockwise these flagella are left handed helices but they undergo polymorphic transformations to right-handed helices when the motor is reversed. These helical deformations themselves can generate motion, with for example Rhodobacter sphaeroides using the polymorphic transformation of the flagellum to generate rotation, or Spiroplasma propagating a change of helix handedness across its body's length to generate forward motion. Recent experiments reported on an artificial helical microswimmer generating motion without a propagating change in handedness. Made of a temperature sensitive gel, these swimmers moved by changing the dimensions of the helix in a non-reciprocal way. Inspired by these results and helix's ubiquitous presence in the bacterial world, we investigate how a deforming helix moves within a viscous fluid. Maintaining a single handedness along its entire length, we discuss how a perfect deforming helix can create a non-reciprocal swimming stroke, identify its principle directions of motion, and calculate the swimming kinematics asymptotically.

Applying Space Technology to Enhance Control of an Artificial Arm

NASA Technical Reports Server (NTRS)

Atkins, Diane; Donovan, William H.; Novy, Mara; Abramczyk, Robert

1997-01-01

At the present time, myoelectric prostheses perform only one function of the hand: open and close with the thumb, index and middle finger coming together to grasp various shaped objects. To better understand the limitations of the current single-function prostheses and the needs of the individuals who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (August 1992 - November 1994), surveyed approximately 2500 individuals with upper limb loss. When asked to identify specific features of their current electric prosthesis that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement as well as poor control capability. Simply building a mechanism with individual finger and wrist motion is not enough. Individuals with upper limb loss tend to reject prostheses that require continuous visual monitoring and concentration to control. Robotics researchers at NASA's Johnson Space Center (JSC) and Rice University have made substantial progress in myoelectric teleoperation. A myoelectric teleoperation system translates signals generated by an able-bodied robot operator's muscles during hand motions into commands that drive a robot's hand through identical motions. Farry's early work in myoelectric teleoperation used variations over time in the myoelectric spectrum as inputs to neural networks to discriminate grasp types and thumb motions. The resulting schemes yielded up to 93% correct classification on thumb motions. More recently, Fernandez achieved 100% correct non-realtime classification of thumb abduction, extension, and flexion on the same myoelectric data. Fernandez used genetic programming to develop functions that discriminate between thumb motions using myoelectric signal parameters. Genetic programming (GP) is an evolutionary programming method where the computer can modify the discriminating functions' form to improve its performance, not just adjust numerical coefficients or weights. Although the function development may require much computational time and many training cases, the resulting discrimination functions can run in realtime on modest computers. These results suggest that myoelectric signals might be a feasible teleoperation medium, allowing an operator to use his or her own hand and arm as a master to intuitively control an anthropomorphic robot in a remote location such as outer space.

Finger tips detection for two handed gesture recognition

NASA Astrophysics Data System (ADS)

Bhuyan, M. K.; Kar, Mithun Kumar; Neog, Debanga Raj

2011-10-01

In this paper, a novel algorithm is proposed for fingertips detection in view of two-handed static hand pose recognition. In our method, finger tips of both hands are detected after detecting hand regions by skin color-based segmentation. At first, the face is removed in the image by using Haar classifier and subsequently, the regions corresponding to the gesturing hands are isolated by a region labeling technique. Next, the key geometric features characterizing gesturing hands are extracted for two hands. Finally, for all possible/allowable finger movements, a probabilistic model is developed for pose recognition. Proposed method can be employed in a variety of applications like sign language recognition and human-robot-interactions etc.

A Study on Immersion and Presence of a Portable Hand Haptic System for Immersive Virtual Reality

PubMed Central

Kim, Mingyu; Jeon, Changyu; Kim, Jinmo

2017-01-01

This paper proposes a portable hand haptic system using Leap Motion as a haptic interface that can be used in various virtual reality (VR) applications. The proposed hand haptic system was designed as an Arduino-based sensor architecture to enable a variety of tactile senses at low cost, and is also equipped with a portable wristband. As a haptic system designed for tactile feedback, the proposed system first identifies the left and right hands and then sends tactile senses (vibration and heat) to each fingertip (thumb and index finger). It is incorporated into a wearable band-type system, making its use easy and convenient. Next, hand motion is accurately captured using the sensor of the hand tracking system and is used for virtual object control, thus achieving interaction that enhances immersion. A VR application was designed with the purpose of testing the immersion and presence aspects of the proposed system. Lastly, technical and statistical tests were carried out to assess whether the proposed haptic system can provide a new immersive presence to users. According to the results of the presence questionnaire and the simulator sickness questionnaire, we confirmed that the proposed hand haptic system, in comparison to the existing interaction that uses only the hand tracking system, provided greater presence and a more immersive environment in the virtual reality. PMID:28513545

A Study on Immersion and Presence of a Portable Hand Haptic System for Immersive Virtual Reality.

PubMed

Kim, Mingyu; Jeon, Changyu; Kim, Jinmo

2017-05-17

This paper proposes a portable hand haptic system using Leap Motion as a haptic interface that can be used in various virtual reality (VR) applications. The proposed hand haptic system was designed as an Arduino-based sensor architecture to enable a variety of tactile senses at low cost, and is also equipped with a portable wristband. As a haptic system designed for tactile feedback, the proposed system first identifies the left and right hands and then sends tactile senses (vibration and heat) to each fingertip (thumb and index finger). It is incorporated into a wearable band-type system, making its use easy and convenient. Next, hand motion is accurately captured using the sensor of the hand tracking system and is used for virtual object control, thus achieving interaction that enhances immersion. A VR application was designed with the purpose of testing the immersion and presence aspects of the proposed system. Lastly, technical and statistical tests were carried out to assess whether the proposed haptic system can provide a new immersive presence to users. According to the results of the presence questionnaire and the simulator sickness questionnaire, we confirmed that the proposed hand haptic system, in comparison to the existing interaction that uses only the hand tracking system, provided greater presence and a more immersive environment in the virtual reality.

46 CFR 503.59 - Safeguarding classified information.

Code of Federal Regulations, 2010 CFR

2010-10-01

... another shall be protected with a classified document cover sheet and hand delivered by an appropriately... Security Officer: (1) Determines in writing that access is consistent with the interest of national... with paragraphs (e) and (f) of this section must agree in writing: (1) To be subject to a national...

Common fractures and dislocations of the hand.

PubMed

Jones, Neil F; Jupiter, Jesse B; Lalonde, Donald H

2012-11-01

After reading this article, the participant should be able to: 1. Describe the concept of early protected movement with Kirschner-wired finger fractures to the hand therapist. 2. Choose the most appropriate method of fracture fixation to achieve the goal of a full range of motion. 3. Describe the methods of treatment available for the most common fractures and dislocations of the hand. The main goal of treatment of hand and finger fractures and dislocations is to attain a full range of wrist and nonscissoring finger motion after the treatment is accomplished. This CME article consists of literature review, illustrations, movies, and an online CME examination to bring the participant recent available information on the topic. The authors reviewed literature regarding the most current treatment strategies for common hand and finger fractures and dislocations. Films were created to illustrate operative and rehabilitation methods used to treat these problems. A series of multiple-choice questions, answers, discussions, and references were written and are provided online so that the participant can receive the full benefit of this review. Many treatment options are available, from buddy and Coban taping to closed reduction with immobilization; percutaneous pins or screws; and open reduction with pins, screws, or plates. Knowledge of all available options is important because all can be used to achieve the goal of treatment in the shortest time possible. The commonly used methods of treatment are reviewed and illustrated. Management of common hand and finger fractures and dislocations includes the need to focus on achieving a full range of motion after treatment. A balance of fracture reduction with minimal dissection and early protected movement will achieve the goal.

An on-line BCI for control of hand grasp sequence and holding using adaptive probabilistic neural network.

PubMed

Hazrati, Mehrnaz Kh; Erfanian, Abbas

2008-01-01

This paper presents a new EEG-based Brain-Computer Interface (BCI) for on-line controlling the sequence of hand grasping and holding in a virtual reality environment. The goal of this research is to develop an interaction technique that will allow the BCI to be effective in real-world scenarios for hand grasp control. Moreover, for consistency of man-machine interface, it is desirable the intended movement to be what the subject imagines. For this purpose, we developed an on-line BCI which was based on the classification of EEG associated with imagination of the movement of hand grasping and resting state. A classifier based on probabilistic neural network (PNN) was introduced for classifying the EEG. The PNN is a feedforward neural network that realizes the Bayes decision discriminant function by estimating probability density function using mixtures of Gaussian kernels. Two types of classification schemes were considered here for on-line hand control: adaptive and static. In contrast to static classification, the adaptive classifier was continuously updated on-line during recording. The experimental evaluation on six subjects on different days demonstrated that by using the static scheme, a classification accuracy as high as the rate obtained by the adaptive scheme can be achieved. At the best case, an average classification accuracy of 93.0% and 85.8% was obtained using adaptive and static scheme, respectively. The results obtained from more than 1500 trials on six subjects showed that interactive virtual reality environment can be used as an effective tool for subject training in BCI.

New inverse synthetic aperture radar algorithm for translational motion compensation

NASA Astrophysics Data System (ADS)

Bocker, Richard P.; Henderson, Thomas B.; Jones, Scott A.; Frieden, B. R.

1991-10-01

Inverse synthetic aperture radar (ISAR) is an imaging technique that shows real promise in classifying airborne targets in real time under all weather conditions. Over the past few years a large body of ISAR data has been collected and considerable effort has been expended to develop algorithms to form high-resolution images from this data. One important goal of workers in this field is to develop software that will do the best job of imaging under the widest range of conditions. The success of classifying targets using ISAR is predicated upon forming highly focused radar images of these targets. Efforts to develop highly focused imaging computer software have been challenging, mainly because the imaging depends on and is affected by the motion of the target, which in general is not precisely known. Specifically, the target generally has both rotational motion about some axis and translational motion as a whole with respect to the radar. The slant-range translational motion kinematic quantities must be first accurately estimated from the data and compensated before the image can be focused. Following slant-range motion compensation, the image is further focused by determining and correcting for target rotation. The use of the burst derivative measure is proposed as a means to improve the computational efficiency of currently used ISAR algorithms. The use of this measure in motion compensation ISAR algorithms for estimating the slant-range translational motion kinematic quantities of an uncooperative target is described. Preliminary tests have been performed on simulated as well as actual ISAR data using both a Sun 4 workstation and a parallel processing transputer array. Results indicate that the burst derivative measure gives significant improvement in processing speed over the traditional entropy measure now employed.

Use of a Proximity Sensor Switch for "Hands Free" Operation of Computer-Based Video Prompting by Young Adults with Moderate Intellectual Disability

ERIC Educational Resources Information Center

Ivey, Alexandria N.; Mechling, Linda C.; Spencer, Galen P.

2015-01-01

In this study, the effectiveness of a "hands free" approach for operating video prompts to complete multi-step tasks was measured. Students advanced the video prompts by using a motion (hand wave) over a proximity sensor switch. Three young adult females with a diagnosis of moderate intellectual disability participated in the study.…

Reliability and validity of the delta finger-to-palm (FTP), a new measure of finger range of motion in systemic sclerosis.

PubMed

Torok, Kathryn S; Baker, Nancy A; Lucas, Mary; Domsic, Robyn T; Boudreau, Robert; Medsger, Thomas A

2010-01-01

To determine the reliability and validity of a new measure of finger motion in patients with systemic sclerosis (SSc), the 'delta finger-topalm' (delta FTP) and compare its psychometric properties to the traditional measure of finger motion, the finger-topalm (FTP). Phase 1: The reliability of the delta FTP and FTP were examined in 39 patients with SSc. Phase 2: Criterion and convergent construct validity of both measures were examined in 17 patients with SSc by comparing them to other clinical measures: Total Active Range of Motion (TAROM), Hand Mobility in Scleroderma (HAMIS), the Duruoz Hand Index (DHI), Health Assessment Questionnaire (HAQ), and modified Rodnan skin score (mRSS). Phase 3: Sensitivity to change of the delta FTP was investigated in 24 patients with early diffuse cutaneous SSc. Both measures had excellent intra-rater and inter-rater reliability (ICC 0.92 to 0.99). Fair to strong correlations (rs=0.49-0.94) were observed between the delta FTP and TAROM, HAMIS, and DHI. Fair to moderate correlations were observed between delta FTP and HAQ components related to hand function and upper extremity mRSS. Correlations of the traditional FTP with these measures were fair to strong, but most often the delta FTP outperformed the FTP. The effect size and standardised response mean for the mean delta FTP were 0.50 and 1.10 respectively, over a 2-8 month period. The delta FTP is a valid and reliable measure of finger motion in patients with SSc which outperforms the FTP.

Health Problems Discovery from Motion-Capture Data of Elderly

NASA Astrophysics Data System (ADS)

Pogorelc, B.; Gams, M.

Rapid aging of the population of the developed countries could exceed the society's capacity for taking care for them. In order to help solving this problem, we propose a system for automatic discovery of health problems from motion-capture data of gait of elderly. The gait of the user is captured with the motion capture system, which consists of tags attached to the body and sensors situated in the apartment. Position of the tags is acquired by the sensors and the resulting time series of position coordinates are analyzed with machine learning algorithms in order to identify the specific health problem. We propose novel features for training a machine learning classifier that classifies the user's gait into: i) normal, ii) with hemiplegia, iii) with Parkinson's disease, iv) with pain in the back and v) with pain in the leg. Results show that naive Bayes needs more tags and less noise to reach classification accuracy of 98 % than support vector machines for 99 %.

Identifying sports videos using replay, text, and camera motion features

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1999-12-01

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

Classifying and Analyzing 3d Cell Motion in Jammed Microgels

NASA Astrophysics Data System (ADS)

Bhattacharjee, Tapomoy; Sawyer, W. Gregory; Angelini, Thomas

Soft granular polyelectrolyte microgels swell in liquid cell growth media to form a continuous elastic solid that can easily transition between solid to fluid state under a low shear stress. Such Liquid-like solids (LLS) have recently been used to create 3D cellular constructs as well as to support, culture and harvest cells in 3D. Current understanding of cell migration mechanics in 3D was established from experiments performed in natural and synthetic polymer networks. Spatial variation in network structure and the transience of degradable gels limit their usefulness in quantitative cell mechanics studies. By contrast, LLS growth media approximates a homogeneous continuum, enabling tractable cell mechanics measurements to be performed in 3D. Here, we introduce a process to understand and classify cytotoxic T cell motion in 3D by studying cellular motility in LLS media. General classification of T cell motion can be achieved with a very traditional statistical approach: the cell's mean squared displacement (MSD) as a function of delay time. We will also use Langevin approaches combined with the constitutive equations of the LLS medium to predict the statistics of T cell motion. National Science Foundation under Grant No. DMR-1352043.

Upper-limb tremor suppression with a 7DOF exoskeleton power-assist robot.

PubMed

Kiguchi, Kazuo; Hayashi, Yoshiaki

2013-01-01

A tremor which is one of the involuntary motions is somewhat rhythmic motion that may occur in various body parts. Although there are several kinds of the tremor, an essential tremor is the most common tremor disorder of the arm. The essential tremor is a disorder of unknown cause, and it is common in the elderly. The essential tremor interferes with a patient's daily living activity, because it may occur during a voluntary motion. If a patient of an essential tremor uses an EMG-based controlled power-assist robot, the robot might misunderstand the user's motion intention because of the effect of the essential tremor. In that case, upper-limb power-assist robots must carry out tremor suppression as well as power-assist, since a person performs various precise tasks with certain tools by the upper-limb in daily living. Therefore, it is important to suppress the tremor at the hand and grasped tool. However, in the case of the tremor suppression control method which suppressed the vibrations of the hand and the tip of the tool, vibration of other part such as elbow might occur. In this paper, the tremor suppression control method for upper-limb power-assist robot is proposed. In the proposed method, the vibration of the elbow is suppressed in addition to the hand and the tip of the tool. The validity of the proposed method was verified by the experiments.

Design of a Lightweight Soft Robotic Arm Using Pneumatic Artificial Muscles and Inflatable Sleeves.

PubMed

Ohta, Preston; Valle, Luis; King, Jonathan; Low, Kevin; Yi, Jaehyun; Atkeson, Christopher G; Park, Yong-Lae

2018-04-01

As robots begin to interact with humans and operate in human environments, safety becomes a major concern. Conventional robots, although reliable and consistent, can cause injury to anyone within its range of motion. Soft robotics, wherein systems are made to be soft and mechanically compliant, are thus a promising alternative due to their lightweight nature and ability to cushion impacts, but current designs often sacrifice accuracy and usefulness for safety. We, therefore, have developed a bioinspired robotic arm combining elements of rigid and soft robotics such that it exhibits the positive qualities of both, namely compliance and accuracy, while maintaining a low weight. This article describes the design of a robotic arm-wrist-hand system with seven degrees of freedom (DOFs). The shoulder and elbow each has two DOFs for two perpendicular rotational motions on each joint, and the hand has two DOFs for wrist rotations and one DOF for a grasp motion. The arm is pneumatically powered using custom-built McKibben type pneumatic artificial muscles, which are inflated and deflated using binary and proportional valves. The wrist and hand motions are actuated through servomotors. In addition to the actuators, the arm is equipped with a potentiometer in each joint for detecting joint angle changes. Simulation and experimental results for closed-loop position control are also presented in the article.

Avoiding space robot collisions utilizing the NASA/GSFC tri-mode skin sensor

NASA Technical Reports Server (NTRS)

Prinz, F. B. S.; Mahalingam, S.

1992-01-01

A capacitance based proximity sensor, the 'Capaciflector' (Vranish 92), has been developed at the Goddard Space Flight Center of NASA. We had investigated the use of this sensor for avoiding and maneuvering around unexpected objects (Mahalingam 92). The approach developed there would help in executing collision-free gross motions. Another important aspect of robot motion planning is fine motion planning. Let us classify manipulator robot motion planning into two groups at the task level: gross motion planning and fine motion planning. We use the term 'gross planning' where the major degrees of freedom of the robot execute large motions, for example, the motion of a robot in a pick and place type operation. We use the term 'fine motion' to indicate motions of the robot where the large dofs do not move much, and move far less than the mirror dofs, such as in inserting a peg in a hole. In this report we describe our experiments and experiences in this area.

10 CFR 76.5 - Communications.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Response, U.S Nuclear Regulatory Commission, Washington, DC 20555-0001; (b) By hand delivery to the NRC's... [email protected]; or by writing the Office of Information Services, U.S. Nuclear Regulatory...' classified mailing address listed in appendix A to part 73 of this chapter or delivered by hand in accordance...

CPMs: A Kinesthetic Comprehension Strategy

ERIC Educational Resources Information Center

Block, Cathy Collins; Parris, Sheri R.; Whiteley, Cinnamon S.

2008-01-01

This article discusses a study to determine whether primary grade students can learn comprehension processes via hand motions to portray these mental processes. Comprehension Process Motions (CPMs) were designed to provide students with a way to make abstract comprehension processes more consciously accessible and also to give teachers a way to…

Computer Controlled Optical Surfacing With Orbital Tool Motion

NASA Astrophysics Data System (ADS)

Jones, Robert A.

1985-11-01

Asymmetric aspheric optical surfaces are very difficult to fabricate using classical techniques and laps the same size as the workpiece. Opticians can produce such surfaces by hand grinding and polishing, using small laps with orbital tool motion. However, this is a time consuming process unsuitable for large optical elements.

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation.

PubMed

Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

2016-03-18

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training.

Fusion of Haptic and Gesture Sensors for Rehabilitation of Bimanual Coordination and Dexterous Manipulation

PubMed Central

Yu, Ningbo; Xu, Chang; Li, Huanshuai; Wang, Kui; Wang, Liancheng; Liu, Jingtai

2016-01-01

Disabilities after neural injury, such as stroke, bring tremendous burden to patients, families and society. Besides the conventional constrained-induced training with a paretic arm, bilateral rehabilitation training involves both the ipsilateral and contralateral sides of the neural injury, fitting well with the fact that both arms are needed in common activities of daily living (ADLs), and can promote good functional recovery. In this work, the fusion of a gesture sensor and a haptic sensor with force feedback capabilities has enabled a bilateral rehabilitation training therapy. The Leap Motion gesture sensor detects the motion of the healthy hand, and the omega.7 device can detect and assist the paretic hand, according to the designed cooperative task paradigm, as much as needed, with active force feedback to accomplish the manipulation task. A virtual scenario has been built up, and the motion and force data facilitate instantaneous visual and audio feedback, as well as further analysis of the functional capabilities of the patient. This task-oriented bimanual training paradigm recruits the sensory, motor and cognitive aspects of the patient into one loop, encourages the active involvement of the patients into rehabilitation training, strengthens the cooperation of both the healthy and impaired hands, challenges the dexterous manipulation capability of the paretic hand, suits easy of use at home or centralized institutions and, thus, promises effective potentials for rehabilitation training. PMID:26999149

Classification of Palmprint Using Principal Line

NASA Astrophysics Data System (ADS)

Prasad, Munaga V. N. K.; Kumar, M. K. Pramod; Sharma, Kuldeep

In this paper, a new classification scheme for palmprint is proposed. Palmprint is one of the reliable physiological characteristics that can be used to authenticate an individual. Palmprint classification provides an important indexing mechanism in a very large palmprint database. Here, the palmprint database is initially categorized into two groups, right hand group and left hand group. Then, each group is further classified based on the distance traveled by principal line i.e. Heart Line During pre processing, a rectangular Region of Interest (ROI) in which only heart line is present, is extracted. Further, ROI is divided into 6 regions and depending upon the regions in which the heart line traverses the palmprint is classified accordingly. Consequently, our scheme allows 64 categories for each group forming a total number of 128 possible categories. The technique proposed in this paper includes only 15 such categories and it classifies not more than 20.96% of the images into a single category.

30 CFR 75.1728 - Power-driven pulleys.

Code of Federal Regulations, 2010 CFR

2010-07-01

... hands except on slow-moving equipment especially designed for hand feeding. (b) Pulleys of conveyors shall not be cleaned manually while the conveyor is in motion. (c) Coal spilled beneath belt conveyor... MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Miscellaneous § 75.1728 Power-driven pulleys. (a) Belts...

Localized motion in random matrix decomposition of complex financial systems

NASA Astrophysics Data System (ADS)

Jiang, Xiong-Fei; Zheng, Bo; Ren, Fei; Qiu, Tian

2017-04-01

With the random matrix theory, we decompose the multi-dimensional time series of complex financial systems into a set of orthogonal eigenmode functions, which are classified into the market mode, sector mode, and random mode. In particular, the localized motion generated by the business sectors, plays an important role in financial systems. Both the business sectors and their impact on the stock market are identified from the localized motion. We clarify that the localized motion induces different characteristics of the time correlations for the stock-market index and individual stocks. With a variation of a two-factor model, we reproduce the return-volatility correlations of the eigenmodes.

A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface

PubMed Central

Yaacoub, Charles; Mhanna, Georges; Rihana, Sandy

2017-01-01

Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5%) while improving the accuracy, sensitivity, specificity, and precision of the classifier. PMID:28124985

A Genetic-Based Feature Selection Approach in the Identification of Left/Right Hand Motor Imagery for a Brain-Computer Interface.

PubMed

Yaacoub, Charles; Mhanna, Georges; Rihana, Sandy

2017-01-23

Electroencephalography is a non-invasive measure of the brain electrical activity generated by millions of neurons. Feature extraction in electroencephalography analysis is a core issue that may lead to accurate brain mental state classification. This paper presents a new feature selection method that improves left/right hand movement identification of a motor imagery brain-computer interface, based on genetic algorithms and artificial neural networks used as classifiers. Raw electroencephalography signals are first preprocessed using appropriate filtering. Feature extraction is carried out afterwards, based on spectral and temporal signal components, and thus a feature vector is constructed. As various features might be inaccurate and mislead the classifier, thus degrading the overall system performance, the proposed approach identifies a subset of features from a large feature space, such that the classifier error rate is reduced. Experimental results show that the proposed method is able to reduce the number of features to as low as 0.5% (i.e., the number of ignored features can reach 99.5%) while improving the accuracy, sensitivity, specificity, and precision of the classifier.

Influence of cognitive style and interstimulus interval on the hemispheric processing of tactile stimuli.

PubMed

Minagawa, N; Kashu, K

1989-06-01

16 adult subjects performed a tactile recognition task. According to our 1984 study, half of the subjects were classified as having a left hemispheric preference for the processing of visual stimuli, while the other half were classified as having a right hemispheric preference for the processing of visual stimuli. The present task was conducted according to the S1-S2 matching paradigm. The standard stimulus was a readily recognizable object and was presented tactually to either the left or right hand of each subject. The comparison stimulus was an object-picture and was presented visually by slide in a tachistoscope. The interstimulus interval was .05 sec. or 2.5 sec. Analysis indicated that the left-preference group showed right-hand superiority, and the right-preference group showed left-hand superiority. The notion of individual hemisphericity was supported in tactile processing.

Evaluating Remapped Physical Reach for Hand Interactions with Passive Haptics in Virtual Reality.

PubMed

Han, Dustin T; Suhail, Mohamed; Ragan, Eric D

2018-04-01

Virtual reality often uses motion tracking to incorporate physical hand movements into interaction techniques for selection and manipulation of virtual objects. To increase realism and allow direct hand interaction, real-world physical objects can be aligned with virtual objects to provide tactile feedback and physical grasping. However, unless a physical space is custom configured to match a specific virtual reality experience, the ability to perfectly match the physical and virtual objects is limited. Our research addresses this challenge by studying methods that allow one physical object to be mapped to multiple virtual objects that can exist at different virtual locations in an egocentric reference frame. We study two such techniques: one that introduces a static translational offset between the virtual and physical hand before a reaching action, and one that dynamically interpolates the position of the virtual hand during a reaching motion. We conducted two experiments to assess how the two methods affect reaching effectiveness, comfort, and ability to adapt to the remapping techniques when reaching for objects with different types of mismatches between physical and virtual locations. We also present a case study to demonstrate how the hand remapping techniques could be used in an immersive game application to support realistic hand interaction while optimizing usability. Overall, the translational technique performed better than the interpolated reach technique and was more robust for situations with larger mismatches between virtual and physical objects.

Age and sex differences in ranges of motion and motion patterns.

PubMed

Hwang, Jaejin; Jung, Myung-Chul

2015-01-01

This study investigated the effects of age and sex on joint ranges of motion (ROMs) and motion patterns. Forty participants performed 18 motions using eight body segments at self-selected speeds. Older subjects showed smaller ROMs than younger subjects for 11 motions; the greatest difference in ROM was 44.9% for eversion/inversion of the foot. Older subjects also required more time than younger subjects to approach the peak angular velocity for six motions. In contrast, sex significantly affected ROMs but not motion patterns. Male subjects exhibited smaller ROMs than female subjects for four motions; the greatest sex-dependent difference in ROM was 29.7% for ulnar/radial deviation of the hand. The age and sex effects depended on the specific segments used and motions performed, possibly because of differences in anatomical structures and frequencies of use of the joints in habitual physical activities between the groups.

Development of a robotic evaluation system for the ability of proprioceptive sensation in slow hand motion.

PubMed

Tanaka, Yoshiyuki; Mizoe, Genki; Kawaguchi, Tomohiro

2015-01-01

This paper proposes a simple diagnostic methodology for checking the ability of proprioceptive/kinesthetic sensation by using a robotic device. The perception ability of virtual frictional forces is examined in operations of the robotic device by the hand at a uniform slow velocity along the virtual straight/circular path. Experimental results by healthy subjects demonstrate that percentage of correct answers for the designed perceptual tests changes in the motion direction as well as the arm configuration and the HFM (human force manipulability) measure. It can be supposed that the proposed methodology can be applied into the early detection of neuromuscular/neurological disorders.

Hand VR Exergame for Occupational Health Care.

PubMed

Ortiz, Saskia; Uribe-Quevedo, Alvaro; Kapralos, Bill

2016-01-01

The widespread use and ubiquity of mobile computing technologies such as smartphones, tablets, laptops and portable gaming consoles has led to an increase in musculoskeletal disorders due to overuse, bad posture, repetitive movements, fixed postures and physical de-conditioning caused by low muscular demands while using (and over-using) these devices. In this paper we present the development of a hand motion-based virtual reality-based exergame for occupational health purposes that allows the user to perform simple exercises using a cost-effective non-invasive motion capture device to help overcome and prevent some of the muskoloskeletal problems associated with the over-use of keyboards and mobile devices.

Sparse Coding of Natural Human Motion Yields Eigenmotions Consistent Across People

NASA Astrophysics Data System (ADS)

Thomik, Andreas; Faisal, A. Aldo

2015-03-01

Providing a precise mathematical description of the structure of natural human movement is a challenging problem. We use a data-driven approach to seek a generative model of movement capturing the underlying simplicity of spatial and temporal structure of behaviour observed in daily life. In perception, the analysis of natural scenes has shown that sparse codes of such scenes are information theoretic efficient descriptors with direct neuronal correlates. Translating from perception to action, we identify a generative model of movement generation by the human motor system. Using wearable full-hand motion capture, we measure the digit movement of the human hand in daily life. We learn a dictionary of ``eigenmotions'' which we use for sparse encoding of the movement data. We show that the dictionaries are generally well preserved across subjects with small deviations accounting for individuality of the person and variability in tasks. Further, the dictionary elements represent motions which can naturally describe hand movements. Our findings suggest the motor system can compose complex movement behaviours out of the spatially and temporally sparse activation of ``eigenmotion'' neurons, and is consistent with data on grasp-type specificity of specialised neurons in the premotor cortex. Andreas is supported by the Luxemburg Research Fund (1229297).

A System for Video Surveillance and Monitoring CMU VSAM Final Report

DTIC Science & Technology

1999-11-30

motion-based skeletonization, neural network , spatio-temporal salience Patterns inside image chips, spurious motion rejection, model -based... network of sensors with respect to the model coordinate system, computation of 3D geolocation estimates, and graphical display of object hypotheses...rithms have been developed. The first uses view dependent visual properties to train a neural network classifier to recognize four classes: single

Tongue motor training support system.

PubMed

Sasaki, Makoto; Onishi, Kohei; Nakayama, Atsushi; Kamata, Katsuhiro; Stefanov, Dimitar; Yamaguchi, Masaki

2014-01-01

In this paper, we introduce a new tongue-training system that can be used for improvement of the tongue's range of motion and muscle strength after dysphagia. The training process is organized in game-like manner. Initially, we analyzed surface electromyography (EMG) signals of the suprahyoid muscles of five subjects during tongue-training motions. This test revealed that four types tongue training motions and a swallowing motion could be classified with 93.5% accuracy. Recognized EMG signals during tongue motions were designed to allow control of a mouse cursor via intentional tongue motions. Results demonstrated that simple PC games could be played by tongue motions, achieving in this way efficient, enjoyable and pleasant tongue training. Using the proposed method, dysphagia patients can choose games that suit their preferences and/or state of mind. It is expected that the proposed system will be an efficient tool for long-term tongue motor training and maintaining patients' motivation.

EVALUATION AND TREATMENT OF A PATIENT DIAGNOSED WITH ADHESIVE CAPSULITIS CLASSIFIED AS A DERANGEMENT USING THE MCKENZIE METHOD: A CASE REPORT.

PubMed

Bowser, Ashley; Swanson, Brian T

2016-08-01

The McKenzie Method of mechanical diagnosis and therapy (MDT) is supported in the literature as a valid and reliable approach to the management of spine injuries. It can also be applied to the peripheral joints, but has not been explored through research to the same extent. This method sub-classifies an injury based on tissue response to mechanical loading and repeated motion testing, with directional preferences identified in the exam used to guide treatment. The purpose of this case report is to demonstrate the assessment, intervention, and clinical outcomes of a subject classified as having a shoulder derangement syndrome using MDT methodology. The subject was a 52-year-old female with a four-week history of insidious onset left shoulder pain, referred to physical therapy with a medical diagnosis of adhesive capsulitis. She presented with pain (4-7/10 on the visual analog scale [VAS]) and decreased shoulder range of motion that limited her activities of daily living and work capabilities (Upper Extremity Functional Index (UEFI) score: 55/80). Active and passive ranges of motion (A/PROM) were limited in all planes. Repeated motion testing was performed, with an immediate reduction in pain and increased shoulder motion in all planes following repeated shoulder extension. As a result, her MDT classification was determined to be derangement syndrome. Treatment involved specific exercises, primarily repeated motions, identified as symptom alleviating during the evaluation process. The subject demonstrated significant improvements in the UEFI (66/80), VAS (0-2/10), and ROM within six visits over eight weeks. At the conclusion of treatment, A/PROM was observed to be equal to the R shoulder without pain. This subject demonstrated improved symptoms and functional abilities following evaluation and treatment using MDT methodology. While a cause-effect relationship cannot be determined with a single case, MDT methodology may be a useful approach to the examination, and potentially management, of patients with shoulder pain. This method offers a patient specific approach to treating the shoulder, particularly when the pathoanatomic structure affected is unclear. 4.

Efficacy of Low Level Laser Therapy After Hand Flexor Tendon Repair

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

Ayad, K. E.; Abd El Mejeed, S. F.; El Gohary, H. M.

Flexor tendon injury is a common problem requiring suturing repair followed by early postoperative mobilization. Muscle atrophy, joint stiffness, osteoarthritis, infection, skin necrosis, ulceration of joint cartilage and tendocutaneous adhesion are familiar complications produced by prolonged immobilization of surgically repaired tendon ruptures. The purpose of this study was to clarify the importance of low level laser therapy after hand flexor tendon repair in zone II. Thirty patients aging between 20 and 40 years were divided into two groups. Patients in group A (n = 15) received a conventional therapeutic exercise program while patients in group B (n = 15) receivedmore » low level laser therapy combined with the same therapeutic exercise program. The results showed a statistically significant increase in total active motion of the proximal and distal interphalangeal joints as well as maximum hand grip strength at three weeks and three months postoperative, but improvement was more significant in group B. It was concluded that the combination of low level laser therapy and early therapeutic exercises was more effective than therapeutic exercises alone in improving total active motion of proximal and distal interphalangeal joints and hand grip strength after hand flexor tendon repair.« less

Motion-compensated hand-held common-path Fourier-domain optical coherence tomography probe for image-guided intervention

NASA Astrophysics Data System (ADS)

Huang, Yong; Song, Cheol; Liu, Xuan; Kang, Jin U.

2013-03-01

A motion-compensated hand-held common-path Fourier-domain optical coherence tomography imaging probe has been developed for image guided intervention during microsurgery. A hand-held prototype instrument was designed and fabricated by integrating an imaging fiber probe inside a stainless steel needle which is attached to the ceramic shaft of a piezoelectric motor housed in an aluminum handle. The fiber probe obtains A-scan images. The distance information was extracted from the A-scans to track the sample surface distance and a fixed distance was maintained by a feedback motor control which effectively compensated hand tremor and target movements in the axial direction. Graphical user interface, real-time data processing, and visualization based on a CPU-GPU hybrid programming architecture were developed and used in the implantation of this system. To validate the system, free-hand optical coherence tomography images using various samples were obtained. The system can be easily integrated into microsurgical tools and robotics for a wide range of clinical applications. Such tools could offer physicians the freedom to easily image sites of interest with reduced risk and higher image quality.

Biomechanical analysis of the circular friction hand massage.

PubMed

Ryu, Jeseong; Son, Jongsang; Ahn, Soonjae; Shin, Isu; Kim, Youngho

2015-01-01

A massage can be beneficial to relieve muscle tension on the neck and shoulder area. Various massage systems have been developed, but their motions are not uniform throughout different body parts nor specifically targeted to the neck and shoulder areas. Pressure pattern and finger movement trajectories of the circular friction hand massage on trapezius, levator scapulae, and deltoid muscles were determined to develop a massage system that can mimic the motion and the pressure of the circular friction massage. During the massage, finger movement trajectories were measured using a 3D motion capture system, and finger pressures were simultaneously obtained using a grip pressure sensor. Results showed that each muscle had different finger movement trajectory and pressure pattern. The trapezius muscle experienced a higher pressure, longer massage time (duration of pressurization), and larger pressure-time integral than the other muscles. These results could be useful to design a better massage system simulating human finger movements.

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

NASA Technical Reports Server (NTRS)

Dickenson, Reuben D.; Lorenz, Christine H.; Peterson, Steven W.; Strauss, Alvin M.; Main, John A.

1992-01-01

A new method for analyzing the kinematics of joint motion using magnetic resonance imaging (MRI) is described. The reconstruction of the metacarpalphalangeal joint of the left index finger into a 3D graphic display is shown. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones are obtained and processed by analyzing the screw motion of the joint. Landmark positions are chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily 2D planar motion of this joint is then studied using a method of constructing coordinate systems using three or more points. A transformation matrix based on a world coordinate system describes the location and orientation of the local target coordinate system. The findings show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove design for EVA.

Towards Development of Robotic Aid for Rehabilitation of Locomotion-Impaired Subjects

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.

2000-01-01

Manual assistance of therapists to help movement of legs of spinal cord injured (SCI) subjects during stepping on a treadmill for locomotion rehabilitation has severe economic and technical limitations. Scientists at the Department of Physiological Science at the University of California Los Angeles (UCLA) and roboticists at the Jet Propulsion Laboratory (JPL) initiated a joint effort to develop a robotic mechanism capable of performing controlled motions equivalent to the arm and hand motions of therapists assisting the stepping of locomotion impaired subjects on a treadmill, while the subjects' body weight is partially supported by an overhead harness. A first necessary technical step towards this development is to measure and understand the kinematics and dynamics of the therapists' arm and hand motions as they are reflected on the subjects' leg movement. This paper describes an initial measurement system developed for this purpose together with the related measurement results, and outlines the planned future technical work.

Observation and Classification of Prehension in Preschool Children: A Reliability Study.

ERIC Educational Resources Information Center

Moss, S. C.; Hogg, J.

1981-01-01

The variety of hand grips of 12 children, most of whom were moderately or severely retarded, were classified in order to begin an analysis of hand function. Test reliability was not as great when items were presented to the children as compared to when children were observed or rated by videotape. (FG)

Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network

PubMed Central

Zhai, Xiaolong; Jelfs, Beth; Chan, Rosa H. M.; Tin, Chung

2017-01-01

Hand movement classification based on surface electromyography (sEMG) pattern recognition is a promising approach for upper limb neuroprosthetic control. However, maintaining day-to-day performance is challenged by the non-stationary nature of sEMG in real-life operation. In this study, we propose a self-recalibrating classifier that can be automatically updated to maintain a stable performance over time without the need for user retraining. Our classifier is based on convolutional neural network (CNN) using short latency dimension-reduced sEMG spectrograms as inputs. The pretrained classifier is recalibrated routinely using a corrected version of the prediction results from recent testing sessions. Our proposed system was evaluated with the NinaPro database comprising of hand movement data of 40 intact and 11 amputee subjects. Our system was able to achieve ~10.18% (intact, 50 movement types) and ~2.99% (amputee, 10 movement types) increase in classification accuracy averaged over five testing sessions with respect to the unrecalibrated classifier. When compared with a support vector machine (SVM) classifier, our CNN-based system consistently showed higher absolute performance and larger improvement as well as more efficient training. These results suggest that the proposed system can be a useful tool to facilitate long-term adoption of prosthetics for amputees in real-life applications. PMID:28744189

Self-Recalibrating Surface EMG Pattern Recognition for Neuroprosthesis Control Based on Convolutional Neural Network.

PubMed

Zhai, Xiaolong; Jelfs, Beth; Chan, Rosa H M; Tin, Chung

2017-01-01

Hand movement classification based on surface electromyography (sEMG) pattern recognition is a promising approach for upper limb neuroprosthetic control. However, maintaining day-to-day performance is challenged by the non-stationary nature of sEMG in real-life operation. In this study, we propose a self-recalibrating classifier that can be automatically updated to maintain a stable performance over time without the need for user retraining. Our classifier is based on convolutional neural network (CNN) using short latency dimension-reduced sEMG spectrograms as inputs. The pretrained classifier is recalibrated routinely using a corrected version of the prediction results from recent testing sessions. Our proposed system was evaluated with the NinaPro database comprising of hand movement data of 40 intact and 11 amputee subjects. Our system was able to achieve ~10.18% (intact, 50 movement types) and ~2.99% (amputee, 10 movement types) increase in classification accuracy averaged over five testing sessions with respect to the unrecalibrated classifier. When compared with a support vector machine (SVM) classifier, our CNN-based system consistently showed higher absolute performance and larger improvement as well as more efficient training. These results suggest that the proposed system can be a useful tool to facilitate long-term adoption of prosthetics for amputees in real-life applications.

Design of a haptic device with grasp and push-pull force feedback for a master-slave surgical robot.

PubMed

Hu, Zhenkai; Yoon, Chae-Hyun; Park, Samuel Byeongjun; Jo, Yung-Ho

2016-07-01

We propose a portable haptic device providing grasp (kinesthetic) and push-pull (cutaneous) sensations for optical-motion-capture master interfaces. Although optical-motion-capture master interfaces for surgical robot systems can overcome the stiffness, friction, and coupling problems of mechanical master interfaces, it is difficult to add haptic feedback to an optical-motion-capture master interface without constraining the free motion of the operator's hands. Therefore, we utilized a Bowden cable-driven mechanism to provide the grasp and push-pull sensation while retaining the free hand motion of the optical-motion capture master interface. To evaluate the haptic device, we construct a 2-DOF force sensing/force feedback system. We compare the sensed force and the reproduced force of the haptic device. Finally, a needle insertion test was done to evaluate the performance of the haptic interface in the master-slave system. The results demonstrate that both the grasp force feedback and the push-pull force feedback provided by the haptic interface closely matched with the sensed forces of the slave robot. We successfully apply our haptic interface in the optical-motion-capture master-slave system. The results of the needle insertion test showed that our haptic feedback can provide more safety than merely visual observation. We develop a suitable haptic device to produce both kinesthetic grasp force feedback and cutaneous push-pull force feedback. Our future research will include further objective performance evaluations of the optical-motion-capture master-slave robot system with our haptic interface in surgical scenarios.

Compliant finger sensor for sensorimotor studies in MEG and MR environment

NASA Astrophysics Data System (ADS)

Li, Y.; Yong, X.; Cheung, T. P. L.; Menon, C.

2016-07-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are widely used for functional brain imaging. The correlations between the sensorimotor functions of the hand and brain activities have been investigated in MEG/fMRI studies. Currently, limited information can be drawn from these studies due to the limitations of existing motion sensors that are used to detect hand movements. One major challenge in designing these motion sensors is to limit the signal interference between the motion sensors and the MEG/fMRI. In this work, a novel finger motion sensor, which contains low-ferromagnetic and non-conductive materials, is introduced. The finger sensor consists of four air-filled chambers. When compressed by finger(s), the pressure change in the chambers can be detected by the electronics of the finger sensor. Our study has validated that the interference between the finger sensor and an MEG is negligible. Also, by applying a support vector machine algorithm to the data obtained from the finger sensor, at least 11 finger patterns can be discriminated. Comparing to the use of traditional electromyography (EMG) in detecting finger motion, our proposed finger motion sensor is not only MEG/fMRI compatible, it is also easy to use. As the signals acquired from the sensor have a higher SNR than that of the EMG, no complex algorithms are required to detect different finger movement patterns. Future studies can utilize this motion sensor to investigate brain activations during different finger motions and correlate the activations with the sensory and motor functions respectively.

Motion representation of the long fingers: a proposal for the definitions of new anatomical frames.

PubMed

Coupier, Jérôme; Moiseev, Fédor; Feipel, Véronique; Rooze, Marcel; Van Sint Jan, Serge

2014-04-11

Despite the availability of the International Society of Biomechanics (ISB) recommendations for the orientation of anatomical frames, no consensus exists about motion representations related to finger kinematics. This paper proposes novel anatomical frames for motion representation of the phalangeal segments of the long fingers. A three-dimensional model of a human forefinger was acquired from a non-pathological fresh-frozen hand. Medical imaging was used to collect phalangeal discrete positions. Data processing was performed using a customized software interface ("lhpFusionBox") to create a specimen-specific model and to reconstruct the discrete motion path. Five examiners virtually palpated two sets of landmarks. These markers were then used to build anatomical frames following two methods: a reference method following ISB recommendations and a newly-developed method based on the mean helical axis (HA). Motion representations were obtained and compared between examiners. Virtual palpation precision was around 1mm, which is comparable to results from the literature. The comparison of the two methods showed that the helical axis method seemed more reproducible between examiners especially for secondary, or accessory, motions. Computed Root Mean Square distances comparing methods showed that the ISB method displayed a variability 10 times higher than the HA method. The HA method seems to be suitable for finger motion representation using discrete positions from medical imaging. Further investigations are required before being able to use the methodology with continuous tracking of markers set on the subject's hand. Copyright © 2014 Elsevier Ltd. All rights reserved.

Treb-Bot: Development and Use of a Trebuchet Simulator

ERIC Educational Resources Information Center

Constans, Eric; Constans, Aileen

2015-01-01

The trebuchet has quickly become a favorite project for physics and engineering teachers seeking to provide students with a simple, but spectacular, hands-on design project that can be applied to the study of projectile motion, rotational motion, and the law of conservation of energy. While there have been free trebuchet simulators and range…

Reduced Sensitivity to Minimum-Jerk Biological Motion in Autism Spectrum Conditions

ERIC Educational Resources Information Center

Cook, Jennifer; Saygin, Ayse Pinar; Swain, Rachel; Blakemore, Sarah-Jayne

2009-01-01

We compared psychophysical thresholds for biological and non-biological motion detection in adults with autism spectrum conditions (ASCs) and controls. Participants watched animations of a biological stimulus (a moving hand) or a non-biological stimulus (a falling tennis ball). The velocity profile of the movement was varied between 100% natural…

Path integration in tactile perception of shapes.

PubMed

Moscatelli, Alessandro; Naceri, Abdeldjallil; Ernst, Marc O

2014-11-01

Whenever we move the hand across a surface, tactile signals provide information about the relative velocity between the skin and the surface. If the system were able to integrate the tactile velocity information over time, cutaneous touch may provide an estimate of the relative displacement between the hand and the surface. Here, we asked whether humans are able to form a reliable representation of the motion path from tactile cues only, integrating motion information over time. In order to address this issue, we conducted three experiments using tactile motion and asked participants (1) to estimate the length of a simulated triangle, (2) to reproduce the shape of a simulated triangular path, and (3) to estimate the angle between two-line segments. Participants were able to accurately indicate the length of the path, whereas the perceived direction was affected by a direction bias (inward bias). The response pattern was thus qualitatively similar to the ones reported in classical path integration studies involving locomotion. However, we explain the directional biases as the result of a tactile motion aftereffect. Copyright © 2014 Elsevier B.V. All rights reserved.

Motion Analysis System for Instruction of Nihon Buyo using Motion Capture

NASA Astrophysics Data System (ADS)

Shinoda, Yukitaka; Murakami, Shingo; Watanabe, Yuta; Mito, Yuki; Watanuma, Reishi; Marumo, Mieko

The passing on and preserving of advanced technical skills has become an important issue in a variety of fields, and motion analysis using motion capture has recently become popular in the research of advanced physical skills. This research aims to construct a system having a high on-site instructional effect on dancers learning Nihon Buyo, a traditional dance in Japan, and to classify Nihon Buyo dancing according to style, school, and dancer's proficiency by motion analysis. We have been able to study motion analysis systems for teaching Nihon Buyo now that body-motion data can be digitized and stored by motion capture systems using high-performance computers. Thus, with the aim of developing a user-friendly instruction-support system, we have constructed a motion analysis system that displays a dancer's time series of body motions and center of gravity for instructional purposes. In this paper, we outline this instructional motion analysis system based on three-dimensional position data obtained by motion capture. We also describe motion analysis that we performed based on center-of-gravity data obtained by this system and motion analysis focusing on school and age group using this system.

Reliability and validity of the delta finger-to-palm (FTP), a new measure of finger range of motion in systemic sclerosis

PubMed Central

Torok, Kathryn S.; Baker, Nancy A.; Lucas, Mary; Domsic, Robyn T.; Boudreau, Robert; Medsger, Thomas A.

2010-01-01

Objectives To determine the reliability and validity of a new measure of finger motion in patients with systemic sclerosis (SSc), the ‘delta finger-to-palm’ (delta FTP) and compare its psychometric properties to the traditional measure of finger motion, the finger-to-palm (FTP). Methods Phase 1: The reliability of the delta FTP and FTP were examined in 39 patients with SSc. Phase 2: Criterion and convergent construct validity of both measures were examined in 17 patients with SSc by comparing them to other clinical measures: Total Active Range of Motion (TAROM), Hand Mobility in Scleroderma (HAMIS), the Duruoz Hand Index (DHI), Health Assessment Questionnaire (HAQ), and modified Rodnan skin score (mRSS). Phase 3: Sensitivity to change of the delta FTP was investigated in 24 patients with early diffuse cutaneous SSc. Results Both measures had excellent intra-rater and inter-rater reliability (ICC 0.92 to 0.99). Fair to strong correlations (rs=0.49–0.94) were observed between the delta FTP and TAROM, HAMIS, and DHI. Fair to moderate correlations were observed between delta FTP and HAQ components related to hand function and upper extremity mRSS. Correlations of the traditional FTP with these measures were fair to strong, but most often the delta FTP outperformed the FTP. The effect size and standardised response mean for the mean delta FTP were 0.50 and 1.10 respectively, over a 2–8 month period. Conclusion The delta FTP is a valid and reliable measure of finger motion in patients with SSc which outperforms the FTP. PMID:20576211

Comparison of the clinical and functional outcomes following 3- and 4-corner fusions.

PubMed

Singh, Harvinder P; Dias, Joseph J; Phadnis, Joideep; Bain, Gregory

2015-06-01

To explore the clinical and functional outcomes of 3-corner fusion (3CF) for stage 2 and 3 scapholunate advanced collapse and scaphoid nonunion advanced collapse. We compared the results with 4-corner fusion (4CF) using a recent published report. Twelve patients (8 men and 4 women) who had a 3CF, mean age 60 years (range, 34-75 y) were reviewed in clinic more than 1 year after surgery. Subjective outcome measures included the Michigan Hand Questionnaire and Patient Evaluation Measure. Objective outcome measures included range of motion with a flexible electrogoniometer and grip strength measured with a digital dynamometer. The results were compared using a recent report of 24 patients (17 men and 7 women) with a 4CF, mean age 55 years (range, 34-68 y) assessed with similar techniques. The patients receiving 3CF had better subjective scores with the Michigan Hand Questionnaire, including the sub-scores for activities of daily living and satisfaction. The radioulnar arc was greater after the 3CF than after the 4CF. Circumduction of the 3CF was more like a normal wrist than the 4CF. This included having faster and smoother motion, with an axis of circumduction closer to the normal wrist. Peak grip strength was similar after either a 3CF or 4CF but grip strength in the 3CF was 82% of the contralateral wrist compared with 59% for the 4CF. The 3CF provided better patient-rated scores and the arc of wrist motion was more extended, with greater ulnar deviation. Motion was smoother and more closely replicated the normal axis and functional motion of the wrist. Therapeutic III. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

A zero phase adaptive fuzzy Kalman filter for physiological tremor suppression in robotically assisted minimally invasive surgery.

PubMed

Sang, Hongqiang; Yang, Chenghao; Liu, Fen; Yun, Jintian; Jin, Guoguang; Chen, Fa

2016-12-01

Hand physiological tremor of surgeons can cause vibration at the surgical instrument tip, which may make it difficult for the surgeon to perform fine manipulations of tissue, needles, and sutures. A zero phase adaptive fuzzy Kalman filter (ZPAFKF) is proposed to suppress hand tremor and vibration of a robotic surgical system. The involuntary motion can be reduced by adding a compensating signal that has the same magnitude and frequency but opposite phase with the tremor signal. Simulations and experiments using different filters were performed. Results show that the proposed filter can avoid the loss of useful motion information and time delay, and better suppress minor and varying tremor. The ZPAFKF can provide less error, preferred accuracy, better tremor estimation, and more desirable compensation performance, to suppress hand tremor and decrease vibration at the surgical instrument tip. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Quality Control of Structural MRI Images Applied Using FreeSurfer—A Hands-On Workflow to Rate Motion Artifacts

PubMed Central

Backhausen, Lea L.; Herting, Megan M.; Buse, Judith; Roessner, Veit; Smolka, Michael N.; Vetter, Nora C.

2016-01-01

In structural magnetic resonance imaging motion artifacts are common, especially when not scanning healthy young adults. It has been shown that motion affects the analysis with automated image-processing techniques (e.g., FreeSurfer). This can bias results. Several developmental and adult studies have found reduced volume and thickness of gray matter due to motion artifacts. Thus, quality control is necessary in order to ensure an acceptable level of quality and to define exclusion criteria of images (i.e., determine participants with most severe artifacts). However, information about the quality control workflow and image exclusion procedure is largely lacking in the current literature and the existing rating systems differ. Here, we propose a stringent workflow of quality control steps during and after acquisition of T1-weighted images, which enables researchers dealing with populations that are typically affected by motion artifacts to enhance data quality and maximize sample sizes. As an underlying aim we established a thorough quality control rating system for T1-weighted images and applied it to the analysis of developmental clinical data using the automated processing pipeline FreeSurfer. This hands-on workflow and quality control rating system will aid researchers in minimizing motion artifacts in the final data set, and therefore enhance the quality of structural magnetic resonance imaging studies. PMID:27999528

Neural representations of kinematic laws of motion: evidence for action-perception coupling.

PubMed

Dayan, Eran; Casile, Antonino; Levit-Binnun, Nava; Giese, Martin A; Hendler, Talma; Flash, Tamar

2007-12-18

Behavioral and modeling studies have established that curved and drawing human hand movements obey the 2/3 power law, which dictates a strong coupling between movement curvature and velocity. Human motion perception seems to reflect this constraint. The functional MRI study reported here demonstrates that the brain's response to this law of motion is much stronger and more widespread than to other types of motion. Compliance with this law is reflected in the activation of a large network of brain areas subserving motor production, visual motion processing, and action observation functions. Hence, these results strongly support the notion of similar neural coding for motion perception and production. These findings suggest that cortical motion representations are optimally tuned to the kinematic and geometrical invariants characterizing biological actions.

Identifying factors of comfort in using hand tools.

PubMed

Kuijt-Evers, L F M; Groenesteijn, L; de Looze, M P; Vink, P

2004-09-01

To design comfortable hand tools, knowledge about comfort/discomfort in using hand tools is required. We investigated which factors determine comfort/discomfort in using hand tools according to users. Therefore, descriptors of comfort/discomfort in using hand tools were collected from literature and interviews. After that, the relatedness of a selection of the descriptors to comfort in using hand tools was investigated. Six comfort factors could be distinguished (functionality, posture and muscles, irritation and pain of hand and fingers, irritation of hand surface, handle characteristics, aesthetics). These six factors can be classified into three meaningful groups: functionality, physical interaction and appearance. The main conclusions were that (1) the same descriptors were related to comfort and discomfort in using hand tools, (2) descriptors of functionality are most related to comfort in using hand tools followed by descriptors of physical interaction and (3) descriptors of appearance become secondary in comfort in using hand tools.

Neural-Network Control Of Prosthetic And Robotic Hands

NASA Technical Reports Server (NTRS)

Buckley, Theresa M.

1991-01-01

Electronic neural networks proposed for use in controlling robotic and prosthetic hands and exoskeletal or glovelike electromechanical devices aiding intact but nonfunctional hands. Specific to patient, who activates grasping motion by voice command, by mechanical switch, or by myoelectric impulse. Patient retains higher-level control, while lower-level control provided by neural network analogous to that of miniature brain. During training, patient teaches miniature brain to perform specialized, anthropomorphic movements unique to himself or herself.

Effectiveness of a fine motor skills rehabilitation program on upper limb disability, manual dexterity, pinch strength, range of fingers motion, performance in activities of daily living, functional independency, and general self-efficacy in hand osteoarthritis: A randomized clinical trial.

PubMed

Pérez-Mármol, Jose Manuel; García-Ríos, Ma Carmen; Ortega-Valdivieso, María Azucena; Cano-Deltell, Enrique Elías; Peralta-Ramírez, María Isabel; Ickmans, Kelly; Aguilar-Ferrándiz, María Encarnación

A randomized clinical trial. Rehabilitation treatments for improving fine motor skills (FMS) in hand osteoarthritis (HOA) have not been well explored yet. To assess the effectiveness of a rehabilitation program on upper limb disability, independence of activities of daily living (ADLs), fine motor abilities, functional independency, and general self-efficacy in older adults with HOA. About 45 adults (74-86 years) with HOA were assigned to an experimental group for completing an FMS intervention or a control group receiving conventional occupational therapy. Both interventions were performed 3 times/wk, 45 minutes each session, during 8 weeks. Upper limb disability, performance in ADLs, pinch strength, manual dexterity, range of fingers motion, functional independency, and general self-efficacy were assessed at baseline, immediately after treatment, and after 2 months of follow-up. FMS group showed significant improvements with a small effect size on manual dexterity (P ≤ .034; d ≥ 0.48) and a moderate-high effect on range of index (P ≤ .018; d ≥ 0.58) and thumb (P ≤ .027; d ≥ 0.39) motion. The control group showed a significant worse range of motion over time in some joints at the index (P ≤ .037; d ≥ 0.36) finger and thumb (P ≤ .017; d ≥ 0.55). A rehabilitation intervention for FMS may improve manual dexterity and range of fingers motion in HOA, but its effects on upper limb disability, performance in ADLs, pinch strength, functionality, and self-efficacy remain uncertain. Specific interventions of the hand are needed to prevent a worsening in range of finger motion. 1b. Copyright © 2016 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

Multi-modal gesture recognition using integrated model of motion, audio and video

NASA Astrophysics Data System (ADS)

Goutsu, Yusuke; Kobayashi, Takaki; Obara, Junya; Kusajima, Ikuo; Takeichi, Kazunari; Takano, Wataru; Nakamura, Yoshihiko

2015-07-01

Gesture recognition is used in many practical applications such as human-robot interaction, medical rehabilitation and sign language. With increasing motion sensor development, multiple data sources have become available, which leads to the rise of multi-modal gesture recognition. Since our previous approach to gesture recognition depends on a unimodal system, it is difficult to classify similar motion patterns. In order to solve this problem, a novel approach which integrates motion, audio and video models is proposed by using dataset captured by Kinect. The proposed system can recognize observed gestures by using three models. Recognition results of three models are integrated by using the proposed framework and the output becomes the final result. The motion and audio models are learned by using Hidden Markov Model. Random Forest which is the video classifier is used to learn the video model. In the experiments to test the performances of the proposed system, the motion and audio models most suitable for gesture recognition are chosen by varying feature vectors and learning methods. Additionally, the unimodal and multi-modal models are compared with respect to recognition accuracy. All the experiments are conducted on dataset provided by the competition organizer of MMGRC, which is a workshop for Multi-Modal Gesture Recognition Challenge. The comparison results show that the multi-modal model composed of three models scores the highest recognition rate. This improvement of recognition accuracy means that the complementary relationship among three models improves the accuracy of gesture recognition. The proposed system provides the application technology to understand human actions of daily life more precisely.

Both hand position and movement direction modulate visual attention

PubMed Central

Festman, Yariv; Adam, Jos J.; Pratt, Jay; Fischer, Martin H.

2013-01-01

The current study explored effects of continuous hand motion on the allocation of visual attention. A concurrent paradigm was used to combine visually concealed continuous hand movements with an attentionally demanding letter discrimination task. The letter probe appeared contingent upon the moving right hand passing through one of six positions. Discrimination responses were then collected via a keyboard press with the static left hand. Both the right hand's position and its movement direction systematically contributed to participants' visual sensitivity. Discrimination performance increased substantially when the right hand was distant from, but moving toward the visual probe location (replicating the far-hand effect, Festman et al., 2013). However, this effect disappeared when the probe appeared close to the static left hand, supporting the view that static and dynamic features of both hands combine in modulating pragmatic maps of attention. PMID:24098288

Low-Fatigue Hand Controller For Remote Manipulator

NASA Technical Reports Server (NTRS)

Maclaren, Brice; Mcmurray, Gary; Lipkin, Harvey

1993-01-01

Universal master controller used in brace mode, in which user's forearm rests atop upper (forearm) module. Alternatively, user manipulates hand controller in side mode, which gives greater latitude for motion but requires more muscular effort. Controller provides six degrees of freedom and reflects, back to user, scaled versions of forces experienced by manipulator. Manipulator designed to condense work space into user's natural work volume. Operated by both right-handed and left-handed users. Does not interfere with user's natural movements or obstruct line of sight. Controller compact and portable.

Recognition of surgical skills using hidden Markov models

NASA Astrophysics Data System (ADS)

Speidel, Stefanie; Zentek, Tom; Sudra, Gunther; Gehrig, Tobias; Müller-Stich, Beat Peter; Gutt, Carsten; Dillmann, Rüdiger

2009-02-01

Minimally invasive surgery is a highly complex medical discipline and can be regarded as a major breakthrough in surgical technique. A minimally invasive intervention requires enhanced motor skills to deal with difficulties like the complex hand-eye coordination and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality techniques. To recognize and analyze the current situation for context-aware assistance, we need intraoperative sensor data and a model of the intervention. Characteristics of a situation are the performed activity, the used instruments, the surgical objects and the anatomical structures. Important information about the surgical activity can be acquired by recognizing the surgical gesture performed. Surgical gestures in minimally invasive surgery like cutting, knot-tying or suturing are here referred to as surgical skills. We use the motion data from the endoscopic instruments to classify and analyze the performed skill and even use it for skill evaluation in a training scenario. The system uses Hidden Markov Models (HMM) to model and recognize a specific surgical skill like knot-tying or suturing with an average recognition rate of 92%.

Onboard Classifiers for Science Event Detection on a Remote Sensing Spacecraft

NASA Technical Reports Server (NTRS)

Castano, Rebecca; Mazzoni, Dominic; Tang, Nghia; Greeley, Ron; Doggett, Thomas; Cichy, Ben; Chien, Steve; Davies, Ashley

2006-01-01

Typically, data collected by a spacecraft is downlinked to Earth and pre-processed before any analysis is performed. We have developed classifiers that can be used onboard a spacecraft to identify high priority data for downlink to Earth, providing a method for maximizing the use of a potentially bandwidth limited downlink channel. Onboard analysis can also enable rapid reaction to dynamic events, such as flooding, volcanic eruptions or sea ice break-up. Four classifiers were developed to identify cryosphere events using hyperspectral images. These classifiers include a manually constructed classifier, a Support Vector Machine (SVM), a Decision Tree and a classifier derived by searching over combinations of thresholded band ratios. Each of the classifiers was designed to run in the computationally constrained operating environment of the spacecraft. A set of scenes was hand-labeled to provide training and testing data. Performance results on the test data indicate that the SVM and manual classifiers outperformed the Decision Tree and band-ratio classifiers with the SVM yielding slightly better classifications than the manual classifier.

Automatic Identification of Motion Artifacts in EHG Recording for Robust Analysis of Uterine Contractions

PubMed Central

Ye-Lin, Yiyao; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. PMID:24523828

Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions.

PubMed

Ye-Lin, Yiyao; Garcia-Casado, Javier; Prats-Boluda, Gema; Alberola-Rubio, José; Perales, Alfredo

2014-01-01

Electrohysterography (EHG) is a noninvasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the TOCO-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and nonartifacted signals. To develop a classifier, a total of eleven spectral, temporal, and nonlinear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique.

Motion in action: A study of second graders' trajectories of experience during guided inquiry science instruction

NASA Astrophysics Data System (ADS)

Hapgood, Susanna Elizabeth

This interpretive case study describes a 10-day inquiry science program of study of motion down inclined planes during which a class of 21 second graders investigated scientific relationships such as mass and speed, speed and momentum, and mass and momentum via both text-based experiences ("second-hand investigations") and hands-on materials-based experiments ("first-hand investigations"). Data sources included over 11 hours of videotaped instruction in addition to children's written work, class-generated artifacts, and paper-and-pencil pre- and posttests. Content analyses informed by both sociocultural and developmental perspectives revealed that, in addition to a significant increase in pre- to posttest scores, children in the class engaged in several processes integral to inquiry, namely, (a) using data as evidence, (b) evaluating investigative procedures, and (c) making sense of multiple forms of representations. In addition, the study describes the range of and shifts in children's ideas about scientific relationships fundamental to developing an understanding of motion. Many children were observed to make causal attributions involving a relationship between two variables, such as the mass and momentum of a ball rolling down a ramp. Discussed are mediating factors such as the teacher's role in scaffolding the class's investigations and features of the innovative "scientists' notebook" texts, which were integral to the instruction. Also presented is evidence of first-hand and second-hand investigations working in concert to provide the elementary school students with rich opportunities to learn and to express their developing understandings of scientific ideas. This study provides a rare glimpse of primary-grade inquiry-based science instruction within a classroom context.

Push-To-Lock, Push-To-Release Mechanism

NASA Technical Reports Server (NTRS)

Lozano, Anselmo, Jr.

1991-01-01

Latch locked or unlocked with single motion of hand. No tools needed to operate it, and user easily opens or closes it with heavily gloved hand. When unlocked, stem free of main body. In locked state, dowel pins in main body hold stem. Latch equipped with lock and key so only authorized users operate it.

Motion data classification on the basis of dynamic time warping with a cloud point distance measure

NASA Astrophysics Data System (ADS)

Switonski, Adam; Josinski, Henryk; Zghidi, Hafedh; Wojciechowski, Konrad

2016-06-01

The paper deals with the problem of classification of model free motion data. The nearest neighbors classifier which is based on comparison performed by Dynamic Time Warping transform with cloud point distance measure is proposed. The classification utilizes both specific gait features reflected by a movements of subsequent skeleton joints and anthropometric data. To validate proposed approach human gait identification challenge problem is taken into consideration. The motion capture database containing data of 30 different humans collected in Human Motion Laboratory of Polish-Japanese Academy of Information Technology is used. The achieved results are satisfactory, the obtained accuracy of human recognition exceeds 90%. What is more, the applied cloud point distance measure does not depend on calibration process of motion capture system which results in reliable validation.

Advanced Techniques for Scene Analysis

DTIC Science & Technology

2010-06-01

robustness prefers a bigger intergration window to handle larger motions. The advantage of pyramidal implementation is that, while each motion vector dL...labeled SAR images. Now the previous algorithm leads to a more dedicated classifier for the particular target; however, our algorithm trades generality for...accuracy is traded for generality. 7.3.2 I-RELIEF Feature weighting transforms the original feature vector x into a new feature vector x′ by assigning each

sEMG-based joint force control for an upper-limb power-assist exoskeleton robot.

PubMed

Li, Zhijun; Wang, Baocheng; Sun, Fuchun; Yang, Chenguang; Xie, Qing; Zhang, Weidong

2014-05-01

This paper investigates two surface electromyogram (sEMG)-based control strategies developed for a power-assist exoskeleton arm. Different from most of the existing position control approaches, this paper develops force control methods to make the exoskeleton robot behave like humans in order to provide better assistance. The exoskeleton robot is directly attached to a user's body and activated by the sEMG signals of the user's muscles, which reflect the user's motion intention. In the first proposed control method, the forces of agonist and antagonist muscles pair are estimated, and their difference is used to produce the torque of the corresponding joints. In the second method, linear discriminant analysis-based classifiers are introduced as the indicator of the motion type of the joints. Then, the classifier's outputs together with the estimated force of corresponding active muscle determine the torque control signals. Different from the conventional approaches, one classifier is assigned to each joint, which decreases the training time and largely simplifies the recognition process. Finally, the extensive experiments are conducted to illustrate the effectiveness of the proposed approaches.

Classification of resistance to passive motion using minimum probability of error criterion.

PubMed

Chan, H C; Manry, M T; Kondraske, G V

1987-01-01

Neurologists diagnose many muscular and nerve disorders by classifying the resistance to passive motion of patients' limbs. Over the past several years, a computer-based instrument has been developed for automated measurement and parameterization of this resistance. In the device, a voluntarily relaxed lower extremity is moved at constant velocity by a motorized driver. The torque exerted on the extremity by the machine is sampled, along with the angle of the extremity. In this paper a computerized technique is described for classifying a patient's condition as 'Normal' or 'Parkinson disease' (rigidity), from the torque versus angle curve for the knee joint. A Legendre polynomial, fit to the curve, is used to calculate a set of eight normally distributed features of the curve. The minimum probability of error approach is used to classify the curve as being from a normal or Parkinson disease patient. Data collected from 44 different subjects was processes and the results were compared with an independent physician's subjective assessment of rigidity. There is agreement in better than 95% of the cases, when all of the features are used.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.

PubMed

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-10-20

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

PubMed Central

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-01-01

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. PMID:27775625

Use of Design Patterns According to Hand Dominance in a Mobile User Interface

ERIC Educational Resources Information Center

Al-Samarraie, Hosam; Ahmad, Yusof

2016-01-01

User interface (UI) design patterns for mobile applications provide a solution to design problems and can improve the usage experience for users. However, there is a lack of research categorizing the uses of design patterns according to users' hand dominance in a learning-based mobile UI. We classified the main design patterns for mobile…

Musculoskeletal model-based control interface mimics physiologic hand dynamics during path tracing task

NASA Astrophysics Data System (ADS)

Crouch, Dustin L.; (Helen Huang, He

2017-06-01

Objective. We investigated the feasibility of a novel, customizable, simplified EMG-driven musculoskeletal model for estimating coordinated hand and wrist motions during a real-time path tracing task. Approach. A two-degree-of-freedom computational musculoskeletal model was implemented for real-time EMG-driven control of a stick figure hand displayed on a computer screen. After 5-10 minutes of undirected practice, subjects were given three attempts to trace 10 straight paths, one at a time, with the fingertip of the virtual hand. Able-bodied subjects completed the task on two separate test days. Main results. Across subjects and test days, there was a significant linear relationship between log-transformed measures of accuracy and speed (Pearson’s r  =  0.25, p  <  0.0001). The amputee subject could coordinate movement between the wrist and MCP joints, but favored metacarpophalangeal joint motion more highly than able-bodied subjects in 8 of 10 trials. For able-bodied subjects, tracing accuracy was lower at the extremes of the model’s range of motion, though there was no apparent relationship between tracing accuracy and fingertip location for the amputee. Our result suggests that, unlike able-bodied subjects, the amputee’s motor control patterns were not accustomed to the multi-joint dynamics of the wrist and hand, possibly as a result of post-amputation cortical plasticity, disuse, or sensory deficits. Significance. To our knowledge, our study is one of very few that have demonstrated the real-time simultaneous control of multi-joint movements, especially wrist and finger movements, using an EMG-driven musculoskeletal model, which differs from the many data-driven algorithms that dominate the literature on EMG-driven prosthesis control. Real-time control was achieved with very little training and simple, quick (~15 s) calibration. Thus, our model is potentially a practical and effective control platform for multifunctional myoelectric prostheses that could restore more life-like hand function for individuals with upper limb amputation.

Digital ranges of motion: normal values in young adults.

PubMed

Mallon, W J; Brown, H R; Nunley, J A

1991-09-01

Analysis of the range of motion of fingers was done in young (eighteen to thirty-five year old) adult volunteers with no history of previous injury to their hands. The data show that there are slight differences between the individual digits. Notably, metacarpophalangeal flexion and total active motion increase linearly in proceeding from the index to the small finger. There were also minor differences in comparing sexes. Women have greater extension at the metacarpophalangeal joint in both active and passive motion and have a greater total active motion at all digits as a result. A significant tenodesis effect was found at the distal interphalangeal joint in normal subjects. No differences were found that could be attributable to handedness.

Automated Finger Spelling by Highly Realistic 3D Animation

ERIC Educational Resources Information Center

Adamo-Villani, Nicoletta; Beni, Gerardo

2004-01-01

We present the design of a new 3D animation tool for self-teaching (signing and reading) finger spelling the first basic component in learning any sign language. We have designed a highly realistic hand with natural animation of the finger motions. Smoothness of motion (in real time) is achieved via programmable blending of animation segments. The…

Astronomy Resources for Intercurricular Elementary Science (ARIES): Exploring Motion and Forces. What Works Clearinghouse Intervention Report

ERIC Educational Resources Information Center

What Works Clearinghouse, 2012

2012-01-01

"ARIES: Exploring Motion and Forces" is a physical science curriculum for students in grades 5-8 that employs 18 inquiry-centered, hands-on lessons called "explorations." The curriculum draws upon students' curiosity to explore phenomena, allowing for a discovery-based learning process. Group-centered lab work is designed to…

Friction. Physical Science in Action[TM]. Schlessinger Science Library. [Videotape].

ERIC Educational Resources Information Center

2000

Most people think friction is what happens when two things are rubbed together. But there's so much more! Friction is a force that resists motion. Yet, without friction, motion would be impossible. Students will learn more about this natural force and the attempts made at controlling it in the world. Includes a hands-on activity and graphic…

The Equations of Oceanic Motions

NASA Astrophysics Data System (ADS)

Müller, Peter

2006-10-01

Modeling and prediction of oceanographic phenomena and climate is based on the integration of dynamic equations. The Equations of Oceanic Motions derives and systematically classifies the most common dynamic equations used in physical oceanography, from large scale thermohaline circulations to those governing small scale motions and turbulence. After establishing the basic dynamical equations that describe all oceanic motions, M|ller then derives approximate equations, emphasizing the assumptions made and physical processes eliminated. He distinguishes between geometric, thermodynamic and dynamic approximations and between the acoustic, gravity, vortical and temperature-salinity modes of motion. Basic concepts and formulae of equilibrium thermodynamics, vector and tensor calculus, curvilinear coordinate systems, and the kinematics of fluid motion and wave propagation are covered in appendices. Providing the basic theoretical background for graduate students and researchers of physical oceanography and climate science, this book will serve as both a comprehensive text and an essential reference.

Eye Tracking of Occluded Self-Moved Targets: Role of Haptic Feedback and Hand-Target Dynamics.

PubMed

Danion, Frederic; Mathew, James; Flanagan, J Randall

2017-01-01

Previous studies on smooth pursuit eye movements have shown that humans can continue to track the position of their hand, or a target controlled by the hand, after it is occluded, thereby demonstrating that arm motor commands contribute to the prediction of target motion driving pursuit eye movements. Here, we investigated this predictive mechanism by manipulating both the complexity of the hand-target mapping and the provision of haptic feedback. Two hand-target mappings were used, either a rigid (simple) one in which hand and target motion matched perfectly or a nonrigid (complex) one in which the target behaved as a mass attached to the hand by means of a spring. Target animation was obtained by asking participants to oscillate a lightweight robotic device that provided (or not) haptic feedback consistent with the target dynamics. Results showed that as long as 7 s after target occlusion, smooth pursuit continued to be the main contributor to total eye displacement (∼60%). However, the accuracy of eye-tracking varied substantially across experimental conditions. In general, eye-tracking was less accurate under the nonrigid mapping, as reflected by higher positional and velocity errors. Interestingly, haptic feedback helped to reduce the detrimental effects of target occlusion when participants used the nonrigid mapping, but not when they used the rigid one. Overall, we conclude that the ability to maintain smooth pursuit in the absence of visual information can extend to complex hand-target mappings, but the provision of haptic feedback is critical for the maintenance of accurate eye-tracking performance.

Eye Tracking of Occluded Self-Moved Targets: Role of Haptic Feedback and Hand-Target Dynamics

PubMed Central

Mathew, James

2017-01-01

Abstract Previous studies on smooth pursuit eye movements have shown that humans can continue to track the position of their hand, or a target controlled by the hand, after it is occluded, thereby demonstrating that arm motor commands contribute to the prediction of target motion driving pursuit eye movements. Here, we investigated this predictive mechanism by manipulating both the complexity of the hand-target mapping and the provision of haptic feedback. Two hand-target mappings were used, either a rigid (simple) one in which hand and target motion matched perfectly or a nonrigid (complex) one in which the target behaved as a mass attached to the hand by means of a spring. Target animation was obtained by asking participants to oscillate a lightweight robotic device that provided (or not) haptic feedback consistent with the target dynamics. Results showed that as long as 7 s after target occlusion, smooth pursuit continued to be the main contributor to total eye displacement (∼60%). However, the accuracy of eye-tracking varied substantially across experimental conditions. In general, eye-tracking was less accurate under the nonrigid mapping, as reflected by higher positional and velocity errors. Interestingly, haptic feedback helped to reduce the detrimental effects of target occlusion when participants used the nonrigid mapping, but not when they used the rigid one. Overall, we conclude that the ability to maintain smooth pursuit in the absence of visual information can extend to complex hand-target mappings, but the provision of haptic feedback is critical for the maintenance of accurate eye-tracking performance. PMID:28680964

The Ottawa Panel guidelines on programmes involving therapeutic exercise for the management of hand osteoarthritis.

PubMed

Brosseau, Lucie; Thevenot, Odette; MacKiddie, Olivia; Taki, Jade; Wells, George A; Guitard, Paulette; Léonard, Guillaume; Paquet, Nicole; Aydin, Sibel Z; Toupin-April, Karine; Cavallo, Sabrina; Moe, Rikke Helene; Shaikh, Kamran; Gifford, Wendy; Loew, Laurianne; De Angelis, Gino; Shallwani, Shirin Mehdi; Aburub, Ala' S; Mizusaki Imoto, Aline; Rahman, Prinon; Álvarez Gallardo, Inmaculada C; Cosic, Milkana Borges; Østerås, Nina; Lue, Sabrina; Hamasaki, Tokiko; Gaudreault, Nathaly; Towheed, Tanveer E; Koppikar, Sahil; Kjeken, Ingvild; Mahendira, Dharini; Kenny, Glen P; Paterson, Gail; Westby, Marie; Laferrière, Lucie; Longchamp, Guy

2018-06-01

To identify programmes involving therapeutic exercise that are effective for the management of hand osteoarthritis and to provide stakeholders with updated, moderate to high-quality recommendations supporting exercises for hand osteoarthritis. A systematic search and adapted selection criteria included comparable trials with exercise programmes for managing hand osteoarthritis. Based on the evaluated evidence, a panel of experts reached consensus through a Delphi approach endorsing the recommendations. A hierarchical alphabetical grading system (A, B, C+, C, C-, D-, D, D+, E, F) was based on clinical importance (≥15%) and statistical significance ( P < 0.05). Ten moderate- to high-quality studies were included. Eight studies with programmes involving therapeutic exercise (e.g. range of motion (ROM) + isotonic + isometric + functional exercise) seemed to be effective. Forty-six positive grade recommendations (i.e. A, B, C+) were obtained during short-term (<12 weeks) trials for pain, stiffness, physical function, grip strength, pinch strength, range of motion, global assessment, pressure pain threshold, fatigue and abductor pollicis longus moment and during long-term (>12 weeks) trials for physical function and pinch strength. Despite that many programmes involving exercise with positive recommendations for clinical outcomes are available to healthcare professionals and hand osteoarthritis patients that aid in the management of hand osteoarthritis, there is a need for further research to isolate the specific effect of exercise components.

Effect of power-assisted hand-rim wheelchair propulsion on shoulder load in experienced wheelchair users: A pilot study with an instrumented wheelchair.

PubMed

Kloosterman, Marieke G M; Buurke, Jaap H; de Vries, Wiebe; Van der Woude, Lucas H V; Rietman, Johan S

2015-10-01

This study aims to compare hand-rim and power-assisted hand-rim propulsion on potential risk factors for shoulder overuse injuries: intensity and repetition of shoulder loading and force generation in the extremes of shoulder motion. Eleven experienced hand-rim wheelchair users propelled an instrumented wheelchair on a treadmill while upper-extremity kinematic, kinetic and surface electromyographical data was collected during propulsion with and without power-assist. As a result during power-assisted propulsion the peak resultant force exerted at the hand-rim decreased and was performed with significantly less abduction and internal rotation at the shoulder. At shoulder level the anterior directed force and internal rotation and flexion moments decreased significantly. In addition, posterior and the minimal inferior directed forces and the external rotation moment significantly increased. The stroke angle decreased significantly, as did maximum shoulder flexion, extension, abduction and internal rotation. Stroke-frequency significantly increased. Muscle activation in the anterior deltoid and pectoralis major also decreased significantly. In conclusion, compared to hand-rim propulsion power-assisted propulsion seems effective in reducing potential risk factors of overuse injuries with the highest gain on decreased range of motion of the shoulder joint, lower peak propulsion force on the rim and reduced muscle activity. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Dynamic Propagation Channel Characterization and Modeling for Human Body Communication

PubMed Central

Nie, Zedong; Ma, Jingjing; Li, Zhicheng; Chen, Hong; Wang, Lei

2012-01-01

This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC). In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000) were acquired from five volunteers. Various path gains caused by different locations and movements were quantified and the statistical distributions were estimated. In general, for a given reference threshold è = −10 dB, the maximum average level crossing rate of the HBC was approximately 1.99 Hz, the maximum average fade time was 59.4 ms, and the percentage of bad channel duration time was less than 4.16%. The HBC exhibited a fade depth of −4 dB at 90% complementary cumulative probability. The statistical parameters were observed to be centered for each propagation channel. Subsequently a Fritchman model was implemented to estimate the burst characteristics of the on-body fading. It was concluded that the HBC is motion-insensitive, which is sufficient for reliable communication link during motions, and therefore it has great potential for body sensor/area networks. PMID:23250278

Dynamic propagation channel characterization and modeling for human body communication.

PubMed

Nie, Zedong; Ma, Jingjing; Li, Zhicheng; Chen, Hong; Wang, Lei

2012-12-18

This paper presents the first characterization and modeling of dynamic propagation channels for human body communication (HBC). In-situ experiments were performed using customized transceivers in an anechoic chamber. Three HBC propagation channels, i.e., from right leg to left leg, from right hand to left hand and from right hand to left leg, were investigated under thirty-three motion scenarios. Snapshots of data (2,800,000) were acquired from five volunteers. Various path gains caused by different locations and movements were quantified and the statistical distributions were estimated. In general, for a given reference threshold è = -10 dB, the maximum average level crossing rate of the HBC was approximately 1.99 Hz, the maximum average fade time was 59.4 ms, and the percentage of bad channel duration time was less than 4.16%. The HBC exhibited a fade depth of -4 dB at 90% complementary cumulative probability. The statistical parameters were observed to be centered for each propagation channel. Subsequently a Fritchman model was implemented to estimate the burst characteristics of the on-body fading. It was concluded that the HBC is motion-insensitive, which is sufficient for reliable communication link during motions, and therefore it has great potential for body sensor/area networks.

Rural ITS user needs

DOT National Transportation Integrated Search

1999-07-01

The Truck Characteristics Study seeks to develop a better understanding of the physical characteristics of the national truck fleet. With automatic vehicle classifiers (AVC) and weigh-in-motion devices (WIM), only axle spacing and weight information ...

Volumetric analysis of hand, reciprocating and rotary instrumentation techniques in primary molars using spiral computed tomography: An in vitro comparative study.

PubMed

Jeevanandan, Ganesh; Thomas, Eapen

2018-01-01

This present study was conducted to analyze the volumetric change in the root canal space and instrumentation time between hand files, hand files in reciprocating motion, and three rotary files in primary molars. One hundred primary mandibular molars were randomly allotted to one of the five groups. Instrumentation was done using Group I; nickel-titanium (Ni-Ti) hand file, Group II; Ni-Ti hand files in reciprocating motion, Group III; Race rotary files, Group IV; prodesign pediatric rotary files, and Group V; ProTaper rotary files. The mean volumetric changes were assessed using pre- and post-operative spiral computed tomography scans. Instrumentation time was recorded. Statistical analysis to access intergroup comparison for mean canal volume and instrumentation time was done using Bonferroni-adjusted Mann-Whitney test and Mann-Whitney test, respectively. Intergroup comparison of mean canal volume showed statistically significant difference between Groups II versus IV, Groups III versus V, and Groups IV versus V. Intergroup comparison of mean instrumentation time showed statistically significant difference among all the groups except Groups IV versus V. Among the various instrumentation techniques available, rotary instrumentation is the considered to be the better instrumentation technique for canal preparation in primary teeth.

Improved reliability in skeletal age assessment using a pediatric hand MR scanner with a 0.3T permanent magnet.

PubMed

Terada, Yasuhiko; Kono, Saki; Uchiumi, Tomomi; Kose, Katsumi; Miyagi, Ryo; Yamabe, Eiko; Fujinaga, Yasunari; Yoshioka, Hiroshi

2014-01-01

The purpose of this study was to improve the reliability and validity of skeletal age assessment using an open and compact pediatric hand magnetic resonance (MR) imaging scanner. We used such a scanner with 0.3-tesla permanent magnet to image the left hands of 88 healthy children (aged 3.4 to 15.7 years, mean 8.8 years), and 3 raters (2 orthopedic specialists and a radiologist) assessed skeletal age using those images. We measured the strength of agreement in ratings by values of weighted Cohen's κ and the proportion of cases excluded from rating because of motion artifact and inappropriate positioning. We compared the current results with those of a previous study in which 93 healthy children (aged 4.1 to 16.4 years, mean 9.7 years) were examined with an adult hand scanner. The κ values between raters exceeded 0.80, which indicates almost perfect agreement, and most were higher than those of the previous study. The proportion of cases excluded from rating because of motion artifact or inappropriate positioning was also reduced. The results indicate that use of the compact pediatric hand scanner improved the reliability and validity of skeletal age assessments.

Ergonomics: The Study of Work

DTIC Science & Technology

2000-01-01

Disease Name thumbs pain at the base of the thumbs twisting and gripping butchers , house- keepers, packers, seam- stresses, cutters fingers De...Quervain’s disease difficulty moving finger; snapping and jerking movements repeatedly using the index fingers meatpackers, poultry workers, carpenters...line workers rotator cuff tendinitis hands, wrists pain, swelling repetitive or forceful hand and wrist motions core making, poultry process- ing

49 CFR 231.13 - Passenger-train cars with open-end platforms.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Passenger-train cars with open-end platforms. 231... Passenger-train cars with open-end platforms. (a) Hand brakes—(1) Number. Each passenger-train car shall be...) Location. Each hand brake shall be so located that it can be safely operated while car is in motion. (b...

49 CFR 231.13 - Passenger-train cars with open-end platforms.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Passenger-train cars with open-end platforms. 231... Passenger-train cars with open-end platforms. (a) Hand brakes—(1) Number. Each passenger-train car shall be...) Location. Each hand brake shall be so located that it can be safely operated while car is in motion. (b...

49 CFR 231.13 - Passenger-train cars with open-end platforms.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Passenger-train cars with open-end platforms. 231... Passenger-train cars with open-end platforms. (a) Hand brakes—(1) Number. Each passenger-train car shall be...) Location. Each hand brake shall be so located that it can be safely operated while car is in motion. (b...

49 CFR 231.13 - Passenger-train cars with open-end platforms.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Passenger-train cars with open-end platforms. 231... Passenger-train cars with open-end platforms. (a) Hand brakes—(1) Number. Each passenger-train car shall be...) Location. Each hand brake shall be so located that it can be safely operated while car is in motion. (b...

49 CFR 231.13 - Passenger-train cars with open-end platforms.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Passenger-train cars with open-end platforms. 231... Passenger-train cars with open-end platforms. (a) Hand brakes—(1) Number. Each passenger-train car shall be...) Location. Each hand brake shall be so located that it can be safely operated while car is in motion. (b...

Motion-mode energy method for vehicle dynamics analysis and control

NASA Astrophysics Data System (ADS)

Zhang, Nong; Wang, Lifu; Du, Haiping

2014-01-01

Vehicle motion and vibration control is a fundamental motivation for the development of advanced vehicle suspension systems. In a vehicle-fixed coordinate system, the relative motions of the vehicle between body and wheel can be classified into several dynamic stages based on energy intensity, and can be decomposed into sets of uncoupled motion-modes according to modal parameters. Vehicle motions are coupled, but motion-modes are orthogonal. By detecting and controlling the predominating vehicle motion-mode, the system cost and energy consumption of active suspensions could be reduced. A motion-mode energy method (MEM) is presented in this paper to quantify the energy contribution of each motion-mode to vehicle dynamics in real time. The control of motion-modes is prioritised according to the level of motion-mode energy. Simulation results on a 10 degree-of-freedom nonlinear full-car model with the magic-formula tyre model illustrate the effectiveness of the proposed MEM. The contribution of each motion-mode to the vehicle's dynamic behaviour is analysed under different excitation inputs from road irregularities, directional manoeuvres and braking. With the identified dominant motion-mode, novel cost-effective suspension systems, such as active reconfigurable hydraulically interconnected suspension, can possibly be used to control full-car motions with reduced energy consumption. Finally, discussion, conclusions and suggestions for future work are provided.

Automatic Denoising of Functional MRI Data: Combining Independent Component Analysis and Hierarchical Fusion of Classifiers

PubMed Central

Salimi-Khorshidi, Gholamreza; Douaud, Gwenaëlle; Beckmann, Christian F; Glasser, Matthew F; Griffanti, Ludovica; Smith, Stephen M

2014-01-01

Many sources of fluctuation contribute to the fMRI signal, and this makes identifying the effects that are truly related to the underlying neuronal activity difficult. Independent component analysis (ICA) - one of the most widely used techniques for the exploratory analysis of fMRI data - has shown to be a powerful technique in identifying various sources of neuronally-related and artefactual fluctuation in fMRI data (both with the application of external stimuli and with the subject “at rest”). ICA decomposes fMRI data into patterns of activity (a set of spatial maps and their corresponding time series) that are statistically independent and add linearly to explain voxel-wise time series. Given the set of ICA components, if the components representing “signal” (brain activity) can be distinguished form the “noise” components (effects of motion, non-neuronal physiology, scanner artefacts and other nuisance sources), the latter can then be removed from the data, providing an effective cleanup of structured noise. Manual classification of components is labour intensive and requires expertise; hence, a fully automatic noise detection algorithm that can reliably detect various types of noise sources (in both task and resting fMRI) is desirable. In this paper, we introduce FIX (“FMRIB’s ICA-based X-noiseifier”), which provides an automatic solution for denoising fMRI data via accurate classification of ICA components. For each ICA component FIX generates a large number of distinct spatial and temporal features, each describing a different aspect of the data (e.g., what proportion of temporal fluctuations are at high frequencies). The set of features is then fed into a multi-level classifier (built around several different Classifiers). Once trained through the hand-classification of a sufficient number of training datasets, the classifier can then automatically classify new datasets. The noise components can then be subtracted from (or regressed out of) the original data, to provide automated cleanup. On conventional resting-state fMRI (rfMRI) single-run datasets, FIX achieved about 95% overall accuracy. On high-quality rfMRI data from the Human Connectome Project, FIX achieves over 99% classification accuracy, and as a result is being used in the default rfMRI processing pipeline for generating HCP connectomes. FIX is publicly available as a plugin for FSL. PMID:24389422

[Results of treatment for high-pressure injection hand injuries].

PubMed

Zyluk, A; Walaszek, I

2000-01-01

High-pressure injection injuries of the hand have a reputation for being dangerous for individual fingers and even for whole hand. Usually appearing innocuous at presentation because of small puncture entry wound, these injuries result in severe damage of most internal structures in finger and hand due to extensive penetration of injected substance. This paper reviews the outcome of the treatment of such injuries in 10 patients: 9 sustained injection of toxic paint, and one lead shot. All the patients were operated on: eight a few hours after injury and two with 3 days delay. The surgical technique included wide exposure from site of injection up to the farthest place in which foreign substance was seen. Thorough debridment of injected material and contaminated tissue was performed with careful preservation of neurovascular structures and tendons. Wounds were not closed, but managed by open technique. In all patients wounds healed well: in 3 by secondary intention, in 6 by delayed closure and 2 were covered by skin grafts. No amputation was performed. Final results were assessed form 1.5 to 3.5 years after initial injury (mean at 2.5 years). Two patients complained of moderate pain related to the weather, five of cold intolerance and two of impaired sensation on fingertips. Active range of motion of affected fingers was in whole group from 90% to 104% (mean 97%) of the range of motion of unaffected fingers from the other side. Range of motion of the wrist (2 patients) was 76% and 117% of range of motion of the other side. Pinch grip strength was from 81% to 116% (mean 99%), and global grip strength from 77% to 119% (mean 97%) of the other side. All patients went back to their previous jobs and periods of sick leave were from 2 weeks to 6 months (mean 3 mo). Excellent results achieved in this study--full functional recovery in 9 of 10 patients confirm the effectiveness of aggressive treatment by open wound technique of such injuries.

Combining multiple features for color texture classification

NASA Astrophysics Data System (ADS)

Cusano, Claudio; Napoletano, Paolo; Schettini, Raimondo

2016-11-01

The analysis of color and texture has a long history in image analysis and computer vision. These two properties are often considered as independent, even though they are strongly related in images of natural objects and materials. Correlation between color and texture information is especially relevant in the case of variable illumination, a condition that has a crucial impact on the effectiveness of most visual descriptors. We propose an ensemble of hand-crafted image descriptors designed to capture different aspects of color textures. We show that the use of these descriptors in a multiple classifiers framework makes it possible to achieve a very high classification accuracy in classifying texture images acquired under different lighting conditions. A powerful alternative to hand-crafted descriptors is represented by features obtained with deep learning methods. We also show how the proposed combining strategy hand-crafted and convolutional neural networks features can be used together to further improve the classification accuracy. Experimental results on a food database (raw food texture) demonstrate the effectiveness of the proposed strategy.

A comparison of four office chairs using biomechanical measures.

PubMed

Bush, Tamara Reid; Hubbard, Robert P

2008-08-01

The authors sought to use biomechanical measures, including motion and pressure, to compare four office chairs. The fit of a person to a chair is related to the geometric and kinematic compatibility between the two. This geometric compatibility influences the motions that are allowed or prohibited and the support pressures at the body-chair interface. Thus, during evaluation, it is necessary to treat the chair and user as a system. Four dynamic test conditions were evaluated with 14 participants of varying anthropometries. Test conditions were selected to compare the ability to accommodate primary and secondary motions (recline and spinal articulation) of seated occupants. The ability of a chair to allow recline, yet maintain head and hand positions, was compared across chairs. Also, the ability of each chair to allow and support spinal articulation was evaluated. Motion data for the chair, head, thorax, pelvis, and extremities were collected along with chair back pressures. Upon completion of testing, subjective assessments were also conducted. Statistically significant differences were found between chairs relative to head and hand motions. Also, significant differences were noted for the chairs' ability to move with the body during spinal articulation and the ability to provide support. Subjective assessments also yielded differences. Biomechanical analyses using motions and pressures can be conducted on office chairs with significant differences detected in their performance. Biomechanical assessments can be used to compare and contrast office chairs in terms that are relatable to fatigue reduction as well as operator performance.

Generating Concise Rules for Human Motion Retrieval

NASA Astrophysics Data System (ADS)

Mukai, Tomohiko; Wakisaka, Ken-Ichi; Kuriyama, Shigeru

This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

Steering particles by breaking symmetries

NASA Astrophysics Data System (ADS)

Bet, Bram; Samin, Sela; Georgiev, Rumen; Burak Eral, Huseyin; van Roij, René

2018-06-01

We derive general equations of motions for highly-confined particles that perform quasi-two-dimensional motion in Hele-Shaw channels, which we solve analytically, aiming to derive design principles for self-steering particles. Based on symmetry properties of a particle, its equations of motion can be simplified, where we retrieve an earlier-known equation of motion for the orientation of dimer particles consisting of disks (Uspal et al 2013 Nat. Commun. 4), but now in full generality. Subsequently, these solutions are compared with particle trajectories that are obtained numerically. For mirror-symmetric particles, excellent agreement between the analytical and numerical solutions is found. For particles lacking mirror symmetry, the analytic solutions provide means to classify the motion based on particle geometry, while we find that taking the side-wall interactions into account is important to accurately describe the trajectories.

The development of a test methodology for the evaluation of EVA gloves

NASA Technical Reports Server (NTRS)

O'Hara, John M.; Cleland, John; Winfield, Dan

1988-01-01

This paper describes the development of a standardized set of tests designed to assess EVA-gloved hand capabilities in six measurement domains: range of motion, strength, tactile perception, dexterity, fatigue, and comfort. Based upon an assessment of general human-hand functioning and EVA task requirements, several tests within each measurement domain were developed to provide a comprehensive evaluation. All tests were designed to be conducted in a glove box with the bare hand as a baseline and the EVA glove at operating pressure.

A Kinetic Study Using Evaporation of Different Types of Hand-Rub Sanitizers

ERIC Educational Resources Information Center

Pinhas, Allan R.

2010-01-01

Alcohol-based hand-rub sanitizers are the types of products that hospital professionals use very often. These sanitizers can be classified into two major groups: those that contain a large quantity of thickener, and thus are a gel, and those that contain a small quantity of thickener, and thus remain a liquid. In an effort to create a laboratory…

Flight simulator platform motion and air transport pilot training

NASA Technical Reports Server (NTRS)

Lee, Alfred T.; Bussolari, Steven R.

1987-01-01

The effect of a flight simulator platform motion on the performance and training of a pilot was evaluated using subjective ratings and objective performance data obtained on experienced B-727 pilots and pilots with no prior heavy aircraft flying experience flying B-727-200 aircraft simulator used by the FAA in the upgrade and transition training for air carrier operations. The results on experienced pilots did not reveal any reliable effects of wide variations in platform motion design. On the other hand, motion variations significantly affected the behavior of pilots without heavy-aircraft experience. The effect was limited to pitch attitude control inputs during the early phase of landing training.

Study of modeling and evaluation of remote manipulation tasks with force feedback

NASA Technical Reports Server (NTRS)

Hill, J. W.

1979-01-01

The use of time and motion study methods to evaluate force feedback in remote manipulation tasks are described. Several systems of time measurement derived for industrial workers were studied and adapted for manipulator use. A task board incorporating a set of basic motions was designed and built. Results obtained from two subjects in three manipulation situations for each are reported: a force-reflective manipulator, a unilateral manipulator, and the unaided human hand. The results indicate that: (1) a time-and-motion study techniques are applicable to manipulation; and that (2) force feedback facilitates some motions (notably fitting), but not others (such as positioning).

[Non vascularized toe phalangeal transfers for symbrachydactyly. Active range of motion without joint reconstruction].

PubMed

Leca, J-B; Auquit Auckbur, I; Bachy, B; Milliez, P-Y

2008-12-01

Symbrachydactyly is a rare congenital malformation of the hand and its treatment is controversial. Non vascularized toe phalangeal transfers have been used for management of short digits for three children. Six phalanges have been harvested complete with their periosteum. No joint reconstruction has been performed and all children have undergone surgery at a young age. Four of six digits involved have an active range of motion (range 30 to 105 degrees ). All authors who have reported active range of motion of toe phalangeal transfers have performed joint reconstruction. Here, we report obtaining active range of motion of phalangeal transfers without necessity of joint reconstruction.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters.

PubMed

Rempel, David; Camilleri, Matt J; Lee, David L

2015-10-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input.

The Kinematics of Trunk and Upper Extremities in One-Handed and Two-Handed Backhand Stroke

PubMed Central

Stępień, Adam; Bober, Tadeusz; Zawadzki, Jerzy

2011-01-01

The aim of this study was to present kinematics of trunk and upper extremities in tennis players who perform one-handed and two-handed backhand strokes. The study aimed to address the question of whether one of those techniques has some important advantage over the other. If so, what makes it superior? The study included 10 tennis coaches with average coaching experience of 9 years. The coaches were asked to hit 15 one-handed and two-handed backhands. The tests were carried out in a laboratory. A sponge ball was used in order to protect the measurement equipment. Video motion analysis was carried out using BTS SMART system; images were recorded with 6 cameras with a rate of 120 frames per second. The analysis of both backhand strokes focused on the second phase of the stroke (acceleration). The use of an eight-element model of human body for description of upper body motion in both techniques revealed kinematic differences in how both backhands are performed. The two-handed backhand was performed in closed kinetic chain with 8 degrees of freedom, whereas the one-handed backhand involved an open kinetic chain with 7 degrees of freedom. Higher rigidity of upper extremities which are connected with trunk in the two-handed backhand, contributes to an elevated trunk effect in this stroke. This is confirmed by higher component velocities for racket handle, which result from trunk rotation in the two-handed backhand and a negative separation angle in the two-handed backhand at the moment of contact of the racket with the ball. The study does not provide a clear-cut answer to the question of advantages of one technique over the other; however, it reveals dissimilar patterns of driving the racket in both techniques, which suggests the need for extending the analysis of techniques of both backhands with additional kinematics of tennis racket in consideration of measurements of ball velocities. PMID:23486650

Understanding and Visualizing Multitasking and Task Switching Activities: A Time Motion Study to Capture Nursing Workflow

PubMed Central

Yen, Po-Yin; Kelley, Marjorie; Lopetegui, Marcelo; Rosado, Amber L.; Migliore, Elaina M.; Chipps, Esther M.; Buck, Jacalyn

2016-01-01

A fundamental understanding of multitasking within nursing workflow is important in today’s dynamic and complex healthcare environment. We conducted a time motion study to understand nursing workflow, specifically multitasking and task switching activities. We used TimeCaT, a comprehensive electronic time capture tool, to capture observational data. We established inter-observer reliability prior to data collection. We completed 56 hours of observation of 10 registered nurses. We found, on average, nurses had 124 communications and 208 hands-on tasks per 4-hour block of time. They multitasked (having communication and hands-on tasks simultaneously) 131 times, representing 39.48% of all times; the total multitasking duration ranges from 14.6 minutes to 109 minutes, 44.98 minutes (18.63%) on average. We also reviewed workflow visualization to uncover the multitasking events. Our study design and methods provide a practical and reliable approach to conducting and analyzing time motion studies from both quantitative and qualitative perspectives. PMID:28269924

Computation of fluid and particle motion from a time-sequenced image pair: a global outlier identification approach.

PubMed

Ray, Nilanjan

2011-10-01

Fluid motion estimation from time-sequenced images is a significant image analysis task. Its application is widespread in experimental fluidics research and many related areas like biomedical engineering and atmospheric sciences. In this paper, we present a novel flow computation framework to estimate the flow velocity vectors from two consecutive image frames. In an energy minimization-based flow computation, we propose a novel data fidelity term, which: 1) can accommodate various measures, such as cross-correlation or sum of absolute or squared differences of pixel intensities between image patches; 2) has a global mechanism to control the adverse effect of outliers arising out of motion discontinuities, proximity of image borders; and 3) can go hand-in-hand with various spatial smoothness terms. Further, the proposed data term and related regularization schemes are both applicable to dense and sparse flow vector estimations. We validate these claims by numerical experiments on benchmark flow data sets. © 2011 IEEE

Understanding and Visualizing Multitasking and Task Switching Activities: A Time Motion Study to Capture Nursing Workflow.

PubMed

Yen, Po-Yin; Kelley, Marjorie; Lopetegui, Marcelo; Rosado, Amber L; Migliore, Elaina M; Chipps, Esther M; Buck, Jacalyn

2016-01-01

A fundamental understanding of multitasking within nursing workflow is important in today's dynamic and complex healthcare environment. We conducted a time motion study to understand nursing workflow, specifically multitasking and task switching activities. We used TimeCaT, a comprehensive electronic time capture tool, to capture observational data. We established inter-observer reliability prior to data collection. We completed 56 hours of observation of 10 registered nurses. We found, on average, nurses had 124 communications and 208 hands-on tasks per 4-hour block of time. They multitasked (having communication and hands-on tasks simultaneously) 131 times, representing 39.48% of all times; the total multitasking duration ranges from 14.6 minutes to 109 minutes, 44.98 minutes (18.63%) on average. We also reviewed workflow visualization to uncover the multitasking events. Our study design and methods provide a practical and reliable approach to conducting and analyzing time motion studies from both quantitative and qualitative perspectives.

Generating action descriptions from statistically integrated representations of human motions and sentences.

PubMed

Takano, Wataru; Kusajima, Ikuo; Nakamura, Yoshihiko

2016-08-01

It is desirable for robots to be able to linguistically understand human actions during human-robot interactions. Previous research has developed frameworks for encoding human full body motion into model parameters and for classifying motion into specific categories. For full understanding, the motion categories need to be connected to the natural language such that the robots can interpret human motions as linguistic expressions. This paper proposes a novel framework for integrating observation of human motion with that of natural language. This framework consists of two models; the first model statistically learns the relations between motions and their relevant words, and the second statistically learns sentence structures as word n-grams. Integration of these two models allows robots to generate sentences from human motions by searching for words relevant to the motion using the first model and then arranging these words in appropriate order using the second model. This allows making sentences that are the most likely to be generated from the motion. The proposed framework was tested on human full body motion measured by an optical motion capture system. In this, descriptive sentences were manually attached to the motions, and the validity of the system was demonstrated. Copyright © 2016 Elsevier Ltd. All rights reserved.

Force Model for Control of Tendon Driven Hands

NASA Technical Reports Server (NTRS)

Pena, Edward; Thompson, David E.

1997-01-01

Knowing the tendon forces generated for a given task such as grasping via a model, an artificial hand can be controlled. A two-dimensional force model for the index finger was developed. This system is assumed to be in static equilibrium, therefore, the equations of equilibrium were applied at each joint. Constraint equations describing the tendon branch connectivity were used. Gaussian elimination was used to solve for the unknowns of the Linear system. Results from initial work on estimating tendon forces in post-operative hands during active motion therapy were discussed. The results are important for understanding the effects of hand position on tendon tension, elastic effects on tendon tension, and overall functional anatomy of the hand.

[Hand eczema. The clinical classification of the roles of exogenous and endogenous factors in each type].

PubMed

Tamiya, Y

1994-08-01

Hand eczema is one of the most common dermatological disorders. Although it is a general term referring to eczematous dermatitis of the hands, it actually covers a wide range of diseases. The classification of hand eczema is controversial even now, as definitions of individual diseases have not yet been established. It is well-known that exogenous factors, such as chemicals or water, are associated with the occurrence of hand eczema. In this study, we focused on endogenous factors, especially personal or family history of atopy as a causative factor in hand eczema. According to exogenous and endogenous factors, we classified hand eczema into three types: atopic dermatitis, contact dermatitis and dysidrosis. This classification is useful because it makes the definition of each disease clear. Skin-humidity and sebum measurement are simple and rapid methods of determining personal atopy, skin condition and the effect of treatment on hand eczema patients.

Machine learning methods for classifying human physical activity from on-body accelerometers.

PubMed

Mannini, Andrea; Sabatini, Angelo Maria

2010-01-01

The use of on-body wearable sensors is widespread in several academic and industrial domains. Of great interest are their applications in ambulatory monitoring and pervasive computing systems; here, some quantitative analysis of human motion and its automatic classification are the main computational tasks to be pursued. In this paper, we discuss how human physical activity can be classified using on-body accelerometers, with a major emphasis devoted to the computational algorithms employed for this purpose. In particular, we motivate our current interest for classifiers based on Hidden Markov Models (HMMs). An example is illustrated and discussed by analysing a dataset of accelerometer time series.

Thermal bioaerosol cloud tracking with Bayesian classification

NASA Astrophysics Data System (ADS)

Smith, Christian W.; Dupuis, Julia R.; Schundler, Elizabeth C.; Marinelli, William J.

2017-05-01

The development of a wide area, bioaerosol early warning capability employing existing uncooled thermal imaging systems used for persistent perimeter surveillance is discussed. The capability exploits thermal imagers with other available data streams including meteorological data and employs a recursive Bayesian classifier to detect, track, and classify observed thermal objects with attributes consistent with a bioaerosol plume. Target detection is achieved based on similarity to a phenomenological model which predicts the scene-dependent thermal signature of bioaerosol plumes. Change detection in thermal sensor data is combined with local meteorological data to locate targets with the appropriate thermal characteristics. Target motion is tracked utilizing a Kalman filter and nearly constant velocity motion model for cloud state estimation. Track management is performed using a logic-based upkeep system, and data association is accomplished using a combinatorial optimization technique. Bioaerosol threat classification is determined using a recursive Bayesian classifier to quantify the threat probability of each tracked object. The classifier can accept additional inputs from visible imagers, acoustic sensors, and point biological sensors to improve classification confidence. This capability was successfully demonstrated for bioaerosol simulant releases during field testing at Dugway Proving Grounds. Standoff detection at a range of 700m was achieved for as little as 500g of anthrax simulant. Developmental test results will be reviewed for a range of simulant releases, and future development and transition plans for the bioaerosol early warning platform will be discussed.

Reliability enumeration model for the gear in a multi-functional machine

NASA Astrophysics Data System (ADS)

Nasution, M. K. M.; Ambarita, H.

2018-02-01

The angle and direction of motion play an important role in the ability of a multifunctional machine to be able to perform the task to be charged. The movement can be a rotational action that appears to perform a round, by which the rotation can be done by connecting the generator by hand through the help of a hinge formed from two rounded surfaces. The rotation of the entire arm can be carried out by the interconnection between two surfaces having a jagged ring. This link will change according to the angle of motion, and any yeast of the serration will have a share in the success of this process, therefore a robust hand measurement model is established based on canonical provisions.

A novel remote center of motion mechanism for the force-reflective master robot of haptic tele-surgery systems.

PubMed

Hadavand, Mostafa; Mirbagheri, Alireza; Behzadipour, Saeed; Farahmand, Farzam

2014-06-01

An effective master robot for haptic tele-surgery applications needs to provide a solution for the inversed movements of the surgical tool, in addition to sufficient workspace and manipulability, with minimal moving inertia. A novel 4 + 1-DOF mechanism was proposed, based on a triple parallelogram linkage, which provided a Remote Center of Motion (RCM) at the back of the user's hand. The kinematics of the robot was analyzed and a prototype was fabricated and evaluated by experimental tests. With a RCM at the back of the user's hand the actuators far from the end effector, the robot could produce the sensation of hand-inside surgery with minimal moving inertia. The target workspace was achieved with an acceptable manipulability. The trajectory tracking experiments revealed small errors, due to backlash at the joints. The proposed mechanism meets the basic requirements of an effective master robot for haptic tele-surgery applications. Copyright © 2013 John Wiley & Sons, Ltd.

Motion deficit in nodal interphalangeal joint osteoarthritis by digital goniometer in housewives.

PubMed

Ventura-Ríos, L; Hayes-Salinas, M; Ferrusquia-Toriz, D; Cariño-Escobar, R I; Cruz-Arenas, E; Gutiérrez-Martínez, J; González-Ramírez, L; Hernández-Díaz, C

2018-06-01

Range of motion (ROM) measured objectively in nodal hand osteoarthritis (NHOA) is missing. Evaluation of collateral ligaments by ultrasound (US) is unknown in NHOA also. To compare ROM in interphalangeal joints in housewives with nodal OA, with a control group by a digital system using angle to voltage (Multielgon). The second objective was to assess correlation between collateral radial and ulnar ligaments thickness and ROM. For this cross-sectional observational study, we assessed 60 hands with symptomatic NHOA and 30 hands of healthy housewives matched for age. We obtained clinical and demographic characteristics (a complete standardized physical examination of hand joints, DASH questionnaire, pain surveys, gross grasp hand goniometer, and ROM measurements by Multielgon. Presence of synovitis, power Doppler signal, osteophytes, and collateral ligaments thickness was evaluated by US. We used descriptive statistics, Spearman correlation, X 2 test, t test and odds ratio. Significant less gross grasp and ROM in the right hand were observed in NHOA (p = 0.01 for both). Presence of OA, painful joints, disease duration, and score DASH were significant correlated with reduced ROM (OR 4.12, 4.12, 1.04 and 1.09, respectively). Reduced ROM was statistical significant in thumb MCP and IP joints, second and third DIP in dominant hand. There was no association between collateral radial and ulnar ligaments and reduced ROM. Synovitis and osteophytes were more prevalent in OA group. Multielgon demonstrated the pattern of reduced ROM in nodal OA of housewives particularly in MCP and IP thumb joints, second and third distal interphalangeal joints.

PLAY HANDS PROTECTIVE GLOVES: TECHNICAL NOTE ON DESIGN AND CONCEPT.

PubMed

Houston-Hicks, Michele; Lura, Derek J; Highsmith, M Jason

2016-09-01

Cerebral Palsy (CP) is the leading cause of childhood motor disability, with a global incidence of 1.6 to 2.5/1,000 live births. Approximately 23% of children with CP are dependent upon assistive technologies. Some children with developmental disabilities have self-injurious behaviors such as finger biting but also have therapeutic needs. The purpose of this technical note is to describe design considerations for a protective glove and finger covering that maintains finger dexterity for children who exhibit finger and hand chewing (dermatophagia) and require therapeutic range of motion and may benefit from sensory stimulation resulting from constant contact between glove and skin. Protecting Little and Adolescent Youth (PLAY) Hands are protective gloves for children with developmental disorders such as CP who injure themselves by biting their hands due to pain or sensory issues. PLAY Hands will be cosmetically appealing gloves that provide therapeutic warmth, tactile sensory feedback, range of motion for donning/ doffing, and protection to maximize function and quality of life for families of children with developmental disorders. The technology is either a per-finger protective orthosis or an entire glove solution designed from durable 3D-printed biodegradable/bioabsorbable materials such as thermoplastics. PLAY Hands represent a series of protective hand wear interventions in the areas of self-mutilating behavior, kinematics, and sensation. They will be made available in a range of protective iterations from single- or multi-digit finger orthoses to a basic glove design to a more structurally robust and protective iteration. To improve the quality of life for patients and caregivers, they are conceptualized to be cosmetically appealing, protective, and therapeutic.

Development of excavator training simulator using leap motion controller

NASA Astrophysics Data System (ADS)

Fahmi, F.; Nainggolan, F.; Andayani, U.; Siregar, B.

2018-03-01

Excavator is a heavy machinery that is used for many industries purposes. Controlling the excavator is not easy. Its operator has to be trained well in many skills to make sure it is safe, effective, and efficient while using the excavator. In this research, we proposed a virtual reality excavator simulator supported by a device called Leap Motion Controller that supports finger and hand motions as an input. This prototype will be developed than in the virtual reality environment to give a more real sensing to the user.

The Posture of Putting One's Palms Together Modulates Visual Motion Event Perception.

PubMed

Saito, Godai; Gyoba, Jiro

2018-02-01

We investigated the effect of an observer's hand postures on visual motion perception using the stream/bounce display. When two identical visual objects move across collinear horizontal trajectories toward each other in a two-dimensional display, observers perceive them as either streaming or bouncing. In our previous study, we found that when observers put their palms together just below the coincidence point of the two objects, the percentage of bouncing responses increased, mainly depending on the proprioceptive information from their own hands. However, it remains unclear if the tactile or haptic (force) information produced by the postures mostly influences the stream/bounce perception. We solved this problem by changing the tactile and haptic information on the palms of the hands. Experiment 1 showed that the promotion of bouncing perception was observed only when the posture of directly putting one's palms together was used, while there was no effect when a brick was sandwiched between the participant's palms. Experiment 2 demonstrated that the strength of force used when putting the palms together had no effect on increasing bounce perception. Our findings indicate that the hands-induced bounce effect derives from the tactile information produced by the direct contact between both palms.

Development of hand exoskeleton for rehabilitation of post-stroke patient

NASA Astrophysics Data System (ADS)

Zaid, Amran Mohd; Chean, Tee Chu; Sukor, Jumadi Abdul; Hanafi, Dirman

2017-10-01

Degenerative muscle diseases characterized by loss of strength in human hand significantly affect the physical of affected individuals. A soft assistive exoskeleton glove is designed to help post-stroke patient with their rehabilitation process. The glove uses soft bending actuator which has a rubber like tender characteristic. Due to its rubber like characteristic, flexion of finger can be achieved easily through pneumatic air without considering other hand motions. The application involves a post-stroke patient to wear the soft exoskeleton glove on his paralyzed hand and control the actuation of the glove by using pneumatic air source. The fabrication of the soft bending actuator involves silicone rubber Mold Star® 15 SLOW which falls within the soft category of shore A hardness scale. The soft bending actuator is controlled by Arduino Mega 2560 as main controller board and relay module is used to trigger the 3/2-way single solenoid valve by switching on the 24VDC power supply. The actuation of the soft bending actuator can be manipulated by setting delay ON and OFF for the relay switching. Thus, the repetition of the bending motion can be customized to fulfil the rehabilitation needs of the patient.

Real-time marker-free motion capture system using blob feature analysis

NASA Astrophysics Data System (ADS)

Park, Chang-Joon; Kim, Sung-Eun; Kim, Hong-Seok; Lee, In-Ho

2005-02-01

This paper presents a real-time marker-free motion capture system which can reconstruct 3-dimensional human motions. The virtual character of the proposed system mimics the motion of an actor in real-time. The proposed system captures human motions by using three synchronized CCD cameras and detects the root and end-effectors of an actor such as a head, hands, and feet by exploiting the blob feature analysis. And then, the 3-dimensional positions of end-effectors are restored and tracked by using Kalman filter. At last, the positions of the intermediate joint are reconstructed by using anatomically constrained inverse kinematics algorithm. The proposed system was implemented under general lighting conditions and we confirmed that the proposed system could reconstruct motions of a lot of people wearing various clothes in real-time stably.

On the local standard of rest

NASA Technical Reports Server (NTRS)

Yuan, C.

1982-01-01

Under the influence of a spiral gravitational field, there should be differences among the mean motions of different types of objects with different dispersion velocities in a sipral galaxy. The old stars with high dispersion velocity should have essentially no mean motion normal to the galactic rotation. On the other hand, young objects and interstellar gas may be moving relative to the old stars at a velocity of a few kilometer per second in both the radial (galacto-centric), and circular directions, depending on the spiral model adopted. Such a velocity is usually referred as the systematic motion or the streaming motion. The conventionally adopted local standard of rest is indeed co-moving with the young objects of the solar vicinity. Therefore, it has a net systematic motion with respect to the circular motion of an equilibrium galactic model, defined by the old stars.

Haptic fMRI: using classification to quantify task-correlated noise during goal-directed reaching motions.

PubMed

Menon, Samir; Quigley, Paul; Yu, Michelle; Khatib, Oussama

2014-01-01

Neuroimaging artifacts in haptic functional magnetic resonance imaging (Haptic fMRI) experiments have the potential to induce spurious fMRI activation where there is none, or to make neural activation measurements appear correlated across brain regions when they are actually not. Here, we demonstrate that performing three-dimensional goal-directed reaching motions while operating Haptic fMRI Interface (HFI) does not create confounding motion artifacts. To test for artifacts, we simultaneously scanned a subject's brain with a customized soft phantom placed a few centimeters away from the subject's left motor cortex. The phantom captured task-related motion and haptic noise, but did not contain associated neural activation measurements. We quantified the task-related information present in fMRI measurements taken from the brain and the phantom by using a linear max-margin classifier to predict whether raw time series data could differentiate between motion planning or reaching. fMRI measurements in the phantom were uninformative (2σ, 45-73%; chance=50%), while those in primary motor, visual, and somatosensory cortex accurately classified task-conditions (2σ, 90-96%). We also localized artifacts due to the haptic interface alone by scanning a stand-alone fBIRN phantom, while an operator performed haptic tasks outside the scanner's bore with the interface at the same location. The stand-alone phantom had lower temporal noise and had similar mean classification but a tighter distribution (bootstrap Gaussian fit) than the brain phantom. Our results suggest that any fMRI measurement artifacts for Haptic fMRI reaching experiments are dominated by actual neural responses.

Comparison of sEMG-Based Feature Extraction and Motion Classification Methods for Upper-Limb Movement

PubMed Central

Guo, Shuxiang; Pang, Muye; Gao, Baofeng; Hirata, Hideyuki; Ishihara, Hidenori

2015-01-01

The surface electromyography (sEMG) technique is proposed for muscle activation detection and intuitive control of prostheses or robot arms. Motion recognition is widely used to map sEMG signals to the target motions. One of the main factors preventing the implementation of this kind of method for real-time applications is the unsatisfactory motion recognition rate and time consumption. The purpose of this paper is to compare eight combinations of four feature extraction methods (Root Mean Square (RMS), Detrended Fluctuation Analysis (DFA), Weight Peaks (WP), and Muscular Model (MM)) and two classifiers (Neural Networks (NN) and Support Vector Machine (SVM)), for the task of mapping sEMG signals to eight upper-limb motions, to find out the relation between these methods and propose a proper combination to solve this issue. Seven subjects participated in the experiment and six muscles of the upper-limb were selected to record sEMG signals. The experimental results showed that NN classifier obtained the highest recognition accuracy rate (88.7%) during the training process while SVM performed better in real-time experiments (85.9%). For time consumption, SVM took less time than NN during the training process but needed more time for real-time computation. Among the four feature extraction methods, WP had the highest recognition rate for the training process (97.7%) while MM performed the best during real-time tests (94.3%). The combination of MM and NN is recommended for strict real-time applications while a combination of MM and SVM will be more suitable when time consumption is not a key requirement. PMID:25894941

Energy flow analysis during the tennis serve: comparison between injured and noninjured tennis players.

PubMed

Martin, Caroline; Bideau, Benoit; Bideau, Nicolas; Nicolas, Guillaume; Delamarche, Paul; Kulpa, Richard

2014-11-01

Energy flow has been hypothesized to be one of the most critical biomechanical concepts related to tennis performance and overuse injuries. However, the relationships among energy flow during the tennis serve, ball velocity, and overuse injuries have not been assessed. To investigate the relationships among the quality and magnitude of energy flow, the ball velocity, and the peaks of upper limb joint kinetics and to compare the energy flow during the serve between injured and noninjured tennis players. Case-control study; Level of evidence, 3. The serves of expert tennis players were recorded with an optoelectronic motion capture system. The forces and torques of the upper limb joints were calculated from the motion captures by use of inverse dynamics. The amount of mechanical energy generated, absorbed, and transferred was determined by use of a joint power analysis. Then the players were followed during 2 seasons to identify upper limb overuse injuries with a questionnaire. Finally, players were classified into 2 groups according to the questionnaire results: injured or noninjured. Ball velocity increased and upper limb joint kinetics decreased with the quality of energy flow from the trunk to the hand + racket segment. Injured players showed a lower quality of energy flow through the upper limb kinetic chain, a lower ball velocity, and higher rates of energy absorbed by the shoulder and elbow compared with noninjured players. The findings of this study imply that improper energy flow during the tennis serve can decrease ball velocity, increase upper limb joint kinetics, and thus increase overuse injuries of the upper limb joints. © 2014 The Author(s).

Design and control of five fingered under-actuated robotic hand

NASA Astrophysics Data System (ADS)

Sahoo, Biswojit; Parida, Pramod Kumar

2018-04-01

Now a day's research regarding humanoid robots and its application in different fields (industry, household, rehabilitation and exploratory) is going on entire the globe. Among which a challenging topic is to design a dexterous robotic hand which not only can perform as a hand of a robot but also can be used in re habilitation. The basic key concern is a dexterous robot hand which can be able to mimic the function of biological hand to perform different operations. This thesis work is regarding design and control of a under-actuated robotic hand consisting of four under actuated fingers (index finger, middle finger, little finger and ring finger ) , a thumb and a dexterous palm which can copy the motions and grasp type of human hand which having 21degrees of freedom instead of 25Degree Of Freedom.

Towards SSVEP-based, portable, responsive Brain-Computer Interface.

PubMed

Kaczmarek, Piotr; Salomon, Pawel

2015-08-01

A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2-8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed for recognition purposes. Obtained results suggest that T-H classifier enables to significantly increase classifier performance (resulting in accuracy of 76%, while maintaining average false positive detection rate of stimulus different then observed one between 2-13%, depending on stimulus frequency). It was shown that the parameters of T-H classifier, maximizing true positive rate, can be estimated by gradient-based search since the single maximum was observed. Moreover the preliminary results, performed on a test group (N=4), suggest that for T-H classifier exists a certain set of parameters for which the system accuracy is similar to accuracy obtained for user-trained classifier.

Validation of the Leap Motion Controller using markered motion capture technology.

PubMed

Smeragliuolo, Anna H; Hill, N Jeremy; Disla, Luis; Putrino, David

2016-06-14

The Leap Motion Controller (LMC) is a low-cost, markerless motion capture device that tracks hand, wrist and forearm position. Integration of this technology into healthcare applications has begun to occur rapidly, making validation of the LMC׳s data output an important research goal. Here, we perform a detailed evaluation of the kinematic data output from the LMC, and validate this output against gold-standard, markered motion capture technology. We instructed subjects to perform three clinically-relevant wrist (flexion/extension, radial/ulnar deviation) and forearm (pronation/supination) movements. The movements were simultaneously tracked using both the LMC and a marker-based motion capture system from Motion Analysis Corporation (MAC). Adjusting for known inconsistencies in the LMC sampling frequency, we compared simultaneously acquired LMC and MAC data by performing Pearson׳s correlation (r) and root mean square error (RMSE). Wrist flexion/extension and radial/ulnar deviation showed good overall agreement (r=0.95; RMSE=11.6°, and r=0.92; RMSE=12.4°, respectively) with the MAC system. However, when tracking forearm pronation/supination, there were serious inconsistencies in reported joint angles (r=0.79; RMSE=38.4°). Hand posture significantly influenced the quality of wrist deviation (P<0.005) and forearm supination/pronation (P<0.001), but not wrist flexion/extension (P=0.29). We conclude that the LMC is capable of providing data that are clinically meaningful for wrist flexion/extension, and perhaps wrist deviation. It cannot yet return clinically meaningful data for measuring forearm pronation/supination. Future studies should continue to validate the LMC as updated versions of their software are developed. Copyright © 2016 Elsevier Ltd. All rights reserved.

A Hands-on Exploration of the Retrograde Motion of Mars as Seen from the Earth

ERIC Educational Resources Information Center

Pincelli, M. M.; Otranto, S.

2013-01-01

In this paper, we propose a set of activities based on the use of a celestial simulator to gain insights into the retrograde motion of Mars as seen from the Earth. These activities provide a useful link between the heliocentric concepts taught in schools and those tackled in typical introductory physics courses based on classical mechanics for…

OCT-based angiography in real time with hand-held probe

NASA Astrophysics Data System (ADS)

Gelikonov, Grigory V.; Moiseev, Alexander A.; Ksenofontov, Sergey Y.; Terpelov, Dmitry A.; Gelikonov, Valentine M.

2018-03-01

This work is dedicated to development of the OCT system capable to visualize blood vessel network for everyday clinical use. Following problems were solved during the development: compensation of specific natural tissue displacements, induced by contact scanning mode and physiological motion of patients (e.g. respiratory and cardiac motions) and on-line visualization of vessel net to provide the feedback for system operator.

Grip Preference, Dermatoglyphics, and Hand Use in Captive Chimpanzees (Pan troglodytes)

PubMed Central

Hopkins, William D.; Russell, Jamie L.; Hostetter, Autumn; Pilcher, Dawn; Dahl, Jeremy F.

2007-01-01

This paper examined the association between grip type, hand use, and fingerprint patterns in a sample of captive chimpanzees. Grip type for simple reaching was assessed for the left and right hand and classified as thumb-index, middle-index, or single-digit responses. Fingerprint patterns were characterized as whorls, loops, or arches on each finger. The results indicated that chimpanzees exhibit significantly more thumb-index responses for the right compared to the left hand. In addition, thumb-index responses were more prevalent for subjects that had a whorl compared to a loop or arch on their thumb. The results suggest that fingerprint patterns are associated with individual differences in grasping type in chimpanzees as well as some variation in hand use. PMID:15761856

Recognizing human activities using appearance metric feature and kinematics feature

NASA Astrophysics Data System (ADS)

Qian, Huimin; Zhou, Jun; Lu, Xinbiao; Wu, Xinye

2017-05-01

The problem of automatically recognizing human activities from videos through the fusion of the two most important cues, appearance metric feature and kinematics feature, is considered. And a system of two-dimensional (2-D) Poisson equations is introduced to extract the more discriminative appearance metric feature. Specifically, the moving human blobs are first detected out from the video by background subtraction technique to form a binary image sequence, from which the appearance feature designated as the motion accumulation image and the kinematics feature termed as centroid instantaneous velocity are extracted. Second, 2-D discrete Poisson equations are employed to reinterpret the motion accumulation image to produce a more differentiated Poisson silhouette image, from which the appearance feature vector is created through the dimension reduction technique called bidirectional 2-D principal component analysis, considering the balance between classification accuracy and time consumption. Finally, a cascaded classifier based on the nearest neighbor classifier and two directed acyclic graph support vector machine classifiers, integrated with the fusion of the appearance feature vector and centroid instantaneous velocity vector, is applied to recognize the human activities. Experimental results on the open databases and a homemade one confirm the recognition performance of the proposed algorithm.

Brownian motion curve-based textural classification and its application in cancer diagnosis.

PubMed

Mookiah, Muthu Rama Krishnan; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

2011-06-01

To develop an automated diagnostic methodology based on textural features of the oral mucosal epithelium to discriminate normal and oral submucous fibrosis (OSF). A total of 83 normal and 29 OSF images from histopathologic sections of the oral mucosa are considered. The proposed diagnostic mechanism consists of two parts: feature extraction using Brownian motion curve (BMC) and design ofa suitable classifier. The discrimination ability of the features has been substantiated by statistical tests. An error back-propagation neural network (BPNN) is used to classify OSF vs. normal. In development of an automated oral cancer diagnostic module, BMC has played an important role in characterizing textural features of the oral images. Fisher's linear discriminant analysis yields 100% sensitivity and 85% specificity, whereas BPNN leads to 92.31% sensitivity and 100% specificity, respectively. In addition to intensity and morphology-based features, textural features are also very important, especially in histopathologic diagnosis of oral cancer. In view of this, a set of textural features are extracted using the BMC for the diagnosis of OSF. Finally, a textural classifier is designed using BPNN, which leads to a diagnostic performance with 96.43% accuracy. (Anal Quant

Using motion capture to assess colonoscopy experience level

PubMed Central

Svendsen, Morten Bo; Preisler, Louise; Hillingsoe, Jens Georg; Svendsen, Lars Bo; Konge, Lars

2014-01-01

AIM: To study technical skills of colonoscopists using a Microsoft Kinect™ for motion analysis to develop a tool to guide colonoscopy education. RESULTS: Ten experienced endoscopists (gastroenterologists, n = 2; colorectal surgeons, n = 8) and 11 novices participated in the study. A Microsoft Kinect™ recorded the movements of the participants during the insertion of the colonoscope. We used a modified script from Microsoft to record skeletal data. Data were saved and later transferred to MatLab for analysis and the calculation of statistics. The test was performed on a physical model, specifically the “Kagaku Colonoscope Training Model” (Kyoto Kagaku Co. Ltd, Kyoto, Japan). After the introduction to the scope and colonoscopy model, the test was performed. Seven metrics were analyzed to find discriminative motion patterns between the novice and experienced endoscopists: hand distance from gurney, number of times the right hand was used to control the small wheel of the colonoscope, angulation of elbows, position of hands in relation to body posture, angulation of body posture in relation to the anus, mean distance between the hands and percentage of time the hands were approximated to each other. RESULTS: Four of the seven metrics showed discriminatory ability: mean distance between hands [45 cm for experienced endoscopists (SD 2) vs 37 cm for novice endoscopists (SD 6)], percentage of time in which the two hands were within 25 cm of each other [5% for experienced endoscopists (SD 4) vs 12% for novice endoscopists (SD 9)], the level of the right hand below the sighting line (z-axis) (25 cm for experienced endoscopists vs 36 cm for novice endoscopists, P < 0.05) and the level of the left hand below the z-axis (6 cm for experienced endoscopists vs 15 cm for novice endoscopists, P < 0.05). By plotting the distributions of the percentages for each group, we determined the best discriminatory value between the groups. A pass score was set at the intersection of the distributions, and the consequences of the standard were explored for each test. By using the contrasting group method, we showed a discriminatory value of Z = 1.51 to be the pass/fail value of the data showing discriminatory ability. The pass score allowed all ten experienced endoscopists as well as five novice endoscopists to pass the test. CONCLUSION: Identified metrics can be used to discriminate between experienced and novice endoscopists and to provide non-biased feedback. Whether it is possible to use this tool to train novices in a clinical setting requires further study. PMID:24891932

A Novel Feature Selection Technique for Text Classification Using Naïve Bayes.

PubMed

Dey Sarkar, Subhajit; Goswami, Saptarsi; Agarwal, Aman; Aktar, Javed

2014-01-01

With the proliferation of unstructured data, text classification or text categorization has found many applications in topic classification, sentiment analysis, authorship identification, spam detection, and so on. There are many classification algorithms available. Naïve Bayes remains one of the oldest and most popular classifiers. On one hand, implementation of naïve Bayes is simple and, on the other hand, this also requires fewer amounts of training data. From the literature review, it is found that naïve Bayes performs poorly compared to other classifiers in text classification. As a result, this makes the naïve Bayes classifier unusable in spite of the simplicity and intuitiveness of the model. In this paper, we propose a two-step feature selection method based on firstly a univariate feature selection and then feature clustering, where we use the univariate feature selection method to reduce the search space and then apply clustering to select relatively independent feature sets. We demonstrate the effectiveness of our method by a thorough evaluation and comparison over 13 datasets. The performance improvement thus achieved makes naïve Bayes comparable or superior to other classifiers. The proposed algorithm is shown to outperform other traditional methods like greedy search based wrapper or CFS.

The influence of ship motion of manual control skills

NASA Technical Reports Server (NTRS)

Mcleod, P.; Poulton, C.; Duross, H.; Lewis, W.

1981-01-01

The effects of ship motion on a range of typical manual control skills were examined on the Warren Spring ship motion simulator driven in heave, pitch, and roll by signals taken from the frigate HMS Avenger at 13 m/s (25 knots) into a force 4 wind. The motion produced a vertical r.m.s. acceleration of 0.024g, mostly between 0.1 and 0.3 Hz, with comparatively little pitch or roll. A task involving unsupported arm movements was seriously affected by the motion; a pursuit tracking task showed a reliable decrement although it was still performed reasonably well (pressure and free moving tracking controls were affected equally by the motion); a digit keying task requiring ballistic hand movements was unaffected. There was no evidence that these effects were caused by sea sickness. The differing response to motion of the different tasks, from virtual destruction to no effect, suggests that a major benefit could come from an attempt to design the man/control interface onboard ship around motion resistant tasks.

Correlation mapping for visualizing propagation of pulsatile CSF motion in intracranial space based on magnetic resonance phase contrast velocity images: preliminary results.

PubMed

Yatsushiro, Satoshi; Hirayama, Akihiro; Matsumae, Mitsunori; Kajiwara, Nao; Abdullah, Afnizanfaizal; Kuroda, Kagayaki

2014-01-01

Correlation time mapping based on magnetic resonance (MR) velocimetry has been applied to pulsatile cerebrospinal fluid (CSF) motion to visualize the pressure transmission between CSF at different locations and/or between CSF and arterial blood flow. Healthy volunteer experiments demonstrated that the technique exhibited transmitting pulsatile CSF motion from CSF space in the vicinity of blood vessels with short delay and relatively high correlation coefficients. Patient and healthy volunteer experiments indicated that the properties of CSF motion were different from the healthy volunteers. Resultant images in healthy volunteers implied that there were slight individual difference in the CSF driving source locations. Clinical interpretation for these preliminary results is required to apply the present technique for classifying status of hydrocephalus.

System description document for the Anthrobot-2: A dexterous robot hand

NASA Technical Reports Server (NTRS)

Ali, Michael S.; Engler, Charles, Jr.

1991-01-01

The Anthrobot-2 is an anatomically correct, fully functioning robot hand. The number of fingers, the proportions of the links, the placement and motion of the thumb, and the shape of the palm follow those of the human hand. Each of the finger and thumb joints are servo-controlled. The Anthrobot-2 also includes a two-degree-of-freedom wrist. The entire package, including wrist, hand, and actuators, will mount on the ends of a variety of industrial manipulators. A patent has been applied for on the design. The Anthrobot-2 will be useful in tasks where dexterous manipulation or telemanipulation are required.

A bio-inspired design of a hand robotic exoskeleton for rehabilitation

NASA Astrophysics Data System (ADS)

Ong, Aira Patrice R.; Bugtai, Nilo T.

2018-02-01

This paper presents the methodology for the design of a five-degree of freedom wearable robotic exoskeleton for hand rehabilitation. The design is inspired by the biological structure and mechanism of the human hand. One of the distinct features of the device is the cable-driven actuation, which provides the flexion and extension motion. A prototype of the orthotic device has been developed to prove the model of the system and has been tested in a 3D printed mechanical hand. The result showed that the proposed device was consistent with the requirements of bionics and was able to demonstrate the flexion and extension of the system.

Interacting with mobile devices by fusion eye and hand gestures recognition systems based on decision tree approach

NASA Astrophysics Data System (ADS)

Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.

2017-03-01

Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.

Rapid and coordinated processing of global motion images by local clusters of retinal ganglion cells.

PubMed

Matsumoto, Akihiro; Tachibana, Masao

2017-01-01

Even when the body is stationary, the whole retinal image is always in motion by fixational eye movements and saccades that move the eye between fixation points. Accumulating evidence indicates that the brain is equipped with specific mechanisms for compensating for the global motion induced by these eye movements. However, it is not yet fully understood how the retina processes global motion images during eye movements. Here we show that global motion images evoke novel coordinated firing in retinal ganglion cells (GCs). We simultaneously recorded the firing of GCs in the goldfish isolated retina using a multi-electrode array, and classified each GC based on the temporal profile of its receptive field (RF). A moving target that accompanied the global motion (simulating a saccade following a period of fixational eye movements) modulated the RF properties and evoked synchronized and correlated firing among local clusters of the specific GCs. Our findings provide a novel concept for retinal information processing during eye movements.

A Non-Contact Measurement System for the Range of Motion of the Hand

PubMed Central

Pham, Trieu; Pathirana, Pubudu N.; Trinh, Hieu; Fay, Pearse

2015-01-01

An accurate and standardised tool to measure the active range of motion (ROM) of the hand is essential to any progressive assessment scenario in hand therapy practice. Goniometers are widely used in clinical settings for measuring the ROM of the hand. However, such measurements have limitations with regard to inter-rater and intra-rater reliability and involve direct physical contact with the hand, possibly increasing the risk of transmitting infections. The system proposed in this paper is the first non-contact measurement system utilising Intel Perceptual Technology and a Senz3D Camera for measuring phalangeal joint angles. To enhance the accuracy of the system, we developed a new approach to achieve the total active movement without measuring three joint angles individually. An equation between the actual spacial position and measurement value of the proximal inter-phalangeal joint was established through the measurement values of the total active movement, so that its actual position can be inferred. Verified by computer simulations, experimental results demonstrated a significant improvement in the calculation of the total active movement and successfully recovered the actual position of the proximal inter-phalangeal joint angles. A trial that was conducted to examine the clinical applicability of the system involving 40 healthy subjects confirmed the practicability and consistency in the proposed system. The time efficiency conveyed a stronger argument for this system to replace the current practice of using goniometers. PMID:26225976

Magnetotherapy in hand osteoarthritis: a pilot trial.

PubMed

Kanat, Elvan; Alp, Alev; Yurtkuran, Merih

2013-12-01

To evaluate the effectiveness of magnetotherapy in the treatment of hand osteoarthritis (HO). In this randomized controlled single-blind follow-up study, patients with HO were randomly assigned into 2 groups (G1 and G2). The subjects in G1 (n=25) received 25Hz, 450 pulse/s, 5-80G, magnetotherapy of totally 10 days and 20 min/day combined with active range of motion/strengthening exercises for the hand. G2 (n=25) received sham-magnetotherapy for 20 min/day for the same duration combined with the same hand exercises. Outcome measures were pain and joint stiffness evaluation, handgrip and pinchgrip strength (HPS), Duruöz and Auscan Hand Osteoarthritis Indexes (DAOI) and Short Form-36 Health Questionnaire (SF-36) administered at baseline, immediately after treatment and at the follow up. When the groups were compared with each other, improvement observed in SF-36 Pain (p<0.001), SF-36 Social Function (p=0.030), SF-36 Vitality (p=0.002), SF-36 General Health (p=0.001), Pain at rest (p<0.001), Pain at motion (p<0.001), Joint stiffness (p<0.001), DAOI (p<0.001) were in favor of G1. Changes in pain, function and quality of life scores showed significant advantage in favor of the applied electromagnetic intervention in patients with HO. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessing the Accuracy of a Wrist Motion Tracking Method for Counting Bites across Demographic and Food Variables

PubMed Central

Shen, Yiru; Salley, James; Muth, Eric; Hoover, Adam

2017-01-01

This paper describes a study to test the accuracy of a method that tracks wrist motion during eating to detect and count bites. The purpose was to assess its accuracy across demographic (age, gender, ethnicity) and bite (utensil, container, hand used, food type) variables. Data were collected in a cafeteria under normal eating conditions. A total of 271 participants ate a single meal while wearing a watch-like device to track their wrist motion. Video was simultaneously recorded of each participant and subsequently reviewed to determine the ground truth times of bites. Bite times were operationally defined as the moment when food or beverage was placed into the mouth. Food and beverage choices were not scripted or restricted. Participants were seated in groups of 2–4 and were encouraged to eat naturally. A total of 24,088 bites of 374 different food and beverage items were consumed. Overall the method for automatically detecting bites had a sensitivity of 75% with a positive predictive value of 89%. A range of 62–86% sensitivity was found across demographic variables, with slower eating rates trending towards higher sensitivity. Variations in sensitivity due to food type showed a modest correlation with the total wrist motion during the bite, possibly due to an increase in head-towards-plate motion and decrease in hand-towards-mouth motion for some food types. Overall, the findings provide the largest evidence to date that the method produces a reliable automated measure of intake during unrestricted eating. PMID:28113994

The Classification of Swanson for Congenital Anomalies of Upper Limb Modified by the Japanese Society for Surgery of the Hand (JSSH).

PubMed

Iba, Kousuke; Horii, Emiko; Ogino, Toshihiko; Kazuki, Kenichi; Kashiwa, Katsuhiko

2015-01-01

The aim of this study is to introduce the classification of Swanson for congenital anomalies of upper limb modified by the Japanese Society for Surgery of the Hand (the JSSH modification) in English. The Swanson classification has been widely accepted by most hand surgeons. However, several authors have suggested that complex cases, particularly those involving the complex spectrum of cleft hand and symbrachydactyly, are difficult to classify into the classification schemes. In the JSSH modification, brachysyndactyly, so-called atypical cleft hand and transverse deficiency are included under the same concept of transverse deficiency. Cleft hand, central polydactyly, and syndactyly are included in the same category of abnormal induction of digital rays. We believe that the JSSH modification system is effective in providing hand surgeons with the clinical features and conditions for congenital anomalies.

EEG-Based Brain-Computer Interface for Decoding Motor Imagery Tasks within the Same Hand Using Choi-Williams Time-Frequency Distribution

PubMed Central

Alwanni, Hisham; Baslan, Yara; Alnuman, Nasim; Daoud, Mohammad I.

2017-01-01

This paper presents an EEG-based brain-computer interface system for classifying eleven motor imagery (MI) tasks within the same hand. The proposed system utilizes the Choi-Williams time-frequency distribution (CWD) to construct a time-frequency representation (TFR) of the EEG signals. The constructed TFR is used to extract five categories of time-frequency features (TFFs). The TFFs are processed using a hierarchical classification model to identify the MI task encapsulated within the EEG signals. To evaluate the performance of the proposed approach, EEG data were recorded for eighteen intact subjects and four amputated subjects while imagining to perform each of the eleven hand MI tasks. Two performance evaluation analyses, namely channel- and TFF-based analyses, are conducted to identify the best subset of EEG channels and the TFFs category, respectively, that enable the highest classification accuracy between the MI tasks. In each evaluation analysis, the hierarchical classification model is trained using two training procedures, namely subject-dependent and subject-independent procedures. These two training procedures quantify the capability of the proposed approach to capture both intra- and inter-personal variations in the EEG signals for different MI tasks within the same hand. The results demonstrate the efficacy of the approach for classifying the MI tasks within the same hand. In particular, the classification accuracies obtained for the intact and amputated subjects are as high as 88.8% and 90.2%, respectively, for the subject-dependent training procedure, and 80.8% and 87.8%, respectively, for the subject-independent training procedure. These results suggest the feasibility of applying the proposed approach to control dexterous prosthetic hands, which can be of great benefit for individuals suffering from hand amputations. PMID:28832513

Imagined Hand Clenching Force and Speed Modulate Brain Activity and Are Classified by NIRS Combined With EEG.

PubMed

Fu, Yunfa; Xiong, Xin; Jiang, Changhao; Xu, Baolei; Li, Yongcheng; Li, Hongyi

2017-09-01

Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class classification of these imagined motor parameters by NIRS-EEG were explored. Near infrared probes were aligned with C3 and C4, and EEG electrodes were placed midway between the NIRS probes. NIRS and EEG signals were acquired from six healthy subjects during six imagined hand clenching force and speed tasks involving the right hand. The results showed that NIRS combined with EEG is effective for simultaneously measuring brain activity of the sensorimotor area. The study also showed that in the duration of (0, 10) s for imagined force and speed of hand clenching, HbO first exhibited a negative variation trend, which was followed by a negative peak. After the negative peak, it exhibited a positive variation trend with a positive peak about 6-8 s after termination of imagined movement. During (-2, 1) s, the EEG may have indicated neural processing during the preparation, execution, and monitoring of a given imagined force and speed of hand clenching. The instantaneous phase, frequency, and amplitude feature of the EEG were calculated by Hilbert transform; HbO and the difference between HbO and Hb concentrations were extracted. The features of NIRS and EEG were combined to classify three levels of imagined force [at 20/50/80% MVGF (maximum voluntary grip force)] and speed (at 0.5/1/2 Hz) of hand clenching by SVM. The average classification accuracy of the NIRS-EEG fusion feature was 0.74 ± 0.02. These results may provide increased control commands of force and speed for a brain-controlled robot based on NIRS-EEG.

Osteoarthritis

MedlinePlus

Osteoarthritis is the most common form of arthritis. It causes pain, swelling, and reduced motion in your ... it affects your hands, knees, hips or spine. Osteoarthritis breaks down the cartilage in your joints. Cartilage ...

Pendular motion in the brachiation of captive Lagothrix and Ateles.

PubMed

Turnquist, J E; Schmitt, D; Rose, M D; Cant, J G

1999-01-01

Pendular motion during brachiation of captive Lagothrix lagothricha lugens and Ateles fusciceps robustus was analyzed to demonstrate similarities, and differences, between these two closely related large bodied atelines. This is the first captive study of the kinematics of brachiation in Lagothrix. Videorecordings of one adult male of each species were made in a specially designed cage constructed at the DuMond Conservancy/Monkey Jungle, Miami, FL. Java software (Jandel Scientific Inc., San Rafael, CA) was used for frame-by-frame kinematic analysis of individual strides/steps. Results demonstrate that the sequence of hand and tail contacts differ significantly between the two species with Lagothrix using a new tail hold with every hand hold, while Ateles generally utilizes a new tail hold with only every other hand hold. Stride length and stride frequency, even after adjusting for limb length, also differ significantly between the two species. Lagothrix brachiation utilizes short, choppy strides with quick hand holds, while Ateles uses long, fluid strides with longer hand holds. During brachiation not only is Lagothrix's body significantly less horizontal than that of Ateles but also, within Ateles, there are significant differences between steps depending on tail use. Because of the unique nature of tail use in Ateles, many aspects of body positioning in Lagothrix more closely resemble Ateles steps without a simultaneous tail hold rather than those with one. Overall pendulum length in Lagothrix is shorter than in Ateles. Tail use in Ateles has a significant effect on maximum pendulum length during a step. Although neither species achieves the extreme pendulum effect and long period of free-flight of hylobatids in fast ricochetal brachiation, in captivity both consistently demonstrate effective brachiation with brief periods of free-flight and pendular motion. Morphological similarities between ateline brachiators and hylobatids are fewer and less pronounced in Lagothrix than in Ateles. This study demonstrates that Lagothrix brachiation is also less hylobatid-like than that of Ateles.

Tracking and Counting Motion for Monitoring Food Intake Based-On Depth Sensor and UDOO Board: A Comprehensive Review

NASA Astrophysics Data System (ADS)

Kassim, Muhammad Fuad bin; Norzali Haji Mohd, Mohd

2017-08-01

Technology is all about helping people, which created a new opportunity to take serious action in managing their health care. Moreover, Obesity continues to be a serious public health concern in the Malaysia and continuing to rise. Obesity has been a serious health concern among people. Nearly half of Malaysian people overweight. Most of dietary approach is not tracking and detecting the right calorie intake for weight loss, but currently used tools such as food diaries require users to manually record and track the food calories, making them difficult for daily use. We will be developing a new tool that counts the food intake bite by monitoring hand gesture and face jaw motion movement of caloric intake. The Bite count method showed a good significant that can lead to a successful weight loss by simply monitoring the bite taken during eating. The device used was Kinect Xbox One which used a depth camera to detect the motion on person hand and face during food intake. Previous studies showed that most of the method used to count bite device is worn type. The recent trend is now going towards non-wearable devices due to the difficulty when wearing devices and it has high false alarm ratio. The proposed system gets data from the Kinect that will be monitoring the hand and face gesture of the user while eating. Then, the gesture of hand and face data is sent to the microcontroller board to recognize and start counting bite taken by the user. The system recognizes the patterns of bite taken from user by following the algorithm of basic eating type either using hand or chopstick. This system can help people who are trying to follow a proper way to reduce overweight or eating disorders by monitoring their meal intake and controlling eating rate.

Segmentation of human upper body movement using multiple IMU sensors.

PubMed

Aoki, Takashi; Lin, Jonathan Feng-Shun; Kulic, Dana; Venture, Gentiane

2016-08-01

This paper proposes an approach for the segmentation of human body movements measured by inertial measurement unit sensors. Using the angular velocity and linear acceleration measurements directly, without converting to joint angles, we perform segmentation by formulating the problem as a classification problem, and training a classifier to differentiate between motion end-point and within-motion points. The proposed approach is validated with experiments measuring the upper body movement during reaching tasks, demonstrating classification accuracy of over 85.8%.

A Robust and Fast Computation Touchless Palm Print Recognition System Using LHEAT and the IFkNCN Classifier

PubMed Central

Jaafar, Haryati; Ibrahim, Salwani; Ramli, Dzati Athiar

2015-01-01

Mobile implementation is a current trend in biometric design. This paper proposes a new approach to palm print recognition, in which smart phones are used to capture palm print images at a distance. A touchless system was developed because of public demand for privacy and sanitation. Robust hand tracking, image enhancement, and fast computation processing algorithms are required for effective touchless and mobile-based recognition. In this project, hand tracking and the region of interest (ROI) extraction method were discussed. A sliding neighborhood operation with local histogram equalization, followed by a local adaptive thresholding or LHEAT approach, was proposed in the image enhancement stage to manage low-quality palm print images. To accelerate the recognition process, a new classifier, improved fuzzy-based k nearest centroid neighbor (IFkNCN), was implemented. By removing outliers and reducing the amount of training data, this classifier exhibited faster computation. Our experimental results demonstrate that a touchless palm print system using LHEAT and IFkNCN achieves a promising recognition rate of 98.64%. PMID:26113861

Noninvasive near-infrared topography of human brain activity using intensity modulation spectroscopy

NASA Astrophysics Data System (ADS)

Yamashita, Yuichi; Maki, Atsushi; Ito, Yoshitoshi; Watanabe, Eiju; Mayanagi, Yoshiaki; Koizumi, Hideaki

1996-04-01

We describe the functional topography of human brain activity due to motor stimulation by using near-infrared spectroscopy. Finger motion by each hand was used as the motor stimulation, and activity in the left fronto-central region of the brain was measured. A greater change in oxyhemoglobin concentration due to brain activity during the stimulation was obtained for the right hand than for the left hand. Localization of the activity was obtained by topographically mapping the measured changes for ten positions within the region.

Exploding Balloons, Deformed Balls, Strange Reflections and Breaking Rods: Slow Motion Analysis of Selected Hands-On Experiments

ERIC Educational Resources Information Center

Vollmer, Michael; Mollmann, Klaus-Peter

2011-01-01

A selection of hands-on experiments from different fields of physics, which happen too fast for the eye or video cameras to properly observe and analyse the phenomena, is presented. They are recorded and analysed using modern high speed cameras. Two types of cameras were used: the first were rather inexpensive consumer products such as Casio…

A feasibility study of hand kinematics for EVA analysis using magnetic resonance imaging

NASA Technical Reports Server (NTRS)

Dickenson, Rueben D.; Lorenz, Christine H.; Peterson, Steven W.; Strauss, Alvin M.; Main, John A.

1992-01-01

A new method of analyzing the kinematics of joint motion is developed. Magnetic Resonance Imaging (MRI) offers several distinct advantages. Past methods of studying anatomic joint motion have usually centered on four approaches. These methods are x-ray projection, goniometric linkage analysis, sonic digitization, and landmark measurement of photogrammetry. Of these four, only x-ray is applicable for in vivo studies. The remaining three methods utilize other types of projections of inter-joint measurements, which can cause various types of error. MRI offers accuracy in measurement due to its tomographic nature (as opposed to projection) without the problems associated with x-ray dosage. Once the data acquisition of MR images was complete, the images were processed using a 3D volume rendering workstation. The metacarpalphalangeal (MCP) joint of the left index finger was selected and reconstructed into a three-dimensional graphic display. From the reconstructed volumetric images, measurements of the angles of movement of the applicable bones were obtained and processed by analyzing the screw motion of the MCP joint. Landmark positions were chosen at distinctive locations of the joint at fixed image threshold intensity levels to ensure repeatability. The primarily two dimensional planar motion of this joint was then studied using a method of constructing coordinate systems using three (or more) points. A transformation matrix based on a world coordinate system described the location and orientation of a local target coordinate system. Future research involving volume rendering of MRI data focusing on the internal kinematics of the hand's individual ligaments, cartilage, tendons, etc. will follow. Its findings will show the applicability of MRI to joint kinematics for gaining further knowledge of the hand-glove (power assisted) design for extravehicular activity (EVA).

Real-time, ultrasound-based control of a virtual hand by a trans-radial amputee.

PubMed

Baker, Clayton A; Akhlaghi, Nima; Rangwala, Huzefa; Kosecka, Jana; Sikdar, Siddhartha

2016-08-01

Advancements in multiarticulate upper-limb prosthetics have outpaced the development of intuitive, non-invasive control mechanisms for implementing them. Surface electromyography is currently the most popular non-invasive control method, but presents a number of drawbacks including poor deep-muscle specificity. Previous research established the viability of ultrasound imaging as an alternative means of decoding movement intent, and demonstrated the ability to distinguish between complex grasps in able-bodied subjects via imaging of the anterior forearm musculature. In order to translate this work to clinical viability, able-bodied testing is insufficient. Amputation-induced changes in muscular geometry, dynamics, and imaging characteristics are all likely to influence the effectiveness of our existing techniques. In this work, we conducted preliminary trials with a transradial amputee participant to assess these effects, and potentially elucidate necessary refinements to our approach. Two trials were performed, the first using a set of three motion types, and the second using four. After a brief training period in each trial, the participant was able to control a virtual prosthetic hand in real-time; attempted grasps were successfully classified with a rate of 77% in trial 1, and 71% in trial 2. While the results are sub-optimal compared to our previous able-bodied testing, they are a promising step forward. More importantly, the data collected during these trials can provide valuable information for refining our image processing methods, especially via comparison to previously acquired data from able-bodied individuals. Ultimately, further work with amputees is a necessity for translation towards clinical application.

Picosecond molecular motions in bacteriorhodopsin from neutron scattering.

PubMed Central

Fitter, J; Lechner, R E; Dencher, N A

1997-01-01

The characteristics of internal molecular motions of bacteriorhodopsin in the purple membrane have been studied by quasielastic incoherent neutron scattering. Because of the quasihomogeneous distribution of hydrogen atoms in biological molecules, this technique enables one to study a wide variety of intramolecular motions, especially those occurring in the picosecond to nanosecond time scale. We performed measurements at different energy resolutions with samples at various hydration levels within a temperature range of 10-300 K. The analysis of the data revealed a dynamical transition at temperatures Td between 180 K and 220 K for all motions resolved at time scales ranging from 0.1 to a few hundred picoseconds. Whereas below Td the motions are purely vibrational, they are predominantly diffusive above Td, characterized by an enormously broad distribution of correlation times. The variation of the hydration level, on the other hand, mainly affects motions slower than a few picoseconds. PMID:9336208

A Bio-Inspired, Motion-Based Analysis of Crowd Behavior Attributes Relevance to Motion Transparency, Velocity Gradients, and Motion Patterns

PubMed Central

Raudies, Florian; Neumann, Heiko

2012-01-01

The analysis of motion crowds is concerned with the detection of potential hazards for individuals of the crowd. Existing methods analyze the statistics of pixel motion to classify non-dangerous or dangerous behavior, to detect outlier motions, or to estimate the mean throughput of people for an image region. We suggest a biologically inspired model for the analysis of motion crowds that extracts motion features indicative for potential dangers in crowd behavior. Our model consists of stages for motion detection, integration, and pattern detection that model functions of the primate primary visual cortex area (V1), the middle temporal area (MT), and the medial superior temporal area (MST), respectively. This model allows for the processing of motion transparency, the appearance of multiple motions in the same visual region, in addition to processing opaque motion. We suggest that motion transparency helps to identify “danger zones” in motion crowds. For instance, motion transparency occurs in small exit passages during evacuation. However, motion transparency occurs also for non-dangerous crowd behavior when people move in opposite directions organized into separate lanes. Our analysis suggests: The combination of motion transparency and a slow motion speed can be used for labeling of candidate regions that contain dangerous behavior. In addition, locally detected decelerations or negative speed gradients of motions are a precursor of danger in crowd behavior as are globally detected motion patterns that show a contraction toward a single point. In sum, motion transparency, image speeds, motion patterns, and speed gradients extracted from visual motion in videos are important features to describe the behavioral state of a motion crowd. PMID:23300930

Teacher-in-Space Trainees - Arriflex Motion Picture Camera

NASA Image and Video Library

1985-09-20

S85-40668 (18 Sept. 1985) --- The two teachers, Sharon Christa McAuliffe (left) and Barbara R. Morgan have hands-on experience with an Arriflex motion picture camera following a briefing on space photography. The two began training Sept. 10, 1985 with the STS-51L crew and learning basic procedures for space travelers. The second week of training included camera training, aircraft familiarization and other activities. Photo credit: NASA

Suppurative peritonitis by Klebsiella pneumoniae in captive gold-handed tamarin (Saguinus midas midas).

PubMed

Guerra, Maria F L; Teixeira, Rodrigo H F; Ribeiro, Vanessa L; Cunha, Marcos P V; Oliveira, Maria G X; Davies, Yamê M; Silva, Ketrin C; Silva, Ana P S; Lincopan, Nilton; Moreno, Andrea M; Knöbl, Terezinha

2016-02-01

This report describes an outbreak of suppurative peritonitis caused by Klebsiella pneumoniae in an adult female of captive golden-handed tamarin (Saguinus midas midas). Two virulent and multidrug-resistant strains were isolated and classified through MLST as ST60 and ST1263. The microbiological diagnosis works as a support tool for preventive measures. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Development of hand rehabilitation system for paralysis patient - universal design using wire-driven mechanism.

PubMed

Yamaura, Hiroshi; Matsushita, Kojiro; Kato, Ryu; Yokoi, Hiroshi

2009-01-01

We have developed a hand rehabilitation system for patients suffering from paralysis or contracture. It consists of two components: a hand rehabilitation machine, which moves human finger joints with motors, and a data glove, which provides control of the movement of finger joints attached to the rehabilitation machine. The machine is based on the arm structure type of hand rehabilitation machine; a motor indirectly moves a finger joint via a closed four-link mechanism. We employ a wire-driven mechanism and develop a compact design that can control all three joints (i.e., PIP, DIP and MP ) of a finger and that offers a wider range of joint motion than conventional systems. Furthermore, we demonstrate the hand rehabilitation process, finger joints of the left hand attached to the machine are controlled by the finger joints of the right hand wearing the data glove.

Experiments and kinematics analysis of a hand rehabilitation exoskeleton with circuitous joints.

PubMed

Zhang, Fuhai; Fu, Yili; Zhang, Qinchao; Wang, Shuguo

2015-01-01

Aiming at the hand rehabilitation of stroke patients, a wearable hand exoskeleton with circuitous joint is proposed. The circuitous joint adopts the symmetric pinion and rack mechanism (SPRM) with the parallel mechanism. The exoskeleton finger is a serial mechanism composed of three closed-chain SPRM joints in series. The kinematic equations of the open chain of the finger and the closed chains of the SPRM joints were built to analyze the kinematics of the hand rehabilitation exoskeleton. The experimental setup of the hand rehabilitation exoskeleton was built and the continuous passive motion (CPM) rehabilitation experiment and the test of human-robot interaction force measurement were conducted. Experiment results show that the mechanical design of the hand rehabilitation robot is reasonable and that the kinematic analysis is correct, thus the exoskeleton can be used for the hand rehabilitation of stroke patients.

Hand Rehabilitation Learning System With an Exoskeleton Robotic Glove.

PubMed

Ma, Zhou; Ben-Tzvi, Pinhas; Danoff, Jerome

2016-12-01

This paper presents a hand rehabilitation learning system, the SAFE Glove, a device that can be utilized to enhance the rehabilitation of subjects with disabilities. This system is able to learn fingertip motion and force for grasping different objects and then record and analyze the common movements of hand function including grip and release patterns. The glove is then able to reproduce these movement patterns in playback fashion to assist a weakened hand to accomplish these movements, or to modulate the assistive level based on the user's or therapist's intent for the purpose of hand rehabilitation therapy. Preliminary data have been collected from healthy hands. To demonstrate the glove's ability to manipulate the hand, the glove has been fitted on a wooden hand and the grasping of various objects was performed. To further prove that hands can be safely driven by this haptic mechanism, force sensor readings placed between each finger and the mechanism are plotted. These experimental results demonstrate the potential of the proposed system in rehabilitation therapy.

The Design of Hand Gestures for Human-Computer Interaction: Lessons from Sign Language Interpreters

PubMed Central

Rempel, David; Camilleri, Matt J.; Lee, David L.

2015-01-01

The design and selection of 3D modeled hand gestures for human-computer interaction should follow principles of natural language combined with the need to optimize gesture contrast and recognition. The selection should also consider the discomfort and fatigue associated with distinct hand postures and motions, especially for common commands. Sign language interpreters have extensive and unique experience forming hand gestures and many suffer from hand pain while gesturing. Professional sign language interpreters (N=24) rated discomfort for hand gestures associated with 47 characters and words and 33 hand postures. Clear associations of discomfort with hand postures were identified. In a nominal logistic regression model, high discomfort was associated with gestures requiring a flexed wrist, discordant adjacent fingers, or extended fingers. These and other findings should be considered in the design of hand gestures to optimize the relationship between human cognitive and physical processes and computer gesture recognition systems for human-computer input. PMID:26028955

[The effect of floating-needle therapy combined with rehabilitation training for the hand function recovery of post-stroke patients].

PubMed

Yang, Jiangxia; Xiao, Hong

2015-08-01

To explore the improvement of hand motion function,spasm and self-care ability of daily life for stroke patients treated with floating-needle combined with rehabilitation training. Eighty hand spasm patients of post-stroke within one year after stroke were randomly divided into an observation group and a control group, 40 cases in each one. In the two groups, rehabilitation was adopted for eight weeks,once a day,40 min one time. In the observation group, based on the above treatment and according to muscle fascia trigger point, 2~3 points in both the internal and external sides of forearm were treated with floating-needle. The positive or passive flexion and extension of wrist and knuckle till the relief of spasm hand was combined. The floating-needle therapy was given for eight weeks, on the first three days once a day and later once every other day. Modified Ashworth Scale(MAS), activity of daily life(ADL, Barthel index) scores and Fugl-Meyer(FMA) scores were used to assess the spasm hand degree,activity of daily life and hand motion function before and after 7-day, 14-day and 8-week treatment. After 7-day, 14-day and 8-week treatment, MAS scores were apparently lower than those before treatment in the two groups(all P<0. 05), and Barthel scores and FMA scores were obviously higher than those before-treatment(all P<0. 05). After 14-day and 8-week treatment, FMA scores in the observation group were markedly higher than those in the control group(both P<0. 05). Floating-needle therapy combined with rehabilitation training and simple rehabilitation training could both improve hand spasm degree, hand function and activity of daily life of post-stroke patients, but floating-needle therapy combined with rehabilitation training is superior to simple rehabilitation training for the improvement of hand function.

Consistency of hand preference: predictions to intelligence and school achievement.

PubMed

Kee, D W; Gottfried, A; Bathurst, K

1991-05-01

Gottfried and Bathurst (1983) reported that hand preference consistency measured over time during infancy and early childhood predicts intellectual precocity for females, but not for males. In the present study longitudinal assessments of children previously classified by Gottfried and Bathurst as consistent or nonconsistent in cross-time hand preference were conducted during middle childhood (ages 5 to 9). Findings show that (a) early measurement of hand preference consistency for females predicts school-age intellectual precocity, (b) the locus of the difference between consistent vs. nonconsistent females is in verbal intelligence, and (c) the precocity of the consistent females was also revealed on tests of school achievement, particularly tests of reading and mathematics.

Computational validation of the motor contribution to speech perception.

PubMed

Badino, Leonardo; D'Ausilio, Alessandro; Fadiga, Luciano; Metta, Giorgio

2014-07-01

Action perception and recognition are core abilities fundamental for human social interaction. A parieto-frontal network (the mirror neuron system) matches visually presented biological motion information onto observers' motor representations. This process of matching the actions of others onto our own sensorimotor repertoire is thought to be important for action recognition, providing a non-mediated "motor perception" based on a bidirectional flow of information along the mirror parieto-frontal circuits. State-of-the-art machine learning strategies for hand action identification have shown better performances when sensorimotor data, as opposed to visual information only, are available during learning. As speech is a particular type of action (with acoustic targets), it is expected to activate a mirror neuron mechanism. Indeed, in speech perception, motor centers have been shown to be causally involved in the discrimination of speech sounds. In this paper, we review recent neurophysiological and machine learning-based studies showing (a) the specific contribution of the motor system to speech perception and (b) that automatic phone recognition is significantly improved when motor data are used during training of classifiers (as opposed to learning from purely auditory data). Copyright © 2014 Cognitive Science Society, Inc.

Management of the Stiff Finger: Evidence and Outcomes

PubMed Central

Yang, Guang; McGlinn, Evan P.; Chung, Kevin C.

2014-01-01

SYNOPSIS The term “stiff finger” refers to a reduction in the range of motion in the finger, and it is a condition that has many different causes and involves a number of different structures. Almost all injuries of the fingers and some diseases can cause finger stiffness. Hand surgeons often face difficulty treating stiff fingers that are affected by irreversible soft tissues fibrosis. Stiff fingers can be divided into flexion and extension deformities. They can also be sub-classified into four categories according to the involved tissues extending from the skin to the joint capsule. Prevention of stiff fingers by judicious mobilization of the joints is prudent to avoid more complicated treatment after established stiffness occurs. Static progressive and dynamic splints have been considered as effective non-operative interventions to treat stiff fingers. Most authors believe force of joint distraction and time duration of stretching are two important factors to consider while applying a splint or cast. We also introduce the concepts of capsulotomy and collateral ligament release and other soft tissue release of the MCP and PIP joint in this article. Future outcomes research is vital to assessing the effectiveness of these surgical procedures and guiding postoperative treatment recommendations. PMID:24996467

Chaos and nonlinear dynamics of single-particle orbits in a magnetotaillike magnetic field

NASA Technical Reports Server (NTRS)

Chen, J.; Palmadesso, P. J.

1986-01-01

The properties of charged-particle motion in Hamiltonian dynamics are studied in a magnetotaillike magnetic field configuration. It is shown by numerical integration of the equation of motion that the system is generally nonintegrable and that the particle motion can be classified into three distinct types of orbits: bounded integrable orbits, unbounded stochastic orbits, and unbounded transient orbits. It is also shown that different regions of the phase space exhibit qualitatively different responses to external influences. The concept of 'differential memory' in single-particle distributions is proposed. Physical implications for the dynamical properties of the magnetotail plasmas and the possible generation of non-Maxwellian features in the distribution functions are discussed.

Idea Project Final Report, Laser Vehicle Detector-Classifier

DOT National Transportation Integrated Search

1995-11-28

WEIGH-IN-MOTION OR WIM, COMMERCIAL VEHICLE OPERATIONS OR CVO : THIS INVESTIGATION WAS COMPLETED AS PART OF THE ITS-IDEA PROGRAM, WHICH IS ONE OF THREE IDEA PROGRAMS MANAGED BY THE TRANSPORTATION RESEARCH BOARD (TRB) TO FOSTER INNOVATIONS IN SURFAC...

Image registration for multi-exposed HDRI and motion deblurring

NASA Astrophysics Data System (ADS)

Lee, Seok; Wey, Ho-Cheon; Lee, Seong-Deok

2009-02-01

In multi-exposure based image fusion task, alignment is an essential prerequisite to prevent ghost artifact after blending. Compared to usual matching problem, registration is more difficult when each image is captured under different photographing conditions. In HDR imaging, we use long and short exposure images, which have different brightness and there exist over/under satuated regions. In motion deblurring problem, we use blurred and noisy image pair and the amount of motion blur varies from one image to another due to the different exposure times. The main difficulty is that luminance levels of the two images are not in linear relationship and we cannot perfectly equalize or normalize the brightness of each image and this leads to unstable and inaccurate alignment results. To solve this problem, we applied probabilistic measure such as mutual information to represent similarity between images after alignment. In this paper, we discribed about the characteristics of multi-exposed input images in the aspect of registration and also analyzed the magnitude of camera hand shake. By exploiting the independence of luminance of mutual information, we proposed a fast and practically useful image registration technique in multiple capturing. Our algorithm can be applied to extreme HDR scenes and motion blurred scenes with over 90% success rate and its simplicity enables to be embedded in digital camera and mobile camera phone. The effectiveness of our registration algorithm is examined by various experiments on real HDR or motion deblurring cases using hand-held camera.

Motion artifact detection and correction in functional near-infrared spectroscopy: a new hybrid method based on spline interpolation method and Savitzky-Golay filtering.

PubMed

Jahani, Sahar; Setarehdan, Seyed K; Boas, David A; Yücel, Meryem A

2018-01-01

Motion artifact contamination in near-infrared spectroscopy (NIRS) data has become an important challenge in realizing the full potential of NIRS for real-life applications. Various motion correction algorithms have been used to alleviate the effect of motion artifacts on the estimation of the hemodynamic response function. While smoothing methods, such as wavelet filtering, are excellent in removing motion-induced sharp spikes, the baseline shifts in the signal remain after this type of filtering. Methods, such as spline interpolation, on the other hand, can properly correct baseline shifts; however, they leave residual high-frequency spikes. We propose a hybrid method that takes advantage of different correction algorithms. This method first identifies the baseline shifts and corrects them using a spline interpolation method or targeted principal component analysis. The remaining spikes, on the other hand, are corrected by smoothing methods: Savitzky-Golay (SG) filtering or robust locally weighted regression and smoothing. We have compared our new approach with the existing correction algorithms in terms of hemodynamic response function estimation using the following metrics: mean-squared error, peak-to-peak error ([Formula: see text]), Pearson's correlation ([Formula: see text]), and the area under the receiver operator characteristic curve. We found that spline-SG hybrid method provides reasonable improvements in all these metrics with a relatively short computational time. The dataset and the code used in this study are made available online for the use of all interested researchers.

Motion-compensated detection of heart rate based on the time registration adaptive filter

NASA Astrophysics Data System (ADS)

Yang, Lei; Zhou, Jinsong; Jing, Juanjuan; Li, Yacan; Wei, Lidong; Feng, Lei; He, Xiaoying; Bu, Meixia; Fu, Xilu

2018-01-01

A non-contact heart rate detection method based on the dual-wavelength technique is proposed and demonstrated experimentally. The heart rate is obtained based on the PhotoPlethysmoGraphy (PPG). Each detection module uses the reflection detection probe which is composed of the LED and the photodiode. It is a well-known fact that the differences in the circuits of two detection modules result in different responses of two modules for motion artifacts. It will cause a time delay between the two signals. This poses a great challenge to compensate the motion artifacts during measurements. In order to solve this problem, we have firstly used the time registration and translated the signals to ensure that the two signals are consistent in time domain. Then the adaptive filter is used to compensate the motion artifacts. Moreover, the data obtained by using this non-contact detection system is compared with those of the conventional finger blood volume pulse (BVP) sensor by simultaneously measuring the heart rate of the subject. During the experiment, the left hand remains stationary and is detected by a conventional finger BVP sensor. Meanwhile, the moving palm of right hand is detected by the proposed system. The data obtained from the proposed non-contact system are consistent and comparable with that of the BVP sensor. This method can effectively suppress the interference caused by the two circuit differences and successfully compensate the motion artifacts. This technology can be used in medical and daily heart rate measurement.

Grip preference, dermatoglyphics, and hand use in captive chimpanzees (Pan troglodytes).

PubMed

Hopkins, William D; Russell, Jamie L; Hostetter, Autumn; Pilcher, Dawn; Dahl, Jeremy F

2005-09-01

This paper examined the association between grip type, hand use, and fingerprint patterns in a sample of captive chimpanzees. Grip type for simple reaching was assessed for the left and right hand and classified as thumb-index, middle-index, or single-digit responses. Fingerprint patterns were characterized as whorls, loops, or arches on each finger. The results indicated that chimpanzees exhibit significantly more thumb-index responses for the right compared to the left hand. In addition, thumb-index responses were more prevalent for subjects that had a whorl compared to a loop or arch on their thumb. The results suggest that fingerprint patterns are associated with individual differences in grasping type in chimpanzees as well as some variation in hand use. (c) 2005 Wiley-Liss, Inc.

Kinematics and force analysis of a robot hand based on an artificial biological control scheme

NASA Astrophysics Data System (ADS)

Kim, Man Guen

An artificial biological control scheme (ABCS) is used to study the kinematics and statics of a multifingered hand with a view to developing an efficient control scheme for grasping. The ABCS is based on observation of human grasping, intuitively taking it as the optimum model for robotic grasping. A final chapter proposes several grasping measures to be applied to the design and control of a robot hand. The ABCS leads to the definition of two modes of the grasping action: natural grasping (NG), which is the human motion to grasp the object without any special task command, and forced grasping (FG), which is the motion with a specific task. The grasping direction line (GDL) is defined to determine the position and orientation of the object in the hand. The kinematic model of a redundant robot arm and hand is developed by reconstructing the human upper extremity and using anthropometric measurement data. The inverse kinematic analyses of various types of precision and power grasping are studied by replacing the three-link with one virtual link and using the GDL. The static force analysis for grasping with fingertips is studied by applying the ABCS. A measure of grasping stability, that maintains the positions of contacts as well as the configurations of the redundant fingers, is derived. The grasping stability measure (GSM), a measure of how well the hand maintains grasping under the existence of external disturbance, is derived by the torque vector of the hand calculated from the external force applied to the object. The grasping manipulability measure (GMM), a measure of how well the hand manipulates the object for the task, is derived by the joint velocity vector of the hand calculated from the object velocity. The grasping performance measure (GPM) is defined by the sum of the directional components of the GSM and the GMM. Finally, a planar redundant hand with two fingers is examined in order to study the various postures of the hand performing pinch grasping by applying the GSM and the GMM.

Advances In Engineering Science, Volume 2.

DTIC Science & Technology

1976-11-01

UNDRAINED CLAY BEHAVIOR .... ............ .. 95 Jean-Herve Prevost and Kaare H~eg THEORY OF ORTHODONTIC MOTIONS...compo- nents at a lower level are terminal nodes of a tree. The bracketed numbers on the right hand side of the terminating nodes are the number of...primitive data objects in each instance of the defined object. The bracketed numbers on the right hand side of the non-terminal nodes in the tree are the

A New Movement Detector to Enable People with Multiple Disabilities to Control Environmental Stimulation with Hand Swing through a Commercial Mouse

ERIC Educational Resources Information Center

Shih, Ching-Hsiang; Shih, Ching-Tien

2009-01-01

This study assessed whether two persons with profound multiple disabilities would be able to control environmental stimulation using hand swing and a standard mouse with a newly developed mouse driver (i.e. a new mouse driver replaces standard mouse driver, and turns a mouse into a precise two-dimensional motion detector). The study was performed…

Multimodality approach to classifying hand utilization for the clinical breast examination.

PubMed

Laufer, Shlomi; Cohen, Elaine R; Maag, Anne-Lise D; Kwan, Calvin; Vanveen, Barry; Pugh, Carla M

2014-01-01

The clinical breast examination (CBE) is performed to detect breast pathology. However, little is known regarding clinical technique and how it relates to diagnostic accuracy. We sought to quantify breast examination search patterns and hand utilization with a new data collection and analysis system. Participants performed the CBE while the sensor mapping and video camera system collected performance data. From this data, algorithms were developed that measured the number of hands used during the exam and active examination time. This system is a feasible and reliable method to collect new information on CBE techniques.

Scalable sensing electronics towards a motion capture suit

NASA Astrophysics Data System (ADS)

Xu, Daniel; Gisby, Todd A.; Xie, Shane; Anderson, Iain A.

2013-04-01

Being able to accurately record body motion allows complex movements to be characterised and studied. This is especially important in the film or sport coaching industry. Unfortunately, the human body has over 600 skeletal muscles, giving rise to multiple degrees of freedom. In order to accurately capture motion such as hand gestures, elbow or knee flexion and extension, vast numbers of sensors are required. Dielectric elastomer (DE) sensors are an emerging class of electroactive polymer (EAP) that is soft, lightweight and compliant. These characteristics are ideal for a motion capture suit. One challenge is to design sensing electronics that can simultaneously measure multiple sensors. This paper describes a scalable capacitive sensing device that can measure up to 8 different sensors with an update rate of 20Hz.

Computer vision-based classification of hand grip variations in neurorehabilitation.

PubMed

Zariffa, José; Steeves, John D

2011-01-01

The complexity of hand function is such that most existing upper limb rehabilitation robotic devices use only simplified hand interfaces. This is in contrast to the importance of the hand in regaining function after neurological injury. Computer vision technology has been used to identify hand posture in the field of Human Computer Interaction, but this approach has not been translated to the rehabilitation context. We describe a computer vision-based classifier that can be used to discriminate rehabilitation-relevant hand postures, and could be integrated into a virtual reality-based upper limb rehabilitation system. The proposed system was tested on a set of video recordings from able-bodied individuals performing cylindrical grasps, lateral key grips, and tip-to-tip pinches. The overall classification success rate was 91.2%, and was above 98% for 6 out of the 10 subjects. © 2011 IEEE

Hand rehabilitation after stroke using a wearable, high DOF, spring powered exoskeleton.

PubMed

Tianyao Chen; Lum, Peter S

2016-08-01

Stroke patients often have inappropriate finger flexor activation and finger extensor weakness, which makes it difficult to open their affected hand for functional grasp. The goal was to develop a passive, lightweight, wearable device to enable improved hand function during performance of activities of daily living. The device, HandSOME II, assists with opening the patient's hand using 11 elastic actuators that apply extension torques to finger and thumb joints. Device design and initial testing are described. A novel mechanical design applies forces orthogonal to the finger segments despite the fact that all of the device DOFs are not aligned with human joint DOF. In initial testing with seven stroke subjects with impaired hand function, use of HandSOME II significantly increased maximum extension angles and range of motion in all of the index finger joints (P<;0.05). HandSOME II allows performance of all the grip patterns used in daily activities and can be used as part of home-based therapy programs.

Reduction of motion artifact in pulse oximetry by smoothed pseudo Wigner-Ville distribution

PubMed Central

Yan, Yong-sheng; Poon, Carmen CY; Zhang, Yuan-ting

2005-01-01

Background The pulse oximeter, a medical device capable of measuring blood oxygen saturation (SpO2), has been shown to be a valuable device for monitoring patients in critical conditions. In order to incorporate the technique into a wearable device which can be used in ambulatory settings, the influence of motion artifacts on the estimated SpO2 must be reduced. This study investigates the use of the smoothed psuedo Wigner-Ville distribution (SPWVD) for the reduction of motion artifacts affecting pulse oximetry. Methods The SPWVD approach is compared with two techniques currently used in this field, i.e. the weighted moving average (WMA) and the fast Fourier transform (FFT) approaches. SpO2 and pulse rate were estimated from a photoplethysmographic (PPG) signal recorded when subject is in a resting position as well as in the act of performing four types of motions: horizontal and vertical movements of the hand, and bending and pressing motions of the finger. For each condition, 24 sets of PPG signals collected from 6 subjects, each of 30 seconds, were studied with reference to the PPG signal recorded simultaneously from the subject's other hand, which was stationary at all times. Results and Discussion The SPWVD approach shows significant improvement (p < 0.05), as compared to traditional approaches, when subjects bend their finger or press their finger against the sensor. In addition, the SPWVD approach also reduces the mean absolute pulse rate error significantly (p < 0.05) from 16.4 bpm and 11.2 bpm for the WMA and FFT approaches, respectively, to 5.62 bpm. Conclusion The results suggested that the SPWVD approach could potentially be used to reduce motion artifact on wearable pulse oximeters. PMID:15737241

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis

PubMed Central

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-01-01

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques. PMID:27589760

Through Wall Radar Classification of Human Micro-Doppler Using Singular Value Decomposition Analysis.

PubMed

Ritchie, Matthew; Ash, Matthew; Chen, Qingchao; Chetty, Kevin

2016-08-31

The ability to detect the presence as well as classify the activities of individuals behind visually obscuring structures is of significant benefit to police, security and emergency services in many situations. This paper presents the analysis from a series of experimental results generated using a through-the-wall (TTW) Frequency Modulated Continuous Wave (FMCW) C-Band radar system named Soprano. The objective of this analysis was to classify whether an individual was carrying an item in both hands or not using micro-Doppler information from a FMCW sensor. The radar was deployed at a standoff distance, of approximately 0.5 m, outside a residential building and used to detect multiple people walking within a room. Through the application of digital filtering, it was shown that significant suppression of the primary wall reflection is possible, significantly enhancing the target signal to clutter ratio. Singular Value Decomposition (SVD) signal processing techniques were then applied to the micro-Doppler signatures from different individuals. Features from the SVD information have been used to classify whether the person was carrying an item or walking free handed. Excellent performance of the classifier was achieved in this challenging scenario with accuracies up to 94%, suggesting that future through wall radar sensors may have the ability to reliably recognize many different types of activities in TTW scenarios using these techniques.

Bifurcation theory applied to aircraft motions

NASA Technical Reports Server (NTRS)

Hui, W. H.; Tobak, M.

1985-01-01

Bifurcation theory is used to analyze the nonlinear dynamic stability characteristics of single-degree-of-freedom motions of an aircraft or a flap about a trim position. The bifurcation theory analysis reveals that when the bifurcation parameter, e.g., the angle of attack, is increased beyond a critical value at which the aerodynamic damping vanishes, a new solution representing finite-amplitude periodic motion bifurcates from the previously stable steady motion. The sign of a simple criterion, cast in terms of aerodynamic properties, determines whether the bifurcating solution is stable (supercritical) or unstable (subcritical). For the pitching motion of a flap-plate airfoil flying at supersonic/hypersonic speed, and for oscillation of a flap at transonic speed, the bifurcation is subcritical, implying either that exchanges of stability between steady and periodic motion are accompanied by hysteresis phenomena, or that potentially large aperiodic departures from steady motion may develop. On the other hand, for the rolling oscillation of a slender delta wing in subsonic flight (wing rock), the bifurcation is found to be supercritical. This and the predicted amplitude of the bifurcation periodic motion are in good agreement with experiments.

Bifurcation theory applied to aircraft motions

NASA Technical Reports Server (NTRS)

Hui, W. H.; Tobak, M.

1985-01-01

The bifurcation theory is used to analyze the nonlinear dynamic stability characteristics of single-degree-of-freedom motions of an aircraft or a flap about a trim position. The bifurcation theory analysis reveals that when the bifurcation parameter, e.g., the angle of attack, is increased beyond a critical value at which the aerodynamic damping vanishes, a new solution representing finite-amplitude periodic motion bifurcates from the previously stable steady motion. The sign of a simple criterion, cast in terms of aerodynamic properties, determines whether the bifurcating solution is stable (supercritical) or unstable (critical). For the pitching motion of a flap-plate airfoil flying at supersonic/hypersonic speed, and for oscillation of a flap at transonic speed, the bifurcation is subcritical, implying either that exchanges of stability between steady and periodic motion are accompanied by hysteresis phenomena, or that potentially large aperiodic departures from steady motion may develop. On the other hand, for the rolling oscillation of a slender delta wing in subsonic flight (wing rock), the bifurcation is found to be supercritical. This and the predicted amplitude of the bifurcation periodic motion are in good agreement with the experiments.

Analysis of relative displacement between the HX wearable robotic exoskeleton and the user's hand.

PubMed

Cempini, Marco; Marzegan, Alberto; Rabuffetti, Marco; Cortese, Mario; Vitiello, Nicola; Ferrarin, Maurizio

2014-10-18

Advances in technology are allowing for the production of several viable wearable robotic devices to assist with activities of daily living and with rehabilitation. One of the most pressing limitations to user satisfaction is the lack of consistency in motion between the user and the robotic device. The displacement between the robot and the body segment may not correspond because of differences in skin and tissue compliance, mechanical backlash, and/or incorrect fit. This report presents the results of an analysis of relative displacement between the user's hand and a wearable exoskeleton, the HX. HX has been designed to maximize comfort, wearability and user safety, exploiting chains with multiple degrees-of-freedom with a modular architecture. These appealing features may introduce several uncertainties in the kinematic performances, especially when considering the anthropometry, morphology and degree of mobility of the human hand. The small relative displacements between the hand and the exoskeleton were measured with a video-based motion capture system, while the user executed several different grips in different exoskeleton modes. The analysis furnished quantitative results about the device performance, differentiated among device modules and test conditions. In general, the global relative displacement for the distal part of the device was in the range 0.5-1.5 mm, while within 3 mm (worse but still acceptable) for displacements nearest to the hand dorsum. Conclusions over the HX design principles have been drawn, as well as guidelines for future developments.

Investigation of hand capabilities under a variety of performance conditions and an attempt to explain performance differences

NASA Technical Reports Server (NTRS)

Bishu, Ram R.; Bronkema, Lisa

1993-01-01

Human capabilities such as dexterity, manipulability, and tactile perception are unique and render the hands as a very versatile, effective and a multipurpose tool. This is especially true for environments such as the EVA environment. However, with the use of the protective EVA gloves, there is much evidence to suggest that human performance decreases. In order to determine the nature and cause of this performance decrement, several performance tests were run which studied the effects of gloves on strength, tactile feedback, and range of motion. Tactile sensitivity was measured as a function of grip strength, and the results are discussed. Equipment which was developed to measure finger range of motion along with corresponding finger strength values is discussed. The results of these studies have useful implications for improved glove design.

Human Classification Based on Gestural Motions by Using Components of PCA

NASA Astrophysics Data System (ADS)

Aziz, Azri A.; Wan, Khairunizam; Za'aba, S. K.; B, Shahriman A.; Adnan, Nazrul H.; H, Asyekin; R, Zuradzman M.

2013-12-01

Lately, a study of human capabilities with the aim to be integrated into machine is the famous topic to be discussed. Moreover, human are bless with special abilities that they can hear, see, sense, speak, think and understand each other. Giving such abilities to machine for improvement of human life is researcher's aim for better quality of life in the future. This research was concentrating on human gesture, specifically arm motions for differencing the individuality which lead to the development of the hand gesture database. We try to differentiate the human physical characteristic based on hand gesture represented by arm trajectories. Subjects are selected from different type of the body sizes, and then acquired data undergo resampling process. The results discuss the classification of human based on arm trajectories by using Principle Component Analysis (PCA).

Information Transfer Capacity of Articulators in American Sign Language.

PubMed

Malaia, Evie; Borneman, Joshua D; Wilbur, Ronnie B

2018-03-01

The ability to convey information is a fundamental property of communicative signals. For sign languages, which are overtly produced with multiple, completely visible articulators, the question arises as to how the various channels co-ordinate and interact with each other. We analyze motion capture data of American Sign Language (ASL) narratives, and show that the capacity of information throughput, mathematically defined, is highest on the dominant hand (DH). We further demonstrate that information transfer capacity is also significant for the non-dominant hand (NDH), and the head channel too, as compared to control channels (ankles). We discuss both redundancy and independence in articulator motion in sign language, and argue that the NDH and the head articulators contribute to the overall information transfer capacity, indicating that they are neither completely redundant to, nor completely independent of, the DH.

Risks of musculoskeletal disorders among betel quid preparers in Taiwan.

PubMed

Chang, Jer-Hao; Wu, Jyun-De; Chen, Chih-Yong; Sumd, Shih-Bin; Yin, Hsin-I; Hsu, Der-Jen

2014-04-01

Betel quid chewing is common in Taiwan. The work of betel quid preparers is characterized by long hours of static work, awkward working posture and highly repetitive hand/wrist motion. However, the musculoskeletal health of betel quid preparers receives very little attention. The Chinese version of the Standardized Nordic Musculoskeletal Questionnaire (NMQ) was administered, and electrogoniometers and electromyography were used in this cross-sectional study to characterize the hand/wrist motion of the subjects. Physical examinations on the thumbs and wrists of the subjects were conducted by means of Phalen's test and Finkelstein's test, respectively. Among the 225 participants, more than 95% attributed their musculoskeletal complaints to their work, and shoulder, neck, hand/wrist, and lower back discomfort were most frequently reported. More than 70% of the preparers did not seek medical treatment for their musculoskeletal problems. Based on the physical examination, 24% of the participants had suspected symptom of either carpal tunnel syndrome (CTS) or DeQuervain's tenosynovitis. The instrumental measurements indicated that betel quid preparation is characterized by extreme angle ranges and moderate repetition of wrist motion as well as low forceful exertion. This study concludes that betel quid preparers are a high risk group of developing musculoskeletal disorders (MSDs). Future studies by electrogoniometers and detailed physical examination on betel quid preparers are needed to determine the predisposing factors for CTS. Some intervention measures to prevent MSDs and to lessen psychological stress for this group of workers are strongly suggested. © 2014 Wiley Periodicals, Inc.

Domain wall motion in ferroelectrics: Barkhausen noise

NASA Astrophysics Data System (ADS)

Shur, V.; Rumyantsev, E.; Kozhevnikov, V.; Nikolaeva, E.; Shishkin, E.

2002-03-01

The switching current noise has been recorded during polarization reversal in single-crystalline gadolinium molybdate (GMO) and lithium tantalate (LT). Analysis of Barkhausen noise (BN) data allows to classify the noise types by determination of the critical indexes and fractal dimensions. BN is manifested as the short pulses during the polarization reversal. We have analyzed the BN data recorded in GMO and LT with various types of controlled domain structure. The data treatment in terms of probability distribution of duration, area and energy of individual pulses reveals the critical behavior typical for the fractal records in time. We used the Fourier transform and Hurst's rescaled range analysis for obtaining the Hurst factor, fractal dimension and classifying the noise types. We investigated by computer simulation the mechanism of sideways motion of 180O domain wall by nucleation at the wall taking into account the nuclei-nuclei interaction. It was shown that the moving domain walls display the fractal shape and their motion is accompanied by Flicker noise, which is in accord with experimental data. The research was made possible in part by Programs "Basic Research in Russian Universities" and "Priority Research in High School. Electronics", by Grant No. 01-02-17443 of RFBR, by Award No.REC-005 of CRDF.

Task-oriented training with computer gaming in people with rheumatoid arthritisor osteoarthritis of the hand: study protocol of a randomized controlled pilot trial.

PubMed

Srikesavan, Cynthia Swarnalatha; Shay, Barbara; Robinson, David B; Szturm, Tony

2013-03-09

Significant restriction in the ability to participate in home, work and community life results from pain, fatigue, joint damage, stiffness and reduced joint range of motion and muscle strength in people with rheumatoid arthritis or osteoarthritis of the hand. With modest evidence on the therapeutic effectiveness of conventional hand exercises, a task-oriented training program via real life object manipulations has been developed for people with arthritis. An innovative, computer-based gaming platform that allows a broad range of common objects to be seamlessly transformed into therapeutic input devices through instrumentation with a motion-sense mouse has also been designed. Personalized objects are selected to target specific training goals such as graded finger mobility, strength, endurance or fine/gross dexterous functions. The movements and object manipulation tasks that replicate common situations in everyday living will then be used to control and play any computer game, making practice challenging and engaging. The ongoing study is a 6-week, single-center, parallel-group, equally allocated and assessor-blinded pilot randomized controlled trial. Thirty people with rheumatoid arthritis or osteoarthritis affecting the hand will be randomized to receive either conventional hand exercises or the task-oriented training. The purpose is to determine a preliminary estimation of therapeutic effectiveness and feasibility of the task-oriented training program. Performance based and self-reported hand function, and exercise compliance are the study outcomes. Changes in outcomes (pre to post intervention) within each group will be assessed by paired Student t test or Wilcoxon signed-rank test and between groups (control versus experimental) post intervention using unpaired Student t test or Mann-Whitney U test. The study findings will inform decisions on the feasibility, safety and completion rate and will also provide preliminary data on the treatment effects of the task-oriented training compared with conventional hand exercises in people with rheumatoid arthritis or osteoarthritis of the hand. ClinicalTrials.gov: NCT01635582.

Design of rehabilitation robot hand for fingers CPM training

NASA Astrophysics Data System (ADS)

Zhou, Hongfu; Chan, T. W.; Tong, K. Y.; Kwong, K. K.; Yao, Xifan

2008-10-01

This paper presents a low-cost prototype for rehabilitation robot aide patient do hands CPM (continuous passive motion) training. The design of the prototype is based on the principle of Rutgers Master II glove, but it is better in performance for more improvement made. In the design, it uses linear motors to replace pneumatic actuators to make the product more portable and mobile. It increases finger training range to 180 degree for the full range training of hand finger holding and extension. Also the prototype can not only be wearing on palm and fore arm do training for face to face with finger move together, but also be put in the opposite hand glove wear direction for hand rehabilitation training. During the research, Solidworks is used as the tool for mechanical design and movement simulation. It proved through experiment that the prototype made in the research is appropriate for hand do CPM training.

Foot-mounted inertial measurement unit for activity classification.

PubMed

Ghobadi, Mostafa; Esfahani, Ehsan T

2014-01-01

This paper proposes a classification technique for daily base activity recognition for human monitoring during physical therapy in home. The proposed method estimates the foot motion using single inertial measurement unit, then segments the motion into steps classify them by template-matching as walking, stairs up or stairs down steps. The results show a high accuracy of activity recognition. Unlike previous works which are limited to activity recognition, the proposed approach is more qualitative by providing similarity index of any activity to its desired template which can be used to assess subjects improvement.

Real-Time Hand Posture Recognition Using a Range Camera

NASA Astrophysics Data System (ADS)

Lahamy, Herve

The basic goal of human computer interaction is to improve the interaction between users and computers by making computers more usable and receptive to the user's needs. Within this context, the use of hand postures in replacement of traditional devices such as keyboards, mice and joysticks is being explored by many researchers. The goal is to interpret human postures via mathematical algorithms. Hand posture recognition has gained popularity in recent years, and could become the future tool for humans to interact with computers or virtual environments. An exhaustive description of the frequently used methods available in literature for hand posture recognition is provided. It focuses on the different types of sensors and data used, the segmentation and tracking methods, the features used to represent the hand postures as well as the classifiers considered in the recognition process. Those methods are usually presented as highly robust with a recognition rate close to 100%. However, a couple of critical points necessary for a successful real-time hand posture recognition system require major improvement. Those points include the features used to represent the hand segment, the number of postures simultaneously recognizable, the invariance of the features with respect to rotation, translation and scale and also the behavior of the classifiers against non-perfect hand segments for example segments including part of the arm or missing part of the palm. A 3D time-of-flight camera named SR4000 has been chosen to develop a new methodology because of its capability to provide in real-time and at high frame rate 3D information on the scene imaged. This sensor has been described and evaluated for its capability for capturing in real-time a moving hand. A new recognition method that uses the 3D information provided by the range camera to recognize hand postures has been proposed. The different steps of this methodology including the segmentation, the tracking, the hand modeling and finally the recognition process have been described and evaluated extensively. In addition, the performance of this method has been analyzed against several existing hand posture recognition techniques found in literature. The proposed system is able to recognize with an overall recognition rate of 98% and in real-time 18 out the 33 postures of the American sign language alphabet. This recognition is translation, rotation and scale invariant.

Development and pilot testing of HEXORR: Hand EXOskeleton Rehabilitation Robot

PubMed Central

2010-01-01

Background Following acute therapeutic interventions, the majority of stroke survivors are left with a poorly functioning hemiparetic hand. Rehabilitation robotics has shown promise in providing patients with intensive therapy leading to functional gains. Because of the hand's crucial role in performing activities of daily living, attention to hand therapy has recently increased. Methods This paper introduces a newly developed Hand Exoskeleton Rehabilitation Robot (HEXORR). This device has been designed to provide full range of motion (ROM) for all of the hand's digits. The thumb actuator allows for variable thumb plane of motion to incorporate different degrees of extension/flexion and abduction/adduction. Compensation algorithms have been developed to improve the exoskeleton's backdrivability by counteracting gravity, stiction and kinetic friction. We have also designed a force assistance mode that provides extension assistance based on each individual's needs. A pilot study was conducted on 9 unimpaired and 5 chronic stroke subjects to investigate the device's ability to allow physiologically accurate hand movements throughout the full ROM. The study also tested the efficacy of the force assistance mode with the goal of increasing stroke subjects' active ROM while still requiring active extension torque on the part of the subject. Results For 12 of the hand digits'15 joints in neurologically normal subjects, there were no significant ROM differences (P > 0.05) between active movements performed inside and outside of HEXORR. Interjoint coordination was examined in the 1st and 3rd digits, and no differences were found between inside and outside of the device (P > 0.05). Stroke subjects were capable of performing free hand movements inside of the exoskeleton and the force assistance mode was successful in increasing active ROM by 43 ± 5% (P < 0.001) and 24 ± 6% (P = 0.041) for the fingers and thumb, respectively. Conclusions Our pilot study shows that this device is capable of moving the hand's digits through nearly the entire ROM with physiologically accurate trajectories. Stroke subjects received the device intervention well and device impedance was minimized so that subjects could freely extend and flex their digits inside of HEXORR. Our active force-assisted condition was successful in increasing the subjects' ROM while promoting active participation. PMID:20667083

Context effects on smooth pursuit and manual interception of a disappearing target.

PubMed

Kreyenmeier, Philipp; Fooken, Jolande; Spering, Miriam

2017-07-01

In our natural environment, we interact with moving objects that are surrounded by richly textured, dynamic visual contexts. Yet most laboratory studies on vision and movement show visual objects in front of uniform gray backgrounds. Context effects on eye movements have been widely studied, but it is less well known how visual contexts affect hand movements. Here we ask whether eye and hand movements integrate motion signals from target and context similarly or differently, and whether context effects on eye and hand change over time. We developed a track-intercept task requiring participants to track the initial launch of a moving object ("ball") with smooth pursuit eye movements. The ball disappeared after a brief presentation, and participants had to intercept it in a designated "hit zone." In two experiments ( n = 18 human observers each), the ball was shown in front of a uniform or a textured background that either was stationary or moved along with the target. Eye and hand movement latencies and speeds were similarly affected by the visual context, but eye and hand interception (eye position at time of interception, and hand interception timing error) did not differ significantly between context conditions. Eye and hand interception timing errors were strongly correlated on a trial-by-trial basis across all context conditions, highlighting the close relation between these responses in manual interception tasks. Our results indicate that visual contexts similarly affect eye and hand movements but that these effects may be short-lasting, affecting movement trajectories more than movement end points. NEW & NOTEWORTHY In a novel track-intercept paradigm, human observers tracked a briefly shown object moving across a textured, dynamic context and intercepted it with their finger after it had disappeared. Context motion significantly affected eye and hand movement latency and speed, but not interception accuracy; eye and hand position at interception were correlated on a trial-by-trial basis. Visual context effects may be short-lasting, affecting movement trajectories more than movement end points. Copyright © 2017 the American Physiological Society.

Interactive Explanations: The Functional Role of Gestural and Bodily Action for Explaining and Learning Scientific Concepts in Face-to-Face Arrangements

ERIC Educational Resources Information Center

Scopelitis, Stephanie A.

2013-01-01

As human beings, we live "in", live "with", and live "through" our bodies. And because of this it is no wonder that our hands and bodies are in motion as we interact with others in our world. Hands and body move as we give directions to another, anticipate which way to turn the screwdriver, and direct our friend to…

Binocular Vision-Based Position and Pose of Hand Detection and Tracking in Space

NASA Astrophysics Data System (ADS)

Jun, Chen; Wenjun, Hou; Qing, Sheng

After the study of image segmentation, CamShift target tracking algorithm and stereo vision model of space, an improved algorithm based of Frames Difference and a new space point positioning model were proposed, a binocular visual motion tracking system was constructed to verify the improved algorithm and the new model. The problem of the spatial location and pose of the hand detection and tracking have been solved.

Object instance recognition using motion cues and instance specific appearance models

NASA Astrophysics Data System (ADS)

Schumann, Arne

2014-03-01

In this paper we present an object instance retrieval approach. The baseline approach consists of a pool of image features which are computed on the bounding boxes of a query object track and compared to a database of tracks in order to find additional appearances of the same object instance. We improve over this simple baseline approach in multiple ways: 1) we include motion cues to achieve improved robustness to viewpoint and rotation changes, 2) we include operator feedback to iteratively re-rank the resulting retrieval lists and 3) we use operator feedback and location constraints to train classifiers and learn an instance specific appearance model. We use these classifiers to further improve the retrieval results. The approach is evaluated on two popular public datasets for two different applications. We evaluate person re-identification on the CAVIAR shopping mall surveillance dataset and vehicle instance recognition on the VIVID aerial dataset and achieve significant improvements over our baseline results.

Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

PubMed Central

Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

2015-01-01

This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

Critical role of foreground stimuli in perceiving visually induced self-motion (vection).

PubMed

Nakamura, S; Shimojo, S

1999-01-01

The effects of a foreground stimulus on vection (illusory perception of self-motion induced by a moving background stimulus) were examined in two experiments. The experiments reveal that the presentation of a foreground pattern with a moving background stimulus may affect vection. The foreground stimulus facilitated vection strength when it remained stationary or moved slowly in the opposite direction to that of the background stimulus. On the other hand, there was a strong inhibition of vection when the foreground stimulus moved slowly with, or quickly against, the background. These results suggest that foreground stimuli, as well as background stimuli, play an important role in perceiving self-motion.

Initial assessment of facial nerve paralysis based on motion analysis using an optical flow method.

PubMed

Samsudin, Wan Syahirah W; Sundaraj, Kenneth; Ahmad, Amirozi; Salleh, Hasriah

2016-01-01

An initial assessment method that can classify as well as categorize the severity of paralysis into one of six levels according to the House-Brackmann (HB) system based on facial landmarks motion using an Optical Flow (OF) algorithm is proposed. The desired landmarks were obtained from the video recordings of 5 normal and 3 Bell's Palsy subjects and tracked using the Kanade-Lucas-Tomasi (KLT) method. A new scoring system based on the motion analysis using area measurement is proposed. This scoring system uses the individual scores from the facial exercises and grades the paralysis based on the HB system. The proposed method has obtained promising results and may play a pivotal role towards improved rehabilitation programs for patients.

Hand-writing motion tracking with vision-inertial sensor fusion: calibration and error correction.

PubMed

Zhou, Shengli; Fei, Fei; Zhang, Guanglie; Liu, Yunhui; Li, Wen J

2014-08-25

The purpose of this study was to improve the accuracy of real-time ego-motion tracking through inertial sensor and vision sensor fusion. Due to low sampling rates supported by web-based vision sensor and accumulation of errors in inertial sensors, ego-motion tracking with vision sensors is commonly afflicted by slow updating rates, while motion tracking with inertial sensor suffers from rapid deterioration in accuracy with time. This paper starts with a discussion of developed algorithms for calibrating two relative rotations of the system using only one reference image. Next, stochastic noises associated with the inertial sensor are identified using Allan Variance analysis, and modeled according to their characteristics. Finally, the proposed models are incorporated into an extended Kalman filter for inertial sensor and vision sensor fusion. Compared with results from conventional sensor fusion models, we have shown that ego-motion tracking can be greatly enhanced using the proposed error correction model.

Validation of enhanced kinect sensor based motion capturing for gait assessment

PubMed Central

Müller, Björn; Ilg, Winfried; Giese, Martin A.

2017-01-01

Optical motion capturing systems are expensive and require substantial dedicated space to be set up. On the other hand, they provide unsurpassed accuracy and reliability. In many situations however flexibility is required and the motion capturing system can only temporarily be placed. The Microsoft Kinect v2 sensor is comparatively cheap and with respect to gait analysis promising results have been published. We here present a motion capturing system that is easy to set up, flexible with respect to the sensor locations and delivers high accuracy in gait parameters comparable to a gold standard motion capturing system (VICON). Further, we demonstrate that sensor setups which track the person only from one-side are less accurate and should be replaced by two-sided setups. With respect to commonly analyzed gait parameters, especially step width, our system shows higher agreement with the VICON system than previous reports. PMID:28410413

Dynamic motion analysis of dart throwers motion visualized through computerized tomography and calculation of the axis of rotation.

PubMed

Edirisinghe, Y; Troupis, J M; Patel, M; Smith, J; Crossett, M

2014-05-01

We used a dynamic three-dimensional (3D) mapping method to model the wrist in dynamic unrestricted dart throwers motion in three men and four women. With the aid of precision landmark identification, a 3D coordinate system was applied to the distal radius and the movement of the carpus was described. Subsequently, with dynamic 3D reconstructions and freedom to position the camera viewpoint anywhere in space, we observed the motion pathways of all carpal bones in dart throwers motion and calculated its axis of rotation. This was calculated to lie in 27° of anteversion from the coronal plane and 44° of varus angulation relative to the transverse plane. This technique is a safe and a feasible carpal imaging method to gain key information for decision making in future hand surgical and rehabilitative practices.

Control of joint motion simulators for biomechanical research

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1992-01-01

The authors present a hierarchical adaptive algorithm for controlling upper extremity human joint motion simulators. A joint motion simulator is a computer-controlled, electromechanical system which permits the application of forces to the tendons of a human cadaver specimen in such a way that the cadaver joint under study achieves a desired motion in a physiologic manner. The proposed control scheme does not require knowledge of the cadaver specimen dynamic model, and solves on-line the indeterminate problem which arises because human joints typically possess more actuators than degrees of freedom. Computer simulation results are given for an elbow/forearm system and wrist/hand system under hierarchical control. The results demonstrate that any desired normal joint motion can be accurately tracked with the proposed algorithm. These simulation results indicate that the controller resolved the indeterminate problem redundancy in a physiologic manner, and show that the control scheme was robust to parameter uncertainty and to sensor noise.

REVIEWS OF TOPICAL PROBLEMS: Motion of particles and photons in the gravitational field of a rotating body (In memory of Vladimir Afanas'evich Ruban)

NASA Astrophysics Data System (ADS)

Dymnikova, I. G.

1986-03-01

A study is made of the trajectories of free motion of test particles and photons in the Kerr metric, which describes the gravitational field of a rotating massive body. The trajectories are classified on the basis of the integrals of the motion, which have a clear physical meaning. The cases of a strong gravitational field in the neighborhood of a rotating black hole as well as the weak-field approximation describing the motion of particles in the gravitational field of a rotating star or galaxy are considered. The review includes bound states (orbits) in the field of a rotating mass, scattering and gravitational capture of particles and photons by a rotating black hole, trajectories of falling into a black hole, and the bending of light rays and the gravitational time delay of signals in the gravitational field of a rotating body.

Learning Kinematic Constraints in Laparoscopic Surgery

PubMed Central

Huang, Felix C.; Mussa-Ivaldi, Ferdinando A.; Pugh, Carla M.; Patton, James L.

2012-01-01

To better understand how kinematic variables impact learning in surgical training, we devised an interactive environment for simulated laparoscopic maneuvers, using either 1) mechanical constraints typical of a surgical “box-trainer” or 2) virtual constraints in which free hand movements control virtual tool motion. During training, the virtual tool responded to the absolute position in space (Position-Based) or the orientation (Orientation-Based) of a hand-held sensor. Volunteers were further assigned to different sequences of target distances (Near-Far-Near or Far-Near-Far). Training with the Orientation-Based constraint enabled much lower path error and shorter movement times during training, which suggests that tool motion that simply mirrors joint motion is easier to learn. When evaluated in physically constrained (physical box-trainer) conditions, each group exhibited improved performance from training. However, Position-Based training enabled greater reductions in movement error relative to Orientation-Based (mean difference: 14.0 percent; CI: 0.7, 28.6). Furthermore, the Near-Far-Near schedule allowed a greater decrease in task time relative to the Far-Near-Far sequence (mean −13:5 percent, CI: −19:5, −7:5). Training that focused on shallow tool insertion (near targets) might promote more efficient movement strategies by emphasizing the curvature of tool motion. In addition, our findings suggest that an understanding of absolute tool position is critical to coping with mechanical interactions between the tool and trocar. PMID:23293709

Evaluation of performance, acceptance, and compliance of an auto-injector in healthy and rheumatoid arthritic subjects measured by a motion capture system.

PubMed

Xiao, Xiao; Li, Wei; Clawson, Corbin; Karvani, David; Sondag, Perceval; Hahn, James K

2018-01-01

The study aimed to develop a motion capture system that can track, visualize, and analyze the entire performance of self-injection with the auto-injector. Each of nine healthy subjects and 29 rheumatoid arthritic (RA) patients with different degrees of hand disability performed two simulated injections into an injection pad while six degrees of freedom (DOF) motions of the auto-injector and the injection pad were captured. We quantitatively measured the performance of the injection by calculating needle displacement from the motion trajectories. The max, mean, and SD of needle displacement were analyzed. Assessments of device acceptance and usability were evaluated by a survey questionnaire and independent observations of compliance with the device instruction for use (IFU). A total of 80 simulated injections were performed. Our results showed a similar level of performance among all the subjects with slightly larger, but not statistically significant, needle displacement in the RA group. In particular, no significant effects regarding previous experience in self-injection, grip method, pain in hand, and Cochin score in the RA group were found to have an impact on the mean needle displacement. Moreover, the analysis of needle displacement for different durations of injections indicated that most of the subjects reached their personal maximum displacement in 15 seconds and remained steady or exhibited a small amount of increase from 15 to 60 seconds. Device acceptance was high for most of the questions (ie, >4; >80%) based on a 0-5-point scale or percentage of acceptance. The overall compliance with the device IFU was high for the first injection (96.05%) and reached 98.02% for the second injection. We demonstrated the feasibility of tracking the motions of injection to measure the performance of simulated self-injection. The comparisons of needle displacement showed that even RA patients with severe hand disability could properly perform self-injection with this auto-injector at a similar level with the healthy subjects. Finally, the observed high device acceptance and compliance with device IFU suggest that the system is convenient and easy to use.

Outcomes of Silicone Arthroplasty Stratified by Fingers for the Rheumatoid Metacarpophalangeal Joints

PubMed Central

Chung, Kevin C.; Kotsis, Sandra V.; Shaw Wilgis, E. F.; Fox, David A.; Regan, Marian; Kim, H. Myra; Burke, Frank D.

2015-01-01

Purpose Previous studies have demonstrated that outcomes for the ulnar digits appear to be worse than the radial digits after silicone metacarpophalangeal joint arthroplasty (SMPA) for the rheumatoid hand. This study examines various components of hand deformities in an effort to understand SMPA outcomes in terms of metacarpophalangeal joint range of motion and alignment. We hypothesize that the ulnar fingers will have less improvement marked by greater ulnar drift, extension lag, and less metacarpophalangeal joint (MCPJ) arc of motion than the radial fingers. Methods 68 surgical patients were recruited from 3 sites in this multi-center international prospective cohort study. All patients had a diagnosis of rheumatoid arthritis, were between the ages of 18–80, and were eligible to undergo SMPA based on measured hand deformities (extensor lag and ulnar drift). Ulnar drift, extension lag, and arc of motion for the MCPJ of each finger were measured at baseline (pre-surgical) and 1-year after SMPA. Results All fingers showed an improvement in ulnar drift from baseline to 1-year after surgery. The smallest improvement was in the index finger (12°) and the largest improvement was in the little finger (30°). Similarly, the largest improvement in extension lag was seen in the little finger (47°) and the smallest improvement was seen in the index finger (21°). In terms of MCPJ arc of motion, all fingers moved to a more extended posture and gained an improved arc of motion, but the biggest improvement was observed in the 2 ulnar fingers and less so in the 2 radial fingers. Conclusions Our hypothesis that the ulnar fingers will have worse outcomes than the radial fingers is not proven by this study. Although past experiences have indicated that it is more difficult to maintain posture for the ring and little fingers after SMPA due to the deforming forces, sufficient correction of the deformities in the ulnar fingers is possible, if attention to adequate bone resection and realigning of the extensor mechanism are carefully performed during the procedure. PMID:19896008

Using postural synergies to animate a low-dimensional hand avatar in haptic simulation.

PubMed

Mulatto, Sara; Formaglio, Alessandro; Malvezzi, Monica; Prattichizzo, Domenico

2013-01-01

A technique to animate a realistic hand avatar with 20 DoFs based on the biomechanics of the human hand is presented. The animation does not use any sensor glove or advanced tracker with markers. The proposed approach is based on the knowledge of a set of kinematic constraints on the model of the hand, referred to as postural synergies, which allows to represent the hand posture using a number of variables lower than the number of joints of the hand model. This low-dimensional set of parameters is estimated from direct measurement of the motion of thumb and index finger tracked using two haptic devices. A kinematic inversion algorithm has been developed, which takes synergies into account and estimates the kinematic configuration of the whole hand, i.e., also of the fingers whose end tips are not directly tracked by the two haptic devices. The hand skin is deformable and its deformation is computed using a linear vertex blending technique. The proposed synergy-based animation of the hand avatar involves only algebraic computations and is suitable for real-time implementation as required in haptics.

MIM: Math in Motion for K-2

ERIC Educational Resources Information Center

Chevalier, Cheryl; Pippen, Mary H.; Stevens, Dorothy

2008-01-01

The authors describe a hands-on program that they developed after their attendance at the NCTM Algebra Academy. The article explains how to use literature to capture youngsters' attention and engage them in interactive mathematical activities.

Motion cues that make an impression: Predicting perceived personality by minimal motion information.

PubMed

Koppensteiner, Markus

2013-11-01

The current study presents a methodology to analyze first impressions on the basis of minimal motion information. In order to test the applicability of the approach brief silent video clips of 40 speakers were presented to independent observers (i.e., did not know speakers) who rated them on measures of the Big Five personality traits. The body movements of the speakers were then captured by placing landmarks on the speakers' forehead, one shoulder and the hands. Analysis revealed that observers ascribe extraversion to variations in the speakers' overall activity, emotional stability to the movements' relative velocity, and variation in motion direction to openness. Although ratings of openness and conscientiousness were related to biographical data of the speakers (i.e., measures of career progress), measures of body motion failed to provide similar results. In conclusion, analysis of motion behavior might be done on the basis of a small set of landmarks that seem to capture important parts of relevant nonverbal information.

On the local standard of rest. [comoving with young objects in gravitational field of spiral galaxies

NASA Technical Reports Server (NTRS)

Yuan, C.

1983-01-01

Under the influence of a spiral gravitational field, there should be differences among the mean motions of different types of objects with different dispersion velocities in a spiral galaxy. The old stars with high dispersion velocity should have essentially no mean motion normal to the galactic rotation. On the other hand, young objects and interstellar gas may be moving relative to the old stars at a velocity of a few kilometer per second in both the radial (galacto-centric), and circular directions, depending on the spiral model adopted. Such a velocity is usually referred as the systematic motion or the streaming motion. The conventionally adopted local standard of rest is indeed co-moving with the young objects of the solar vicinity. Therefore, it has a net systematic motion with respect to the circular motion of an equilibrium galactic model, defined by the old stars. Previously announced in STAR as N83-24443

Neural Extrapolation of Motion for a Ball Rolling Down an Inclined Plane

PubMed Central

La Scaleia, Barbara; Lacquaniti, Francesco; Zago, Myrka

2014-01-01

It is known that humans tend to misjudge the kinematics of a target rolling down an inclined plane. Because visuomotor responses are often more accurate and less prone to perceptual illusions than cognitive judgments, we asked the question of how rolling motion is extrapolated for manual interception or drawing tasks. In three experiments a ball rolled down an incline with kinematics that differed as a function of the starting position (4 different positions) and slope (30°, 45° or 60°). In Experiment 1, participants had to punch the ball as it fell off the incline. In Experiment 2, the ball rolled down the incline but was stopped at the end; participants were asked to imagine that the ball kept moving and to punch it. In Experiment 3, the ball rolled down the incline and was stopped at the end; participants were asked to draw with the hand in air the trajectory that would be described by the ball if it kept moving. We found that performance was most accurate when motion of the ball was visible until interception and haptic feedback of hand-ball contact was available (Experiment 1). However, even when participants punched an imaginary moving ball (Experiment 2) or drew in air the imaginary trajectory (Experiment 3), they were able to extrapolate to some extent global aspects of the target motion, including its path, speed and arrival time. We argue that the path and kinematics of a ball rolling down an incline can be extrapolated surprisingly well by the brain using both visual information and internal models of target motion. PMID:24940874

Neural extrapolation of motion for a ball rolling down an inclined plane.

PubMed

La Scaleia, Barbara; Lacquaniti, Francesco; Zago, Myrka

2014-01-01

It is known that humans tend to misjudge the kinematics of a target rolling down an inclined plane. Because visuomotor responses are often more accurate and less prone to perceptual illusions than cognitive judgments, we asked the question of how rolling motion is extrapolated for manual interception or drawing tasks. In three experiments a ball rolled down an incline with kinematics that differed as a function of the starting position (4 different positions) and slope (30°, 45° or 60°). In Experiment 1, participants had to punch the ball as it fell off the incline. In Experiment 2, the ball rolled down the incline but was stopped at the end; participants were asked to imagine that the ball kept moving and to punch it. In Experiment 3, the ball rolled down the incline and was stopped at the end; participants were asked to draw with the hand in air the trajectory that would be described by the ball if it kept moving. We found that performance was most accurate when motion of the ball was visible until interception and haptic feedback of hand-ball contact was available (Experiment 1). However, even when participants punched an imaginary moving ball (Experiment 2) or drew in air the imaginary trajectory (Experiment 3), they were able to extrapolate to some extent global aspects of the target motion, including its path, speed and arrival time. We argue that the path and kinematics of a ball rolling down an incline can be extrapolated surprisingly well by the brain using both visual information and internal models of target motion.

Development of a new assessment tool for cervical myelopathy using hand-tracking sensor: Part 1: validity and reliability.

PubMed

Alagha, M Abdulhadi; Alagha, Mahmoud A; Dunstan, Eleanor; Sperwer, Olaf; Timmins, Kate A; Boszczyk, Bronek M

2017-04-01

To assess the reliability and validity of a hand motion sensor, Leap Motion Controller (LMC), in the 15-s hand grip-and-release test, as compared against human inspection of an external digital camera recording. Fifty healthy participants were asked to fully grip-and-release their dominant hand as rapidly as possible for two trials with a 10-min rest in-between, while wearing a non-metal wrist splint. Each test lasted for 15 s, and a digital camera was used to film the anterolateral side of the hand on the first test. Three assessors counted the frequency of grip-and-release (G-R) cycles independently and in a blinded fashion. The average mean of the three was compared with that measured by LMC using the Bland-Altman method. Test-retest reliability was examined by comparing the two 15-s tests. The mean number of G-R cycles recorded was: 47.8 ± 6.4 (test 1, video observer); 47.7 ± 6.5 (test 1, LMC); and 50.2 ± 6.5 (test 2, LMC). Bland-Altman indicated good agreement, with a low bias (0.15 cycles) and narrow limits of agreement. The ICC showed high inter-rater agreement and the coefficient of repeatability for the number of cycles was ±5.393, with a mean bias of 3.63. LMC appears to be valid and reliable in the 15-s grip-and-release test. This serves as a first step towards the development of an objective myelopathy assessment device and platform for the assessment of neuromotor hand function in general. Further assessment in a clinical setting and to gauge healthy benchmark values is warranted.

Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

PubMed

Bai, Ou; Lin, Peter; Vorbach, Sherry; Li, Jiang; Furlani, Steve; Hallett, Mark

2007-12-01

To explore effective combinations of computational methods for the prediction of movement intention preceding the production of self-paced right and left hand movements from single trial scalp electroencephalogram (EEG). Twelve naïve subjects performed self-paced movements consisting of three key strokes with either hand. EEG was recorded from 128 channels. The exploration was performed offline on single trial EEG data. We proposed that a successful computational procedure for classification would consist of spatial filtering, temporal filtering, feature selection, and pattern classification. A systematic investigation was performed with combinations of spatial filtering using principal component analysis (PCA), independent component analysis (ICA), common spatial patterns analysis (CSP), and surface Laplacian derivation (SLD); temporal filtering using power spectral density estimation (PSD) and discrete wavelet transform (DWT); pattern classification using linear Mahalanobis distance classifier (LMD), quadratic Mahalanobis distance classifier (QMD), Bayesian classifier (BSC), multi-layer perceptron neural network (MLP), probabilistic neural network (PNN), and support vector machine (SVM). A robust multivariate feature selection strategy using a genetic algorithm was employed. The combinations of spatial filtering using ICA and SLD, temporal filtering using PSD and DWT, and classification methods using LMD, QMD, BSC and SVM provided higher performance than those of other combinations. Utilizing one of the better combinations of ICA, PSD and SVM, the discrimination accuracy was as high as 75%. Further feature analysis showed that beta band EEG activity of the channels over right sensorimotor cortex was most appropriate for discrimination of right and left hand movement intention. Effective combinations of computational methods provide possible classification of human movement intention from single trial EEG. Such a method could be the basis for a potential brain-computer interface based on human natural movement, which might reduce the requirement of long-term training. Effective combinations of computational methods can classify human movement intention from single trial EEG with reasonable accuracy.

A method of depth image based human action recognition

NASA Astrophysics Data System (ADS)

Li, Pei; Cheng, Wanli

2017-05-01

In this paper, we propose an action recognition algorithm framework based on human skeleton joint information. In order to extract the feature of human motion, we use the information of body posture, speed and acceleration of movement to construct spatial motion feature that can describe and reflect the joint. On the other hand, we use the classical temporal pyramid matching algorithm to construct temporal feature and describe the motion sequence variation from different time scales. Then, we use bag of words to represent these actions, which is to present every action in the histogram by clustering these extracted feature. Finally, we employ Hidden Markov Model to train and test the extracted motion features. In the experimental part, the correctness and effectiveness of the proposed model are comprehensively verified on two well-known datasets.

Blockade of 5-hydroxytryptamine(3) receptors prevents cisplatin-induced but not motion- or xylazine-induced emesis in the cat

NASA Technical Reports Server (NTRS)

Lucot, James B.

1989-01-01

The effects of the 5-hydroxytryptamine(3) (5-HT-3) antagonists ICS 205-930 and MDL 72222 on the emesis induced by motion or by emetic doses of xylazine (0.66 mg/kg administered SC) or cisplatin (7.5 mg/kg infused over a period of 4-5 min) were investigated in cats. It was found that neither the low (0.1 mg/kg) or the high (1.0 mg.kg) doses of ICS 205-930 or MDL 72222 prevented emesis elicited by screening motion challenges or xylazine. On the other hand, treatment cats by 1.0 mg/kg of ICS 205-930 was effective against cisplatin-induced motion sickness, in agreement with earlier results obtained on other mammals.

Models for the Effects of G-seat Cuing on Roll-axis Tracking Performance

NASA Technical Reports Server (NTRS)

Levison, W. H.; Mcmillan, G. R.; Martin, E. A.

1984-01-01

Including whole-body motion in a flight simulator improves performance for a variety of tasks requiring a pilot to compensate for the effects of unexpected disturbances. A possible mechanism for this improvement is that whole-body motion provides high derivative vehicle state information whic allows the pilot to generate more lead in responding to the external disturbances. During development of motion simulating algorithms for an advanced g-cuing system it was discovered that an algorithm based on aircraft roll acceleration producted little or no performance improvement. On the other hand, algorithms based on roll position or roll velocity produced performance equivalent to whole-body motion. The analysis and modeling conducted at both the sensory system and manual control performance levels to explain the above results are described.

Toe transfer in congenital hand malformations.

PubMed

Foucher, G; Medina, J; Navarro, R; Nagel, D

2001-01-01

Fifty-eight patients with congenital hand abnormalities underwent 65 toe-to-hand transfers. Symbrachydactyly (51 cases) was the most frequent indication. Forty-seven second toe-to-hand transfers were performed in 44 patients. The mean follow-up time was 5.2 years. Two failures occurred in cases in which only one artery was anastomosed; no failures were noted when more than one artery fed the transfer. Two patients with a single second-toe transfer presented with lateral instability of the transferred metatarsophalangeal joint. The mean active range of motion was 38 degrees, with a mean extension lag of 25 degrees. The mean two-point discrimination was 5 mm. Forty-one patients used the transferred toe well, when performing activities of daily living and playing games. Toe-to-hand transfer, prior to the establishment of the grip pattern, facilitates integration of the transfer.

Factors affecting functional recovery after surgery and hand therapy in patients with Dupuytren's disease.

PubMed

Engstrand, Christina; Krevers, Barbro; Kvist, Joanna

2015-01-01

Prospective cohort study. The evidence of the relationship between functional recovery and impairment after surgery and hand therapy are inconsistent. To explore factors that were most related to functional recovery as measured by DASH in patients with Dupuytren's disease. Eighty-one patients undergoing surgery and hand therapy were consecutively recruited. Functional recovery was measured by the Disability of the Arm, Shoulder and Hand (DASH) questionnaire. Explanatory variables: range of motion of the finger joints, five questions regarding safety and social issues of hand function, and health-related quality of life (Euroqol). The three variables "need to take special precautions", "avoid using the hand in social context", and health-related quality of life (EQ-5D index) explained 62.1% of the variance in DASH, where the first variable had the greatest relative effect. Safety and social issues of hand function and quality of life had an evident association with functional recovery. IV. Copyright © 2015 Hanley & Belfus. Published by Elsevier Inc. All rights reserved.

Kinematics of reaching and implications for handedness in rhesus monkey infants

PubMed Central

Nelson, Eliza L.; Konidaris, George D.; Berthier, Neil E.; Braun, Maurine C.; Novak, Matthew F.S.X.; Suomi, Stephen J.; Novak, Melinda A.

2014-01-01

Kinematic studies of reaching in human infants using two-dimensional (2-D) and three-dimensional (3-D) recordings have complemented behavioral studies of infant handedness by providing additional evidence of early right asymmetries. Right hand reaches have been reported to be straighter and smoother than left hand reaches during the first year. Although reaching has been a popular measure of handedness in primates, there has been no systematic comparison of left and right hand reach kinematics. We investigated reaching in infant rhesus monkeys using the 2-D motion analysis software MaxTRAQ Lite+ (Innovision Systems). Linear mixed-effects models revealed that left hand reaches were smoother, but not straighter, than right hand reaches. An early left bias matches previous findings of a left hand preference for reaching in adult rhesus monkeys. Additional work using this kind of kinematic approach will extend our understanding of primate handedness beyond traditional studies measuring only frequency or bouts of hand use. PMID:22031459

A motion-tolerant approach for monitoring SpO2 and heart rate using photoplethysmography signal with dual frame length processing and multi-classifier fusion.

PubMed

Fan, Feiyi; Yan, Yuepeng; Tang, Yongzhong; Zhang, Hao

2017-12-01

Monitoring pulse oxygen saturation (SpO 2 ) and heart rate (HR) using photoplethysmography (PPG) signal contaminated by a motion artifact (MA) remains a difficult problem, especially when the oximeter is not equipped with a 3-axis accelerometer for adaptive noise cancellation. In this paper, we report a pioneering investigation on the impact of altering the frame length of Molgedey and Schuster independent component analysis (ICAMS) on performance, design a multi-classifier fusion strategy for selecting the PPG correlated signal component, and propose a novel approach to extract SpO 2 and HR readings from PPG signal contaminated by strong MA interference. The algorithm comprises multiple stages, including dual frame length ICAMS, a multi-classifier-based PPG correlated component selector, line spectral analysis, tree-based HR monitoring, and post-processing. Our approach is evaluated by multi-subject tests. The root mean square error (RMSE) is calculated for each trial. Three statistical metrics are selected as performance evaluation criteria: mean RMSE, median RMSE and the standard deviation (SD) of RMSE. The experimental results demonstrate that a shorter ICAMS analysis window probably results in better performance in SpO 2 estimation. Notably, the designed multi-classifier signal component selector achieved satisfactory performance. The subject tests indicate that our algorithm outperforms other baseline methods regarding accuracy under most criteria. The proposed work can contribute to improving the performance of current pulse oximetry and personal wearable monitoring devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

The added value of measuring thumb and finger strength when comparing strength measurements in hypoplastic thumb patients.

PubMed

Molenaar, H M Ties; Selles, Ruud W; de Kraker, Marjolein; Stam, Henk J; Hovius, Steven E R

2013-10-01

When interventions to the hand are aimed at improving function of specific fingers or the thumb, the RIHM (Rotterdam Intrinsic Hand Myometer) is a validated tool and offers more detailed information to assess strength of the involved joints besides grip and pinch measurements. In this study, strength was measured in 65 thumbs in 40 patients diagnosed with thumb hypoplasia. These 65 thumbs were classified according to Blauth. Longitudinal radial deficiencies were also classified. The strength measurements comprised of grip, tip, tripod and key pinch. Furthermore palmar abduction and opposition of the thumb as well as abduction of the index and little finger were measured with the RIHM. For all longitudinal radial deficiency patients, grip and pinch strength as well as palmar abduction and thumb opposition were significantly lower than reference values (P<0.001). However, strength in the index finger abduction and the little finger abduction was maintained or decreased to a lesser extent according to the degree of longitudinal radial deficiency. All strength values decreased with increasing Blauth-type. Blauth-type II hands (n=15) with flexor digitorum superficialis 4 opposition transfer including stabilization of the metacarpophalangeal joint showed a trend toward a higher opposition strength without reaching statistical significance (P=0.094),however compared to non-operated Blauth-type II hands (n=6) they showed a lower grip strength (P=0.019). The RIHM is comparable in accuracy to other strength dynamometers. Using the RIHM, we were able to illustrate strength patterns on finger-specific level, showing added value when evaluating outcome in patients with hand related problems. © 2013.

Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

PubMed

Kurzynski, Marek; Krysmann, Maciej; Trajdos, Pawel; Wolczowski, Andrzej

2016-02-01

In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multiclassifier system (MCS) working in a two-level structure with a dynamic ensemble selection (DES) scheme and original concepts of competence function. Additionally, feedback information coming from bioprosthesis sensors on the correct/incorrect classification is applied to the adjustment of the combining mechanism during MCS operation through adaptive tuning competences of base classifiers depending on their decisions. Three MCS systems operating in decision tree structure and with different tuning algorithms are developed. In the MCS1 system, competence is uniformly allocated to each class belonging to the group indicated by the feedback signal. In the MCS2 system, the modification of competence depends on the node of decision tree at which a correct/incorrect classification is made. In the MCS3 system, the randomized model of classifier and the concept of cross-competence are used in the tuning procedure. Experimental investigations on the real data and computer-simulated procedure of generating feedback signals are performed. In these investigations classification accuracy of the MCS systems developed is compared and furthermore, the MCS systems are evaluated with respect to the effectiveness of the procedure of tuning competence. The results obtained indicate that modification of competence of base classifiers during the working phase essentially improves performance of the MCS system and that this improvement depends on the MCS system and tuning method used. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Adult Monteggia Fracture: Patterns and Incidence of Annular Ligament Incarceration Among 121 Cases at a Single Institution Over 19 Years.

PubMed

Hamaker, Max; Zheng, Amy; Eglseder, W Andrew; Pensy, Raymond A

2018-01-01

The purposes of this study were to identify the relative frequency of Monteggia fracture patterns and to investigate the required frequency of open reduction of the proximal radiocapitellar joint. We identified 121 Monteggia fractures at a Level I trauma center from 1996 to 2015 and included 119 in this study. These fractures were identified using a database search for the appropriate International Classification of Diseases, Ninth Revision and Current Procedural Terminology codes as well as individual surgeons' logs. Two fellowship-trained hand surgeons reviewed the identified patients' x-rays and operative notes. Each fracture was classified using Bado's original description, excluding transolecranon and Monteggia variants. Bado I lesion represented 68% (81 of 119) of Monteggia fractures. Annular ligament incarceration preventing radial head reduction occurred in approximately 17% (14 of 81) of this Bado type. Revision fixation of the ulna was not necessary (none of 119 cases) and functional range of motion (average arc, 117°) was recovered in most patients. The reoperation rate of 20% (23 of 119) was related to the severity of the presenting injury and hardware prominence. Most radial head dislocations associated with Monteggia fractures occur anteriorly and will reduce with anatomic plating of the ulna. In cases where the radial head fails to reduce, entrapment of the annular ligament can be expected and open reduction is required. Revision fixation of the ulna to achieve reduction of the radial head is uncommon in our experience. Prognostic IV. Copyright © 2018 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

The Critical Role of Self-Contact for Embodiment in Virtual Reality.

PubMed

Bovet, Sidney; Debarba, Henrique Galvan; Herbelin, Bruno; Molla, Eray; Boulic, Ronan

2018-04-01

With the broad range of motion capture devices available on the market, it is now commonplace to directly control the limb movement of an avatar during immersion in a virtual environment. Here, we study how the subjective experience of embodying a full-body controlled avatar is influenced by motor alteration and self-contact mismatches. Self-contact is in particular a strong source of passive haptic feedback and we assume it to bring a clear benefit in terms of embodiment. For evaluating this hypothesis, we experimentally manipulate self-contacts and the virtual hand displacement relatively to the body. We introduce these body posture transformations to experimentally reproduce the imperfect or incorrect mapping between real and virtual bodies, with the goal of quantifying the limits of acceptance for distorted mapping on the reported body ownership and agency. We first describe how we exploit egocentric coordinate representations to perform a motion capture ensuring that real and virtual hands coincide whenever the real hand is in contact with the body. Then, we present a pilot study that focuses on quantifying our sensitivity to visuo-tactile mismatches. The results are then used to design our main study with two factors, offset (for self-contact) and amplitude (for movement amplification). Our main result shows that subjects' embodiment remains important, even when an artificially amplified movement of the hand was performed, but provided that correct self-contacts are ensured.

Smartphone and Universal Goniometer for Measurement of Elbow Joint Motions: A Comparative Study

PubMed Central

Behnoush, Behnam; Tavakoli, Nasim; Bazmi, Elham; Nateghi Fard, Fariborz; Pourgharib Shahi, Mohammad Hossein; Okazi, Arash; Mokhtari, Tahmineh

2016-01-01

Background Universal goniometer (UG) is commonly used as a standard method to evaluate range of motion (ROM) as part of joint motions. It has some restrictions, such as involvement of both hands of the physician, leads to instability of hands and error. Nowadays smartphones usage has been increasing due to its easy application. Objectives The study was designed to compare the smartphone inclinometer-based app and UG in evaluation of ROM of elbow. Materials and Methods The maximum ROM of elbow in position of flexion and pronation and supination of forearm were examined in 60 healthy volunteers with UG and smartphone. Data were analyzed using SPSS (ver. 16) software and appropriate statistical tests were applied, such as paired t-test, ICC and Bland Altman curves. Results The results of this study showed high reliability and validity of smartphone in regarding UG with ICC > 0.95. The highest reliability for both methods was in elbow supination and the lowest was in the elbow flexion (0.84). Conclusions Smartphones due to ease of access and usage for the physician and the patient, may be good alternatives for UG. PMID:27625754

Range and egomotion estimation from compound photodetector arrays with parallel optical axis using optical flow techniques.

PubMed

Chahl, J S

2014-01-20

This paper describes an application for arrays of narrow-field-of-view sensors with parallel optical axes. These devices exhibit some complementary characteristics with respect to conventional perspective projection or angular projection imaging devices. Conventional imaging devices measure rotational egomotion directly by measuring the angular velocity of the projected image. Translational egomotion cannot be measured directly by these devices because the induced image motion depends on the unknown range of the viewed object. On the other hand, a known translational motion generates image velocities which can be used to recover the ranges of objects and hence the three-dimensional (3D) structure of the environment. A new method is presented for computing egomotion and range using the properties of linear arrays of independent narrow-field-of-view optical sensors. An approximate parallel projection can be used to measure translational egomotion in terms of the velocity of the image. On the other hand, a known rotational motion of the paraxial sensor array generates image velocities, which can be used to recover the 3D structure of the environment. Results of tests of an experimental array confirm these properties.

Vestibulo-Ocular Responses to Vertical Translation using a Hand-Operated Chair as a Field Measure of Otolith Function

NASA Technical Reports Server (NTRS)

Wood, S. J.; Campbell, D. J.; Reschke, M. F.; Prather, L.; Clement, G.

2016-01-01

The translational Vestibulo-Ocular Reflex (tVOR) is an important otolith-mediated response to stabilize gaze during natural locomotion. One goal of this study was to develop a measure of the tVOR using a simple hand-operated chair that provided passive vertical motion. Binocular eye movements were recorded with a tight-fitting video mask in ten healthy subjects. Vertical motion was provided by a modified spring-powered chair (swopper.com) at approximately 2 Hz (+/- 2 cm displacement) to approximate the head motion during walking. Linear acceleration was measured with wireless inertial sensors (Xsens) mounted on the head and torso. Eye movements were recorded while subjects viewed near (0.5m) and far (approximately 4m) targets, and then imagined these targets in darkness. Subjects also provided perceptual estimates of target distances. Consistent with the kinematic properties shown in previous studies, the tVOR gain was greater with near targets, and greater with vision than in darkness. We conclude that this portable chair system can provide a field measure of otolith-ocular function at frequencies sufficient to elicit a robust tVOR.

30 CFR 77.407 - Power-driven pulleys.

Code of Federal Regulations, 2010 CFR

2010-07-01

... equipment especially designed for hand feeding. (b) Pulleys of conveyors shall not be cleaned manually while the conveyor is in motion. ... for Mechanical Equipment § 77.407 Power-driven pulleys. (a) Belts, chains, and ropes shall not be...

A new six-degree-of-freedom force-reflecting hand controller for space telerobotics

NASA Technical Reports Server (NTRS)

Mcaffee, Douglas; Snow, Edward; Townsend, William; Robinson, Lee; Hanson, Joe

1990-01-01

A new 6 degree of freedom universal Force Reflecting Hand Controller (FRHC) was designed for use as the man-machine interface in teleoperated and telerobotic flight systems. The features of this new design include highly intuitive operation, excellent kinesthetic feedback, high fidelity force/torque feedback, a kinematically simple structure, mechanically decoupled motion in all 6 DOF, good back-drivability, and zero backlash. In addition, the new design has a much larger work envelope, smaller stowage volume, greater stiffness and responsiveness, and better overlap of the human operator's range of motion than do previous designs. The utility and basic operation of a new, flight prototype FRHC called the Model X is briefly discussed. The design heritage, general design goals, and design implementation of this advanced new generation of FRHCs are presented, followed by a discussion of basic features and the results of initial testing.

Peak velocity of elbow joint during hair combing activity for normal subject

NASA Astrophysics Data System (ADS)

Che-Nan, Hasyatun; Rambely, Azmin Sham

2018-04-01

Study of upper limb movements is very important for clinical assessment and diagnosis purposes. Thus it requires the analysis of motion. Therefore this study intend to investigate peak velocity of elbow joint during hair-combing activity. Twenty healthy subjects with three trials and age range 20 - 59 years old (n = 60) performed a complete cycle of hand reaching, forward transport, combing, back transport and returning the hand to its initial position. This activity was analyzed using Vicon motion-analysis system, which consisted of three infra-red and high speed cameras. Mean total movement times was recorded at 5.2s for the whole phases. Peak velocities during reaching and forward transport were found to be decreasing in value for the healthy subject. This obtained results provide information on kinematic analysis especially on movement times and peak velocities for clinical, assessment and diagnosis purposes.

Variable Structure Control of a Hand-Launched Glider

NASA Technical Reports Server (NTRS)

Anderson, Mark R.; Waszak, Martin R.

2005-01-01

Variable structure control system design methods are applied to the problem of aircraft spin recovery. A variable structure control law typically has two phases of operation. The reaching mode phase uses a nonlinear relay control strategy to drive the system trajectory to a pre-defined switching surface within the motion state space. The sliding mode phase involves motion along the surface as the system moves toward an equilibrium or critical point. Analysis results presented in this paper reveal that the conventional method for spin recovery can be interpreted as a variable structure controller with a switching surface defined at zero yaw rate. Application of Lyapunov stability methods show that deflecting the ailerons in the direction of the spin helps to insure that this switching surface is stable. Flight test results, obtained using an instrumented hand-launched glider, are used to verify stability of the reaching mode dynamics.

Constant angular velocity of the wrist during the lifting of a sphere.

PubMed

Chappell, P H; Metcalf, C D; Burridge, J H; Yule, V T; Pickering, R M

2010-05-01

The primary objective of the experiments was to investigate the wrist motion of a person while they were carrying out a prehensile task from a clinical hand function test. A six-camera movement system was used to observe the wrist motion of 10 participants. A very light sphere and a heavy sphere were used in the experiments to study any mass effects. While seated at a table, a participant moved a sphere over a small obstacle using their dominant hand. The participants were observed to move their wrist at a constant angular velocity. This phenomenon has not been reported previously. Theoretically, the muscles of the wrist provide an impulse of force at the start of the rotation while the forearm maintains a constant vertical force on a sphere. Light-heavy mean differences for the velocities, absolute velocities, angles and times taken showed no significant differences (p = 0.05).

Infrared thermography based on artificial intelligence as a screening method for carpal tunnel syndrome diagnosis.

PubMed

Jesensek Papez, B; Palfy, M; Mertik, M; Turk, Z

2009-01-01

This study further evaluated a computer-based infrared thermography (IRT) system, which employs artificial neural networks for the diagnosis of carpal tunnel syndrome (CTS) using a large database of 502 thermal images of the dorsal and palmar side of 132 healthy and 119 pathological hands. It confirmed the hypothesis that the dorsal side of the hand is of greater importance than the palmar side when diagnosing CTS thermographically. Using this method it was possible correctly to classify 72.2% of all hands (healthy and pathological) based on dorsal images and > 80% of hands when only severely affected and healthy hands were considered. Compared with the gold standard electromyographic diagnosis of CTS, IRT cannot be recommended as an adequate diagnostic tool when exact severity level diagnosis is required, however we conclude that IRT could be used as a screening tool for severe cases in populations with high ergonomic risk factors of CTS.

Interdependency of the maximum range of flexion-extension of hand metacarpophalangeal joints.

PubMed

Gracia-Ibáñez, V; Vergara, M; Sancho-Bru, J-L

2016-12-01

Mobility of the fingers metacarpophalangeal (MCP) joints depends on the posture of the adjacent ones. Current Biomechanical hand models consider fixed ranges of movement at joints, regardless of the posture, thus allowing for non-realistic postures, generating wrong results in reach studies and forward dynamic analyses. This study provides data for more realistic hand models. The maximum voluntary extension (MVE) and flexion (MVF) of different combinations of MCP joints were measured covering their range of motion. Dependency of the MVF and MVE on the posture of the adjacent MCP joints was confirmed and mathematical models obtained through regression analyses (RMSE 7.7°).

Magnetic resonance imaging as a tool for extravehicular activity analysis

NASA Technical Reports Server (NTRS)

Dickenson, R.; Lorenz, C.; Peterson, S.; Strauss, A.; Main, J.

1992-01-01

The purpose of this research is to examine the value of magnetic resonance imaging (MRI) as a means of conducting kinematic studies of the hand for the purpose of EVA capability enhancement. After imaging the subject hand using a magnetic resonance scanner, the resulting 2D slices were reconstructed into a 3D model of the proximal phalanx of the left hand. Using the coordinates of several landmark positions, one is then able to decompose the motion of the rigid body. MRI offers highly accurate measurements due to its tomographic nature without the problems associated with other imaging modalities for in vivo studies.

High-pressure Injection Injuries of the Hand.

PubMed

Cannon, Tyler A

2016-07-01

High-pressure injection hand injuries are often overlooked, with severe complications owing to the acute inflammatory response. Prognosis for depends on the type of material injected, location of injection, involved pressure, and timing to surgical decompression and debridement. Acute management involves broad-spectrum antibiotics, tetanus prophylaxis, emergent decompression within 6 hours, and complete removal of the injected material. Most patients have residual sequelae of stiffness, pain, sensation loss, and difficulties in returning to work. The hand surgeon's role is prompt surgical intervention, early postoperative motion, and education of patient and staff regarding short- and long-term expectations. Copyright © 2016 Elsevier Inc. All rights reserved.

Linear Back-Drive Differentials

NASA Technical Reports Server (NTRS)

Waydo, Peter

2003-01-01

Linear back-drive differentials have been proposed as alternatives to conventional gear differentials for applications in which there is only limited rotational motion (e.g., oscillation). The finite nature of the rotation makes it possible to optimize a linear back-drive differential in ways that would not be possible for gear differentials or other differentials that are required to be capable of unlimited rotation. As a result, relative to gear differentials, linear back-drive differentials could be more compact and less massive, could contain fewer complex parts, and could be less sensitive to variations in the viscosities of lubricants. Linear back-drive differentials would operate according to established principles of power ball screws and linear-motion drives, but would utilize these principles in an innovative way. One major characteristic of such mechanisms that would be exploited in linear back-drive differentials is the possibility of designing them to drive or back-drive with similar efficiency and energy input: in other words, such a mechanism can be designed so that a rotating screw can drive a nut linearly or the linear motion of the nut can cause the screw to rotate. A linear back-drive differential (see figure) would include two collinear shafts connected to two parts that are intended to engage in limited opposing rotations. The linear back-drive differential would also include a nut that would be free to translate along its axis but not to rotate. The inner surface of the nut would be right-hand threaded at one end and left-hand threaded at the opposite end to engage corresponding right- and left-handed threads on the shafts. A rotation and torque introduced into the system via one shaft would drive the nut in linear motion. The nut, in turn, would back-drive the other shaft, creating a reaction torque. Balls would reduce friction, making it possible for the shaft/nut coupling on each side to operate with 90 percent efficiency.

"Teacher in Space" Trainees - Arriflex Motion Picture Camera

NASA Image and Video Library

1985-09-20

S85-40670 (18 Sept. 1985) --- The two teachers, Sharon Christa McAuliffe and Barbara R. Morgan (out of frame) have hands-on experience with an Arriflex motion picture camera following a briefing on space photography. The two began training Sept. 10, 1985 with the STS-51L crew and learning basic procedures for space travelers. The second week of training included camera training, aircraft familiarization and other activities. McAuliffe zeroes in on a test subject during a practice session with the Arriflex. Photo credit: NASA

Teacher-in-Space Trainees - Arriflex Motion Picture Camera

NASA Image and Video Library

1985-09-20

S85-40669 (18 Sept. 1985) --- The two teachers, Sharon Christa McAuliffe (left) and Barbara R. Morgan have hands-on experience with an Arriflex motion picture camera following a briefing on space photography. The two began training Sept. 10, 1985 with the STS-51L crew and learning basic procedure for space travelers. The second week of training included camera training, aircraft familiarization and other activities. Morgan adjusts a lens as a studious McAuliffe looks on. Photo credit: NASA

"Teacher in Space" Trainees - Arriflex Motion Picture Camera

NASA Image and Video Library

1985-09-20

S85-40671 (18 Sept. 1985) --- The two teachers, Barbara R. Morgan and Sharon Christa McAuliffe (out of frame) have hands-on experience with an Arriflex motion picture camera following a briefing on space photography. The two began training Sept. 10, 1985 with the STS-51L crew and learning basic procedures for space travelers. The second week of training included camera training, aircraft familiarization and other activities. Morgan zeroes in on a test subject during a practice session with the Arriflex. Photo credit: NASA

Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math.

PubMed

Raizada, Rajeev D S; Tsao, Feng-Ming; Liu, Huei-Mei; Holloway, Ian D; Ansari, Daniel; Kuhl, Patricia K

2010-05-15

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain-behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI. Multivariate pattern-based fMRI analysis methods use classifiers to analyse multiple voxels together, but can also introduce selection bias via data-reduction steps as feature selection of voxels, pre-selecting activated regions, or principal components analysis. We show here that strong brain-behaviour links can be revealed without any voxel selection or data reduction, using just plain linear regression as a classifier applied to the whole brain at once, i.e. treating each entire brain volume as a single multi-voxel pattern. The brain-behaviour correlations emerged despite the fact that the classifier was not provided with any information at all about subjects' behaviour, but instead was given only the neural data and its condition-labels. Surprisingly, more powerful classifiers such as a linear SVM and regularised logistic regression produce very similar results. We discuss some possible reasons why the very simple brain-wide linear regression model is able to find correlations with behaviour that are as strong as those obtained on the one hand from a specific ROI and on the other hand from more complex classifiers. In a manner which is unencumbered by arbitrary choices, our approach offers a method for investigating connections between brain and behaviour which is simple, rigorous and direct. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Linking brain-wide multivoxel activation patterns to behaviour: Examples from language and math

PubMed Central

Raizada, Rajeev D.S.; Tsao, Feng-Ming; Liu, Huei-Mei; Holloway, Ian D.; Ansari, Daniel; Kuhl, Patricia K.

2010-01-01

A key goal of cognitive neuroscience is to find simple and direct connections between brain and behaviour. However, fMRI analysis typically involves choices between many possible options, with each choice potentially biasing any brain–behaviour correlations that emerge. Standard methods of fMRI analysis assess each voxel individually, but then face the problem of selection bias when combining those voxels into a region-of-interest, or ROI. Multivariate pattern-based fMRI analysis methods use classifiers to analyse multiple voxels together, but can also introduce selection bias via data-reduction steps as feature selection of voxels, pre-selecting activated regions, or principal components analysis. We show here that strong brain–behaviour links can be revealed without any voxel selection or data reduction, using just plain linear regression as a classifier applied to the whole brain at once, i.e. treating each entire brain volume as a single multi-voxel pattern. The brain–behaviour correlations emerged despite the fact that the classifier was not provided with any information at all about subjects' behaviour, but instead was given only the neural data and its condition-labels. Surprisingly, more powerful classifiers such as a linear SVM and regularised logistic regression produce very similar results. We discuss some possible reasons why the very simple brain-wide linear regression model is able to find correlations with behaviour that are as strong as those obtained on the one hand from a specific ROI and on the other hand from more complex classifiers. In a manner which is unencumbered by arbitrary choices, our approach offers a method for investigating connections between brain and behaviour which is simple, rigorous and direct. PMID:20132896

Improving EMG based classification of basic hand movements using EMD.

PubMed

Sapsanis, Christos; Georgoulas, George; Tzes, Anthony; Lymberopoulos, Dimitrios

2013-01-01

This paper presents a pattern recognition approach for the identification of basic hand movements using surface electromyographic (EMG) data. The EMG signal is decomposed using Empirical Mode Decomposition (EMD) into Intrinsic Mode Functions (IMFs) and subsequently a feature extraction stage takes place. Various combinations of feature subsets are tested using a simple linear classifier for the detection task. Our results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

The application of mean field theory to image motion estimation.

PubMed

Zhang, J; Hanauer, G G

1995-01-01

Previously, Markov random field (MRF) model-based techniques have been proposed for image motion estimation. Since motion estimation is usually an ill-posed problem, various constraints are needed to obtain a unique and stable solution. The main advantage of the MRF approach is its capacity to incorporate such constraints, for instance, motion continuity within an object and motion discontinuity at the boundaries between objects. In the MRF approach, motion estimation is often formulated as an optimization problem, and two frequently used optimization methods are simulated annealing (SA) and iterative-conditional mode (ICM). Although the SA is theoretically optimal in the sense of finding the global optimum, it usually takes many iterations to converge. The ICM, on the other hand, converges quickly, but its results are often unsatisfactory due to its "hard decision" nature. Previously, the authors have applied the mean field theory to image segmentation and image restoration problems. It provides results nearly as good as SA but with much faster convergence. The present paper shows how the mean field theory can be applied to MRF model-based motion estimation. This approach is demonstrated on both synthetic and real-world images, where it produced good motion estimates.

Motion of the drawing hand induces a progressive increase in muscle activity of the non-dominant hand in Ramachandran's mirror-box therapy.

PubMed

Furukawa, Kiminobu; Suzuki, Harue; Fukuda, Jun

2012-11-01

To observe the real-time muscle activity of bilateral hands while subjects draw circles under 2 conditions: with and without using Ramachandran's mirror-box. A total of 24 healthy volunteers. Subjects drew 4 circles sequentially using their dominant hand with the other hand at rest, both with and without looking at a mirror image. Circles were marked by 8 dots on the paper, which subjects connected up to draw the shape. The activity of the bilateral first dorsal interosseus muscles was recorded using surface electromyography. Muscle activity of the dominant hand remained constant during each task. In contrast, muscle activity of the non-dominant hand increased under the condition of watching the image in the mirror, but was low under the non-watching condition. Furthermore, muscle activity of the non-dominant hand increased over the duration of the task. However, wide variation between subjects was observed under the mirror-image condition. Increased muscle action potential of the non-dominant hand may be induced by the circle drawing task of the dominant hand during Ramachandran's mirror-box therapy, which supports previous observations of increased brain activity caused by watching a mirror image.