Fusion of smartphone motion sensors for physical activity recognition.

PubMed

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

2014-06-10

For physical activity recognition, smartphone sensors, such as an accelerometer and a gyroscope, are being utilized in many research studies. So far, particularly, the accelerometer has been extensively studied. In a few recent studies, a combination of a gyroscope, a magnetometer (in a supporting role) and an accelerometer (in a lead role) has been used with the aim to improve the recognition performance. How and when are various motion sensors, which are available on a smartphone, best used for better recognition performance, either individually or in combination? This is yet to be explored. In order to investigate this question, in this paper, we explore how these various motion sensors behave in different situations in the activity recognition process. For this purpose, we designed a data collection experiment where ten participants performed seven different activities carrying smart phones at different positions. Based on the analysis of this data set, we show that these sensors, except the magnetometer, are each capable of taking the lead roles individually, depending on the type of activity being recognized, the body position, the used data features and the classification method employed (personalized or generalized). We also show that their combination only improves the overall recognition performance when their individual performances are not very high, so that there is room for performance improvement. We have made our data set and our data collection application publicly available, thereby making our experiments reproducible.

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks

PubMed Central

Ponce, Hiram; Miralles-Pechuán, Luis; Martínez-Villaseñor, María de Lourdes

2016-01-01

Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior in order to deliver proactive and personalized services. Although many activity recognition systems have been developed for more than two decades, there are still open issues to be tackled with new techniques. We address in this paper one of the main challenges of human activity recognition: Flexibility. Our goal in this work is to present artificial hydrocarbon networks as a novel flexible approach in a human activity recognition system. In order to evaluate the performance of artificial hydrocarbon networks based classifier, experimentation was designed for user-independent, and also for user-dependent case scenarios. Our results demonstrate that artificial hydrocarbon networks classifier is flexible enough to be used when building a human activity recognition system with either user-dependent or user-independent approaches. PMID:27792136

A Flexible Approach for Human Activity Recognition Using Artificial Hydrocarbon Networks.

PubMed

Ponce, Hiram; Miralles-Pechuán, Luis; Martínez-Villaseñor, María de Lourdes

2016-10-25

Physical activity recognition based on sensors is a growing area of interest given the great advances in wearable sensors. Applications in various domains are taking advantage of the ease of obtaining data to monitor personal activities and behavior in order to deliver proactive and personalized services. Although many activity recognition systems have been developed for more than two decades, there are still open issues to be tackled with new techniques. We address in this paper one of the main challenges of human activity recognition: Flexibility. Our goal in this work is to present artificial hydrocarbon networks as a novel flexible approach in a human activity recognition system. In order to evaluate the performance of artificial hydrocarbon networks based classifier, experimentation was designed for user-independent, and also for user-dependent case scenarios. Our results demonstrate that artificial hydrocarbon networks classifier is flexible enough to be used when building a human activity recognition system with either user-dependent or user-independent approaches.

Accelerometer's position independent physical activity recognition system for long-term activity monitoring in the elderly.

PubMed

Khan, Adil Mehmood; Lee, Young-Koo; Lee, Sungyoung; Kim, Tae-Seong

2010-12-01

Mobility is a good indicator of health status and thus objective mobility data could be used to assess the health status of elderly patients. Accelerometry has emerged as an effective means for long-term physical activity monitoring in the elderly. However, the output of an accelerometer varies at different positions on a subject's body, even for the same activity, resulting in high within-class variance. Existing accelerometer-based activity recognition systems thus require firm attachment of the sensor to a subject's body. This requirement makes them impractical for long-term activity monitoring during unsupervised free-living as it forces subjects into a fixed life pattern and impede their daily activities. Therefore, we introduce a novel single-triaxial-accelerometer-based activity recognition system that reduces the high within-class variance significantly and allows subjects to carry the sensor freely in any pocket without its firm attachment. We validated our system using seven activities: resting (lying/sitting/standing), walking, walking-upstairs, walking-downstairs, running, cycling, and vacuuming, recorded from five positions: chest pocket, front left trousers pocket, front right trousers pocket, rear trousers pocket, and inner jacket pocket. Its simplicity, ability to perform activities unimpeded, and an average recognition accuracy of 94% make our system a practical solution for continuous long-term activity monitoring in the elderly.

A survey of online activity recognition using mobile phones.

PubMed

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

2015-01-19

Physical activity recognition using embedded sensors has enabled many context-aware applications in different areas, such as healthcare. Initially, one or more dedicated wearable sensors were used for such applications. However, recently, many researchers started using mobile phones for this purpose, since these ubiquitous devices are equipped with various sensors, ranging from accelerometers to magnetic field sensors. In most of the current studies, sensor data collected for activity recognition are analyzed offline using machine learning tools. However, there is now a trend towards implementing activity recognition systems on these devices in an online manner, since modern mobile phones have become more powerful in terms of available resources, such as CPU, memory and battery. The research on offline activity recognition has been reviewed in several earlier studies in detail. However, work done on online activity recognition is still in its infancy and is yet to be reviewed. In this paper, we review the studies done so far that implement activity recognition systems on mobile phones and use only their on-board sensors. We discuss various aspects of these studies. Moreover, we discuss their limitations and present various recommendations for future research.

Factors associated with parental recognition of a child's overweight status - a cross sectional study

PubMed Central

2011-01-01

Background Very few studies have evaluated the association between a child's lifestyle factors and their parent's ability to recognise the overweight status of their offspring. The aim of this study was to analyze the factors associated with a parent's ability to recognise their own offspring's overweight status. Methods 125 overweight children out of all 1,278 school beginners in Northern Finland were enrolled. Weight and height were measured in health care clinics. Overweight status was defined by BMI according to internationally accepted criteria. A questionnaire to be filled in by parents was delivered by the school nurses. The parents were asked to evaluate their offspring's weight status. The child's eating habits and physical activity patterns were also enquired about. Factor groups of food and physical activity habits were formed by factor analysis. Binary logistic regression was performed using all variables associated with recognition of overweight status in univariate analyses. The significant risk factors in the final model are reported using odds ratios (ORs) and their 95% confidence intervals (CIs). Results Fifty-seven percent (69/120) of the parents of the overweight children considered their child as normal weight. Child's BMI was positively associated with parental recognition of overweight (OR 3.59, CI 1.8 to 7.0). Overweight boys were less likely to be recognised than overweight girls (OR 0.14, CI 0.033 to 0.58). Child's healthy diet (OR 0.22, CI 0.091 to 0.54) and high physical activity (OR 0.29, CI 0.11 to 0.79) were inversely related to parental recognition of overweight status. Conclusions Child's healthy eating habits and physical activity are inversely related to parental recognition of their offspring's overweight. These should be taken into account when planning prevention and treatment strategies for childhood obesity. PMID:21864365

Validation of five minimally obstructive methods to estimate physical activity energy expenditure in young adults in semi-standardized settings.

PubMed

Schneller, Mikkel B; Pedersen, Mogens T; Gupta, Nidhi; Aadahl, Mette; Holtermann, Andreas

2015-03-13

We compared the accuracy of five objective methods, including two newly developed methods combining accelerometry and activity type recognition (Acti4), against indirect calorimetry, to estimate total energy expenditure (EE) of different activities in semi-standardized settings. Fourteen participants performed a standardized and semi-standardized protocol including seven daily life activity types, while having their EE measured by indirect calorimetry. Simultaneously, physical activity was quantified by an ActivPAL3, two ActiGraph GT3X+'s and an Actiheart. EE was estimated by the standard ActivPAL3 software (ActivPAL), ActiGraph GT3X+ (ActiGraph) and Actiheart (Actiheart), and by a combination of activity type recognition via Acti4 software and activity counts per minute (CPM) of either a hip- or thigh-worn ActiGraph GT3X+ (AGhip + Acti4 and AGthigh + Acti4). At group level, estimated physical activities EE by Actiheart (MSE = 2.05) and AGthigh + Acti4 (MSE = 0.25) were not significantly different from measured EE by indirect calorimetry, while significantly underestimated by ActiGraph, ActivPAL and AGhip + Acti4. AGthigh + Acti4 and Actiheart explained 77% and 45%, of the individual variations in measured physical activity EE by indirect calorimetry, respectively. This study concludes that combining accelerometer data from a thigh-worn ActiGraph GT3X+ with activity type recognition improved the accuracy of activity specific EE estimation against indirect calorimetry in semi-standardized settings compared to previously validated methods using CPM only.

Representation, Classification and Information Fusion for Robust and Efficient Multimodal Human States Recognition

ERIC Educational Resources Information Center

Li, Ming

2013-01-01

The goal of this work is to enhance the robustness and efficiency of the multimodal human states recognition task. Human states recognition can be considered as a joint term for identifying/verifing various kinds of human related states, such as biometric identity, language spoken, age, gender, emotion, intoxication level, physical activity, vocal…

A Survey of Online Activity Recognition Using Mobile Phones

PubMed Central

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

2015-01-01

Physical activity recognition using embedded sensors has enabled many context-aware applications in different areas, such as healthcare. Initially, one or more dedicated wearable sensors were used for such applications. However, recently, many researchers started using mobile phones for this purpose, since these ubiquitous devices are equipped with various sensors, ranging from accelerometers to magnetic field sensors. In most of the current studies, sensor data collected for activity recognition are analyzed offline using machine learning tools. However, there is now a trend towards implementing activity recognition systems on these devices in an online manner, since modern mobile phones have become more powerful in terms of available resources, such as CPU, memory and battery. The research on offline activity recognition has been reviewed in several earlier studies in detail. However, work done on online activity recognition is still in its infancy and is yet to be reviewed. In this paper, we review the studies done so far that implement activity recognition systems on mobile phones and use only their on-board sensors. We discuss various aspects of these studies. Moreover, we discuss their limitations and present various recommendations for future research. PMID:25608213

Comparing supervised learning techniques on the task of physical activity recognition.

PubMed

Dalton, A; OLaighin, G

2013-01-01

The objective of this study was to compare the performance of base-level and meta-level classifiers on the task of physical activity recognition. Five wireless kinematic sensors were attached to each subject (n = 25) while they completed a range of basic physical activities in a controlled laboratory setting. Subjects were then asked to carry out similar self-annotated physical activities in a random order and in an unsupervised environment. A combination of time-domain and frequency-domain features were extracted from the sensor data including the first four central moments, zero-crossing rate, average magnitude, sensor cross-correlation, sensor auto-correlation, spectral entropy and dominant frequency components. A reduced feature set was generated using a wrapper subset evaluation technique with a linear forward search and this feature set was employed for classifier comparison. The meta-level classifier AdaBoostM1 with C4.5 Graft as its base-level classifier achieved an overall accuracy of 95%. Equal sized datasets of subject independent data and subject dependent data were used to train this classifier and high recognition rates could be achieved without the need for user specific training. Furthermore, it was found that an accuracy of 88% could be achieved using data from the ankle and wrist sensors only.

Effect of Methylphenidate on Cardiorespiratory Responses in Hyperactive Children

ERIC Educational Resources Information Center

Boileau, Richard A.; And Others

1976-01-01

Recognition by the physical education teacher that the cardiovascular dynamics of the hyperactive child are augmented during methylphenidate (Ritalin) medication is warranted when planning strenuous physical activity. (JD)

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.

PubMed

Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G

2017-09-01

To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.

Physical Activity Recognition with Mobile Phones: Challenges, Methods, and Applications

NASA Astrophysics Data System (ADS)

Yang, Jun; Lu, Hong; Liu, Zhigang; Boda, Péter Pál

In this book chapter, we present a novel system that recognizes and records the physical activity of a person using a mobile phone. The sensor data is collected by built-in accelerometer sensor that measures the motion intensity of the device. The system recognizes five everyday activities in real-time, i.e., stationary, walking, running, bicycling, and in vehicle. We first introduce the sensor's data format, sensor calibration, signal projection, feature extraction, and selection methods. Then we have a detailed discussion and comparison of different choices of feature sets and classifiers. The design and implementation of one prototype system is presented along with resource and performance benchmark on Nokia N95 platform. Results show high recognition accuracies for distinguishing the five activities. The last part of the chapter introduces one demo application built on top of our system, physical activity diary, and a selection of potential applications in mobile wellness, mobile social sharing and contextual user interface domains.

Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC.

PubMed

Lee, Mi Hee; Kim, Jungchae; Jee, Sun Ha; Yoo, Sun Kook

2011-03-01

This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC. We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns. We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 ± 0.61%, 99.1 ± 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring. This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition.

Identifying typical physical activity on smartphone with varying positions and orientations.

PubMed

Miao, Fen; He, Yi; Liu, Jinlei; Li, Ye; Ayoola, Idowu

2015-04-13

Traditional activity recognition solutions are not widely applicable due to a high cost and inconvenience to use with numerous sensors. This paper aims to automatically recognize physical activity with the help of the built-in sensors of the widespread smartphone without any limitation of firm attachment to the human body. By introducing a method to judge whether the phone is in a pocket, we investigated the data collected from six positions of seven subjects, chose five signals that are insensitive to orientation for activity classification. Decision trees (J48), Naive Bayes and Sequential minimal optimization (SMO) were employed to recognize five activities: static, walking, running, walking upstairs and walking downstairs. The experimental results based on 8,097 activity data demonstrated that the J48 classifier produced the best performance with an average recognition accuracy of 89.6% during the three classifiers, and thus would serve as the optimal online classifier. The utilization of the built-in sensors of the smartphone to recognize typical physical activities without any limitation of firm attachment is feasible.

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.

Analysis of differences in exercise recognition by constraints on physical activity of hospitalized cancer patients based on their medical history.

PubMed

Choi, Mi-Ri; Jeon, Sang-Wan; Yi, Eun-Surk

2018-04-01

The purpose of this study is to analyze the differences among the hospitalized cancer patients on their perception of exercise and physical activity constraints based on their medical history. The study used questionnaire survey as measurement tool for 194 cancer patients (male or female, aged 20 or older) living in Seoul metropolitan area (Seoul, Gyeonggi, Incheon). The collected data were analyzed using frequency analysis, exploratory factor analysis, reliability analysis t -test, and one-way distribution using statistical program SPSS 18.0. The following results were obtained. First, there was no statistically significant difference between cancer stage and exercise recognition/physical activity constraint. Second, there was a significant difference between cancer stage and sociocultural constraint/facility constraint/program constraint. Third, there was a significant difference between cancer operation history and physical/socio-cultural/facility/program constraint. Fourth, there was a significant difference between cancer operation history and negative perception/facility/program constraint. Fifth, there was a significant difference between ancillary cancer treatment method and negative perception/facility/program constraint. Sixth, there was a significant difference between hospitalization period and positive perception/negative perception/physical constraint/cognitive constraint. In conclusion, this study will provide information necessary to create patient-centered healthcare service system by analyzing exercise recognition of hospitalized cancer patients based on their medical history and to investigate the constraint factors that prevents patients from actually making efforts to exercise.

Classification of motor activities through derivative dynamic time warping applied on accelerometer data.

PubMed

Muscillo, Rossana; Conforto, Silvia; Schmid, Maurizio; Caselli, Paolo; D'Alessio, Tommaso

2007-01-01

In the context of tele-monitoring, great interest is presently devoted to physical activity, mainly of elderly or people with disabilities. In this context, many researchers studied the recognition of activities of daily living by using accelerometers. The present work proposes a novel algorithm for activity recognition that considers the variability in movement speed, by using dynamic programming. This objective is realized by means of a matching and recognition technique that determines the distance between the signal input and a set of previously defined templates. Two different approaches are here presented, one based on Dynamic Time Warping (DTW) and the other based on the Derivative Dynamic Time Warping (DDTW). The algorithm was applied to the recognition of gait, climbing and descending stairs, using a biaxial accelerometer placed on the shin. The results on DDTW, obtained by using only one sensor channel on the shin showed an average recognition score of 95%, higher than the values obtained with DTW (around 85%). Both DTW and DDTW consistently show higher classification rate than classical Linear Time Warping (LTW).

Multisensor data fusion for physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John W; Freedson, Patty S

2012-03-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multisensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which activity type and energy expenditure are derived. The results show that the method correctly recognized the 13 activity types 88.1% of the time, which is 12.3% higher than using a hip accelerometer alone. Also, the method predicted energy expenditure with a root mean square error of 0.42 METs, 22.2% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor were added to the fusion model. These results demonstrate that the multisensor fusion technique presented is more effective in identifying activity type and energy expenditure than the traditional accelerometer-alone-based methods.

Sports Cardiology: Core Curriculum for Providing Cardiovascular Care to Competitive Athletes and Highly Active People.

PubMed

Baggish, Aaron L; Battle, Robert W; Beckerman, James G; Bove, Alfred A; Lampert, Rachel J; Levine, Benjamin D; Link, Mark S; Martinez, Matthew W; Molossi, Silvana M; Salerno, Jack; Wasfy, Meagan M; Weiner, Rory B; Emery, Michael S

2017-10-10

The last few decades have seen substantial growth in the populations of competitive athletes and highly active people (CAHAP). Although vigorous physical exercise is an effective way to reduce the risk of cardiovascular (CV) disease, CAHAP remain susceptible to inherited and acquired CV disease, and may be most at risk for adverse CV outcomes during intense physical activity. Traditionally, multidisciplinary teams comprising athletic trainers, physical therapists, primary care sports medicine physicians, and orthopedic surgeons have provided clinical care for CAHAP. However, there is increasing recognition that a care team including qualified CV specialists optimizes care delivery for CAHAP. In recognition of the increasing demand for CV specialists competent in the care of CAHAP, the American College of Cardiology has recently established a Sports and Exercise Council. An important primary objective of this council is to define the essential skills necessary to practice effective sports cardiology. Copyright © 2017. Published by Elsevier Inc.

Physical activity monitoring by use of accelerometer-based body-worn sensors in older adults: a systematic literature review of current knowledge and applications.

PubMed

Taraldsen, Kristin; Chastin, Sebastien F M; Riphagen, Ingrid I; Vereijken, Beatrix; Helbostad, Jorunn L

2012-01-01

To systematically review the literature on physical activity variables derived from body-worn sensors during long term monitoring in healthy and in-care older adults. Using pre-designed inclusion and exclusion criteria, a PubMed search strategy was designed to trace relevant reports of studies. Last search date was March 8, 2011. Studies that included persons with mean or median age of >65 years, used accelerometer-based body-worn sensors with a monitoring length of >24h, and reported values on physical activity in the samples assessed. 1403 abstracts were revealed and 134 full-text papers included in the final review. A variety of variables derived from activity counts or recognition of performed activities were reported in healthy older adults as well as in in-care older adults. Three variables were possible to compare across studies, level of Energy Expenditure in kcal per day and activity recognition in terms of total time in walking and total activity. However, physical activity measured by these variables demonstrated large variation between studies and did not distinguish activity between healthy and in-care samples. There is a rich variety in methods used for data collection and analysis as well as in reported variables. Different aspects of physical activity can be described, but the variety makes it challenging to compare across studies. There is an urgent need for developing consensus on activity monitoring protocols and which variables to report. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Hand gesture recognition in confined spaces with partial observability and occultation constraints

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Lexical neutrality in environmental health research: Reflections on the term walkability.

PubMed

Hajna, Samantha; Ross, Nancy A; Griffin, Simon J; Dasgupta, Kaberi

2017-12-08

Neighbourhood environments have important implications for human health. In this piece, we reflect on the environments and health literature and argue that precise use of language is critical for acknowledging the complex and multifaceted influence that neighbourhood environments may have on physical activity and physical activity-related outcomes. Specifically, we argue that the term "neighbourhood walkability", commonly used in the neighbourhoods and health literature, constrains recognition of the breadth of influence that neighbourhood environments might have on a variety of physical activity behaviours. The term draws attention to a single type of physical activity and implies that a universal association exists when in fact the literature is quite mixed. To maintain neutrality in this area of research, we suggest that researchers adopt the term "neighbourhood physical activity environments" for collective measures of neighbourhood attributes that they wish to study in relation to physical activity behaviours or physical activity-related health outcomes.

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition

PubMed Central

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-01-01

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called “deep learning”, which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google’s TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records. PMID:28042838

A Comparison Study of Classifier Algorithms for Cross-Person Physical Activity Recognition.

PubMed

Saez, Yago; Baldominos, Alejandro; Isasi, Pedro

2016-12-30

Physical activity is widely known to be one of the key elements of a healthy life. The many benefits of physical activity described in the medical literature include weight loss and reductions in the risk factors for chronic diseases. With the recent advances in wearable devices, such as smartwatches or physical activity wristbands, motion tracking sensors are becoming pervasive, which has led to an impressive growth in the amount of physical activity data available and an increasing interest in recognizing which specific activity a user is performing. Moreover, big data and machine learning are now cross-fertilizing each other in an approach called "deep learning", which consists of massive artificial neural networks able to detect complicated patterns from enormous amounts of input data to learn classification models. This work compares various state-of-the-art classification techniques for automatic cross-person activity recognition under different scenarios that vary widely in how much information is available for analysis. We have incorporated deep learning by using Google's TensorFlow framework. The data used in this study were acquired from PAMAP2 (Physical Activity Monitoring in the Ageing Population), a publicly available dataset containing physical activity data. To perform cross-person prediction, we used the leave-one-subject-out (LOSO) cross-validation technique. When working with large training sets, the best classifiers obtain very high average accuracies (e.g., 96% using extra randomized trees). However, when the data volume is drastically reduced (where available data are only 0.001% of the continuous data), deep neural networks performed the best, achieving 60% in overall prediction accuracy. We found that even when working with only approximately 22.67% of the full dataset, we can statistically obtain the same results as when working with the full dataset. This finding enables the design of more energy-efficient devices and facilitates cold starts and big data processing of physical activity records.

Smart approaches for assessing free-living energy expenditure following identification of types of physical activity.

PubMed

Plasqui, G

2017-02-01

Accurate assessment of physical activity and energy expenditure has been a research focus for many decades. A variety of wearable sensors have been developed to objectively capture physical activity patterns in daily life. These sensors have evolved from simple pedometers to tri-axial accelerometers, and multi sensor devices measuring different physiological constructs. The current review focuses on how activity recognition may help to improve daily life energy expenditure assessment. A brief overview is given about how different sensors have evolved over time to pave the way for recognition of different activity types. Once the activity is recognized together with the intensity of the activity, an energetic value can be attributed. This concept can then be tested in daily life using the independent reference technique doubly labeled water. So far, many studies have been performed to accurately identify activity types, and some of those studies have also successfully translated this into energy expenditure estimates. Most of these studies have been performed under standardized conditions, and the true applicability in daily life has rarely been addressed. The results so far however are highly promising, and technological advancements together with newly developed algorithms based on physiological constructs will further expand this field of research. © 2017 World Obesity Federation.

Evaluation of the national 'Push Play' campaign in New Zealand--creating population awareness of physical activity.

PubMed

Bauman, Adrian; McLean, Grant; Hurdle, Deb; Walker, Sue; Boyd, John; van Aalst, Ingrid; Carr, Harriette

2003-08-08

Physical inactivity is considered to be as detrimental to public health as hypertension or tobacco use, but there is limited evidence on the impact of community-wide interventions in this area. This paper describes the impact of an initiative to increase physical activity at a population level in New Zealand. A media-led, community-wide intervention campaign was initiated by the Hillary Commission (now SPARC, Sport and Recreation New Zealand). The 'Push Play' campaign recommended 30 minutes of daily, moderate-intensity physical activity as fun, part of community life, and easy to achieve for New Zealand adults. In addition, there were community-level and primary care supporting programmes and events. Annual cross-sectional population surveys (1999-2002) monitored the impact of the campaign on message awareness, recognition of the Push Play logo, intention to be active, and recent activity. There were substantial increases in awareness of the Push Play message (30% in 1999 to 57% in 2002, p <0.001), and of the Push Play logo (14% to 52%, p <0.001). There were significant increases in the numbers of adults who intended to be more active (1.8% in 1999 to 9.4% in 2002). No sustained changes in physical activity levels were seen in these Push Play serial evaluation surveys, with 38.6% of the 1999 sample reporting 5+ days activity per week, increasing to 44.5% in 2000, but declining to 38.0% in 2002. The only significant difference in physical activity levels occurred from 1999 to 2000 (difference 5.8%, 95% CI 0.1%-11.6%). In an unrelated, much larger population survey, a 3% increase in physical activity participation was noted among adults between 1997 and 2001. The national Push Play campaign resulted in increases in message recognition and in intention to become more active. If sustained, efforts like this may have a long-term impact on adult activity patterns, leading to improved health outcomes and reduced health costs.

Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis.

PubMed

Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Banos, Oresti; Lee, Sungyoung

2017-04-23

Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recognition system to differentiate among some specific commuting activities (e.g., bus and subway) that normally involve similar postures. In this work, we recognize those activities by analyzing the vibrations of the vehicle in which the user is traveling. We extract natural vibration features of buses and subways to distinguish between them and address the confusion that can arise because the activities are both static in terms of user movement. We use the gyroscope to fix the accelerometer to the direction of gravity to achieve an orientation-free use of the sensor. We also propose a correction algorithm to increase the accuracy when used in free living conditions and a battery saving algorithm to consume less power without reducing performance. Our experimental results show that the proposed system can adequately recognize each activity, yielding better accuracy in the detection of bus and subway activities than existing methods.

Smartphone Location-Independent Physical Activity Recognition Based on Transportation Natural Vibration Analysis

PubMed Central

Hur, Taeho; Bang, Jaehun; Kim, Dohyeong; Banos, Oresti; Lee, Sungyoung

2017-01-01

Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recognition system to differentiate among some specific commuting activities (e.g., bus and subway) that normally involve similar postures. In this work, we recognize those activities by analyzing the vibrations of the vehicle in which the user is traveling. We extract natural vibration features of buses and subways to distinguish between them and address the confusion that can arise because the activities are both static in terms of user movement. We use the gyroscope to fix the accelerometer to the direction of gravity to achieve an orientation-free use of the sensor. We also propose a correction algorithm to increase the accuracy when used in free living conditions and a battery saving algorithm to consume less power without reducing performance. Our experimental results show that the proposed system can adequately recognize each activity, yielding better accuracy in the detection of bus and subway activities than existing methods. PMID:28441743

Varying behavior of different window sizes on the classification of static and dynamic physical activities from a single accelerometer.

PubMed

Fida, Benish; Bernabucci, Ivan; Bibbo, Daniele; Conforto, Silvia; Schmid, Maurizio

2015-07-01

Accuracy of systems able to recognize in real time daily living activities heavily depends on the processing step for signal segmentation. So far, windowing approaches are used to segment data and the window size is usually chosen based on previous studies. However, literature is vague on the investigation of its effect on the obtained activity recognition accuracy, if both short and long duration activities are considered. In this work, we present the impact of window size on the recognition of daily living activities, where transitions between different activities are also taken into account. The study was conducted on nine participants who wore a tri-axial accelerometer on their waist and performed some short (sitting, standing, and transitions between activities) and long (walking, stair descending and stair ascending) duration activities. Five different classifiers were tested, and among the different window sizes, it was found that 1.5 s window size represents the best trade-off in recognition among activities, with an obtained accuracy well above 90%. Differences in recognition accuracy for each activity highlight the utility of developing adaptive segmentation criteria, based on the duration of the activities. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Advancing from offline to online activity recognition with wearable sensors.

PubMed

Ermes, Miikka; Parkka, Juha; Cluitmans, Luc

2008-01-01

Activity recognition with wearable sensors could motivate people to perform a variety of different sports and other physical exercises. We have earlier developed algorithms for offline analysis of activity data collected with wearable sensors. In this paper, we present our current progress in advancing the platform for the existing algorithms to an online version, onto a PDA. Acceleration data are obtained from wireless motion bands which send the 3D raw acceleration signals via a Bluetooth link to the PDA which then performs the data collection, feature extraction and activity classification. As a proof-of-concept, the online activity system was tested with three subjects. All of them performed at least 5 minutes of each of the following activities: lying, sitting, standing, walking, running and cycling with an exercise bike. The average second-by-second classification accuracies for the subjects were 99%, 97%, and 82 %. These results suggest that earlier developed offline analysis methods for the acceleration data obtained from wearable sensors can be successfully implemented in an online activity recognition application.

Validation of a computerized 24-hour physical activity recall (24PAR) instrument with pattern-recognition activity monitors.

PubMed

Calabro, Miguel A; Welk, Gregory J; Carriquiry, Alicia L; Nusser, Sarah M; Beyler, Nicholas K; Mathews, Charles E

2009-03-01

The purpose of this study was to examine the validity of a computerized 24-hour physical activity recall instrument (24PAR). Participants (n=20) wore 2 pattern-recognition activity monitors (an IDEEA and a SenseWear Pro Armband) for a 24-hour period and then completed the 24PAR the following morning. Participants completed 2 trials, 1 while maintaining a prospective diary of their activities and 1 without a diary. The trials were counterbalanced and completed within a week from each other. Estimates of energy expenditure (EE) and minutes of moderate-to-vigorous physical activity (MVPA) were compared with the criterion measures using 3-way (method by gender by trial) mixed-model ANOVA analyses. For EE, pairwise correlations were high (r>.88), and there were no differences in estimates across methods. Estimates of MVPA were more variable, but correlations were still in the moderate to high range (r>.57). Average activity levels were significantly higher on the logging trial, but there was no significant difference in the accuracy of self-report on days with and without logging. The results of this study support the overall utility of the 24PAR for group-level estimates of daily EE and MVPA.

SVM-based multi-sensor fusion for free-living physical activity assessment.

PubMed

Liu, Shaopeng; Gao, Robert X; John, Dinesh; Staudenmayer, John; Freedson, Patty S

2011-01-01

This paper presents a sensor fusion method for assessing physical activity (PA) of human subjects, based on the support vector machines (SVMs). Specifically, acceleration and ventilation measured by a wearable multi-sensor device on 50 test subjects performing 13 types of activities of varying intensities are analyzed, from which the activity types and related energy expenditures are derived. The result shows that the method correctly recognized the 13 activity types 84.7% of the time, which is 26% higher than using a hip accelerometer alone. Also, the method predicted the associated energy expenditure with a root mean square error of 0.43 METs, 43% lower than using a hip accelerometer alone. Furthermore, the fusion method was effective in reducing the subject-to-subject variability (standard deviation of recognition accuracies across subjects) in activity recognition, especially when data from the ventilation sensor was added to the fusion model. These results demonstrate that the multi-sensor fusion technique presented is more effective in assessing activities of varying intensities than the traditional accelerometer-alone based methods.

Posture and activity recognition and energy expenditure estimation in a wearable platform.

PubMed

Sazonov, Edward; Hegde, Nagaraj; Browning, Raymond C; Melanson, Edward L; Sazonova, Nadezhda A

2015-07-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here, we describe the use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time recognition of various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we compare the use of support vector machines (SVM), multinomial logistic discrimination (MLD), and multilayer perceptrons (MLP) for posture and activity classification followed by activity-branched EE estimation. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a 4-h stay in a room calorimeter. MLD and MLP demonstrated activity classification accuracy virtually identical to SVM (∼ 95%) while reducing the running time and the memory requirements by a factor of >10 3. Comparison of per-minute EE estimation using activity-branched models resulted in accurate EE prediction (RMSE = 0.78 kcal/min for SVM and MLD activity classification, 0.77 kcal/min for MLP versus RMSE of 0.75 kcal/min for manual annotation). These results suggest that low-power computational algorithms can be successfully used for real-time physical activity monitoring and EE estimation on a wearable platform.

Evidence for the Activation of Sensorimotor Information during Visual Word Recognition: The Body-Object Interaction Effect

ERIC Educational Resources Information Center

Siakaluk, Paul D.; Pexman, Penny M.; Aguilera, Laura; Owen, William J.; Sears, Christopher R.

2008-01-01

We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a word's referent. A set of high BOI words (e.g., "mask") and a set of low BOI…

A modified active appearance model based on an adaptive artificial bee colony.

PubMed

Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.

Trajectory of Declines in Physical Activity in Community-Dwelling Older Women: Social Cognitive Influences

PubMed Central

Hall, Katherine S.; Motl, Robert W.; White, Siobhan M.; Wójcicki, Thomas R.; Hu, Liang; Doerksen, Shawna E.

2009-01-01

Studies examining physical activity behavior suggest that activity levels decline with age. Such declines are particularly problematic among older adults in light of the research suggesting a protective effect of physical activity on numerous physical health outcomes associated with independent living. Despite a growing recognition of the importance of a physically active lifestyle, little is known about the role of demographic and psychosocial variables on this trajectory of change. In this study, the roles played by outcome expectations, self-efficacy, and functional limitations on changes in physical activity levels over a 2-year period in older women were assessed using latent growth curve modeling. Data were obtained from 249 community-dwelling older women (M age = 68.12, n = 81 Black, and n = 168 White). Demographic, health status, and psychosocial data were collected via self-report upon entry into the study. Self-reported physical activity was assessed at baseline and again at 12 and 24 months. As expected, physical activity declined over the 2-year period. Self-efficacy demonstrated an indirect association with the trajectory of decline in physical activity through functional limitations. Importantly, the pattern of relationships appears independent of demographic factors and chronic health conditions. PMID:19528360

An investigation into non-invasive physical activity recognition using smartphones.

PubMed

Kelly, Daniel; Caulfield, Brian

2012-01-01

Technology utilized to automatically monitor Activities of Daily Living (ADL) could be a key component in identifying deviations from normal functional profiles and providing feedback on interventions aimed at improving health. However, if activity recognition systems are to be implemented in real world scenarios such as health and wellness monitoring, the activity sensing modality must unobtrusively fit the human environment rather than forcing humans to adhere to sensor specific conditions. Modern smart phones represent a ubiquitous computing device which has already undergone mainstream adoption. In this paper, we investigate the feasibility of using a modern smartphone, with limited placement constraints, as the sensing modality for an activity recognition system. A dataset of 4 subjects performing 7 activities, using varying sensor placement conditions, is utilized to investigate this. Initial experiments show that a decision tree classifier performs activity classification with precision and recall scores of 0.75 and 0.73 respectively. More importantly, as part of this initial experiment, 3 main problems, and subsequently 3 solutions, relating to unconstrained sensor placement were identified. Using our proposed solutions, classification precision and recall scores were improved by +13% and +14.6% respectively.

Enhanced multisensory integration and motor reactivation after active motor learning of audiovisual associations.

PubMed

Butler, Andrew J; James, Thomas W; James, Karin Harman

2011-11-01

Everyday experience affords us many opportunities to learn about objects through multiple senses using physical interaction. Previous work has shown that active motor learning of unisensory items enhances memory and leads to the involvement of motor systems during subsequent perception. However, the impact of active motor learning on subsequent perception and recognition of associations among multiple senses has not been investigated. Twenty participants were included in an fMRI study that explored the impact of active motor learning on subsequent processing of unisensory and multisensory stimuli. Participants were exposed to visuo-motor associations between novel objects and novel sounds either through self-generated actions on the objects or by observing an experimenter produce the actions. Immediately after exposure, accuracy, RT, and BOLD fMRI measures were collected with unisensory and multisensory stimuli in associative perception and recognition tasks. Response times during audiovisual associative and unisensory recognition were enhanced by active learning, as was accuracy during audiovisual associative recognition. The difference in motor cortex activation between old and new associations was greater for the active than the passive group. Furthermore, functional connectivity between visual and motor cortices was stronger after active learning than passive learning. Active learning also led to greater activation of the fusiform gyrus during subsequent unisensory visual perception. Finally, brain regions implicated in audiovisual integration (e.g., STS) showed greater multisensory gain after active learning than after passive learning. Overall, the results show that active motor learning modulates the processing of multisensory associations.

Sudden Event Recognition: A Survey

PubMed Central

Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

2013-01-01

Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

Thermal-to-visible face recognition using partial least squares.

PubMed

Hu, Shuowen; Choi, Jonghyun; Chan, Alex L; Schwartz, William Robson

2015-03-01

Although visible face recognition has been an active area of research for several decades, cross-modal face recognition has only been explored by the biometrics community relatively recently. Thermal-to-visible face recognition is one of the most difficult cross-modal face recognition challenges, because of the difference in phenomenology between the thermal and visible imaging modalities. We address the cross-modal recognition problem using a partial least squares (PLS) regression-based approach consisting of preprocessing, feature extraction, and PLS model building. The preprocessing and feature extraction stages are designed to reduce the modality gap between the thermal and visible facial signatures, and facilitate the subsequent one-vs-all PLS-based model building. We incorporate multi-modal information into the PLS model building stage to enhance cross-modal recognition. The performance of the proposed recognition algorithm is evaluated on three challenging datasets containing visible and thermal imagery acquired under different experimental scenarios: time-lapse, physical tasks, mental tasks, and subject-to-camera range. These scenarios represent difficult challenges relevant to real-world applications. We demonstrate that the proposed method performs robustly for the examined scenarios.

Recognition physical activities with optimal number of wearable sensors using data mining algorithms and deep belief network.

PubMed

Al-Fatlawi, Ali H; Fatlawi, Hayder K; Sai Ho Ling

2017-07-01

Daily physical activities monitoring is benefiting the health care field in several ways, in particular with the development of the wearable sensors. This paper adopts effective ways to calculate the optimal number of the necessary sensors and to build a reliable and a high accuracy monitoring system. Three data mining algorithms, namely Decision Tree, Random Forest and PART Algorithm, have been applied for the sensors selection process. Furthermore, the deep belief network (DBN) has been investigated to recognise 33 physical activities effectively. The results indicated that the proposed method is reliable with an overall accuracy of 96.52% and the number of sensors is minimised from nine to six sensors.

Designing a robust activity recognition framework for health and exergaming using wearable sensors.

PubMed

Alshurafa, Nabil; Xu, Wenyao; Liu, Jason J; Huang, Ming-Chun; Mortazavi, Bobak; Roberts, Christian K; Sarrafzadeh, Majid

2014-09-01

Detecting human activity independent of intensity is essential in many applications, primarily in calculating metabolic equivalent rates and extracting human context awareness. Many classifiers that train on an activity at a subset of intensity levels fail to recognize the same activity at other intensity levels. This demonstrates weakness in the underlying classification method. Training a classifier for an activity at every intensity level is also not practical. In this paper, we tackle a novel intensity-independent activity recognition problem where the class labels exhibit large variability, the data are of high dimensionality, and clustering algorithms are necessary. We propose a new robust stochastic approximation framework for enhanced classification of such data. Experiments are reported using two clustering techniques, K-Means and Gaussian Mixture Models. The stochastic approximation algorithm consistently outperforms other well-known classification schemes which validate the use of our proposed clustered data representation. We verify the motivation of our framework in two applications that benefit from intensity-independent activity recognition. The first application shows how our framework can be used to enhance energy expenditure calculations. The second application is a novel exergaming environment aimed at using games to reward physical activity performed throughout the day, to encourage a healthy lifestyle.

Evaluation of accelerometer based multi-sensor versus single-sensor activity recognition systems.

PubMed

Gao, Lei; Bourke, A K; Nelson, John

2014-06-01

Physical activity has a positive impact on people's well-being and it had been shown to decrease the occurrence of chronic diseases in the older adult population. To date, a substantial amount of research studies exist, which focus on activity recognition using inertial sensors. Many of these studies adopt a single sensor approach and focus on proposing novel features combined with complex classifiers to improve the overall recognition accuracy. In addition, the implementation of the advanced feature extraction algorithms and the complex classifiers exceed the computing ability of most current wearable sensor platforms. This paper proposes a method to adopt multiple sensors on distributed body locations to overcome this problem. The objective of the proposed system is to achieve higher recognition accuracy with "light-weight" signal processing algorithms, which run on a distributed computing based sensor system comprised of computationally efficient nodes. For analysing and evaluating the multi-sensor system, eight subjects were recruited to perform eight normal scripted activities in different life scenarios, each repeated three times. Thus a total of 192 activities were recorded resulting in 864 separate annotated activity states. The methods for designing such a multi-sensor system required consideration of the following: signal pre-processing algorithms, sampling rate, feature selection and classifier selection. Each has been investigated and the most appropriate approach is selected to achieve a trade-off between recognition accuracy and computing execution time. A comparison of six different systems, which employ single or multiple sensors, is presented. The experimental results illustrate that the proposed multi-sensor system can achieve an overall recognition accuracy of 96.4% by adopting the mean and variance features, using the Decision Tree classifier. The results demonstrate that elaborate classifiers and feature sets are not required to achieve high recognition accuracies on a multi-sensor system. Copyright © 2014 IPEM. Published by Elsevier Ltd. All rights reserved.

Hippocampus and nucleus accumbens activity during neutral word recognition related to trait physical anhedonia in patients with schizophrenia: an fMRI study.

PubMed

Lee, Jung Suk; Chun, Ji Won; Kang, Jee In; Kang, Dong-Il; Park, Hae-Jeong; Kim, Jae-Jin

2012-07-30

Emotional memory dysfunction may be associated with anhedonia in schizophrenia. This study aimed to investigate the neurobiological basis of emotional memory and its relationship with anhedonia in schizophrenia specifically in emotional memory relate brain regions of interest (ROIs) including the amygdala, hippocampus, nucleus accumbens, and ventromedial prefrontal cortex. Fourteen patients with schizophrenia and 16 healthy subjects performed a word-image associative encoding task, during which a neutral word was presented with a positive, neutral, or control image. Subjects underwent functional magnetic resonance imaging while performing the recognition task. Correlation analyses were performed between the percent signal change (PSC) in the ROIs and the anhedonia scores. We found no group differences in recognition accuracy and reaction time. The PSC of the hippocampus in the positive and neutral conditions, and the PSC in the nucleus accumbens in the control condition, appeared to be negatively correlated with the Physical Anhedonia Scale (PAS) scores in patients with schizophrenia, while significant correlations with the PAS scores were not observed in healthy subjects. This study provides further evidences of the role of the hippocampus and nucleus accumbens in trait physical anhedonia and possible associations between emotional memory deficit and trait physical anhedonia in patients with schizophrenia. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Emotion Recognition in Fathers and Mothers at High-Risk for Child Physical Abuse

ERIC Educational Resources Information Center

Asla, Nagore; de Paul, Joaquin; Perez-Albeniz, Alicia

2011-01-01

Objective: The present study was designed to determine whether parents at high risk for physical child abuse, in comparison with parents at low risk, show deficits in emotion recognition, as well as to examine the moderator effect of gender and stress on the relationship between risk for physical child abuse and emotion recognition. Methods: Based…

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

PubMed Central

Othman, Zulaiha Ali

2014-01-01

Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition. PMID:25165748

Introducing a modular activity monitoring system.

PubMed

Reiss, Attila; Stricker, Didier

2011-01-01

In this paper, the idea of a modular activity monitoring system is introduced. By using different combinations of the system's three modules, different functionality becomes available: 1) a coarse intensity estimation of physical activities 2) different features based on HR-data and 3) the recognition of basic activities and postures. 3D-accelerometers--placed on lower arm, chest and foot--and a heart rate monitor were used as sensors. A dataset with 8 subjects and 14 different activities was recorded to evaluate the performance of the system. The overall performance on the intensity estimation task, relying on the chest-worn accelerometer and the HR-monitor, was 94.37%. The overall performance on the activity recognition task, using all three accelerometer placements and the HR-monitor, was 90.65%. This paper also gives an analysis of the importance of different accelerometer placements and the importance of a HR-monitor for both tasks.

``Physics and the girly girl—there is a contradiction somewhere'': doctoral students' positioning around discourses of gender and competence in physics

NASA Astrophysics Data System (ADS)

Gonsalves, Allison J.

2014-06-01

Doctoral physics students have stories about what kinds of actions, behaviours and ways of doing physics allow individuals to be recognized as physicists. Viewing a physics department as a case study, and individual participants as embedded cases, this study used a sociocultural approach to examine the ways doctoral students construct these stories about becoming physicists. Through observations, photo-elicitation, and life history interviews, eleven men and women shared stories about their experiences with physics, and the contexts that have enabled or constrained their trajectories into doctoral physics. The results of this study revealed the salience of recognition in the constitution of physicist identities; but how recognition was achieved often entailed the reproduction or reworking of persistent discourses of gender norms. Various interchangeable forms of competence (technical, analytical, and academic) emerged as assets that can be used to achieve recognition in this physics community. However, competence was not the only means by which one might be recognized as a physicist. Contributing to the possibility for recognition was the performance of stereotypical Discourses for physicist that relied on traditional gender norms for the field. The results demonstrated that achieving recognition as a competent physicist often involved a complex negotiation of gender roles and the practice of physics.

Functional dissociation of the left and right fusiform gyrus in self-face recognition.

PubMed

Ma, Yina; Han, Shihui

2012-10-01

It is well known that the fusiform gyrus is engaged in face perception, such as the processes of face familiarity and identity. However, the functional role of the fusiform gyrus in face processing related to high-level social cognition remains unclear. The current study assessed the functional role of individually defined fusiform face area (FFA) in the processing of self-face physical properties and self-face identity. We used functional magnetic resonance imaging to monitor neural responses to rapidly presented face stimuli drawn from morph continua between self-face (Morph 100%) and a gender-matched friend's face (Morph 0%) in a face recognition task. Contrasting Morph 100% versus Morph 60% that differed in self-face physical properties but were both recognized as the self uncovered neural activity sensitive to self-face physical properties in the left FFA. Contrasting Morphs 50% that were recognized as the self versus a friend on different trials revealed neural modulations associated with self-face identity in the right FFA. Moreover, the right FFA activity correlated with the frequency of recognizing Morphs 50% as the self. Our results provide evidence for functional dissociations of the left and right FFAs in the representations of self-face physical properties and self-face identity. Copyright © 2011 Wiley Periodicals, Inc.

How consumer physical activity monitors could transform human physiology research.

PubMed

Wright, Stephen P; Hall Brown, Tyish S; Collier, Scott R; Sandberg, Kathryn

2017-03-01

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O 2 , and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing. Copyright © 2017 the American Physiological Society.

How consumer physical activity monitors could transform human physiology research

PubMed Central

Hall Brown, Tyish S.; Collier, Scott R.; Sandberg, Kathryn

2017-01-01

A sedentary lifestyle and lack of physical activity are well-established risk factors for chronic disease and adverse health outcomes. Thus, there is enormous interest in measuring physical activity in biomedical research. Many consumer physical activity monitors, including Basis Health Tracker, BodyMedia Fit, DirectLife, Fitbit Flex, Fitbit One, Fitbit Zip, Garmin Vivofit, Jawbone UP, MisFit Shine, Nike FuelBand, Polar Loop, Withings Pulse O2, and others have accuracies similar to that of research-grade physical activity monitors for measuring steps. This review focuses on the unprecedented opportunities that consumer physical activity monitors offer for human physiology and pathophysiology research because of their ability to measure activity continuously under real-life conditions and because they are already widely used by consumers. We examine current and potential uses of consumer physical activity monitors as a measuring or monitoring device, or as an intervention in strategies to change behavior and predict health outcomes. The accuracy, reliability, reproducibility, and validity of consumer physical activity monitors are reviewed, as are limitations and challenges associated with using these devices in research. Other topics covered include how smartphone apps and platforms, such as the Apple ResearchKit, can be used in conjunction with consumer physical activity monitors for research. Lastly, the future of consumer physical activity monitors and related technology is considered: pattern recognition, integration of sleep monitors, and other biosensors in combination with new forms of information processing. PMID:28052867

Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement.

PubMed

Chiang, Shu-Yin; Kan, Yao-Chiang; Chen, Yun-Shan; Tu, Ying-Ching; Lin, Hsueh-Chun

2016-12-03

Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC.

Fuzzy Computing Model of Activity Recognition on WSN Movement Data for Ubiquitous Healthcare Measurement

PubMed Central

Chiang, Shu-Yin; Kan, Yao-Chiang; Chen, Yun-Shan; Tu, Ying-Ching; Lin, Hsueh-Chun

2016-01-01

Ubiquitous health care (UHC) is beneficial for patients to ensure they complete therapeutic exercises by self-management at home. We designed a fuzzy computing model that enables recognizing assigned movements in UHC with privacy. The movements are measured by the self-developed body motion sensor, which combines both accelerometer and gyroscope chips to make an inertial sensing node compliant with a wireless sensor network (WSN). The fuzzy logic process was studied to calculate the sensor signals that would entail necessary features of static postures and dynamic motions. Combinations of the features were studied and the proper feature sets were chosen with compatible fuzzy rules. Then, a fuzzy inference system (FIS) can be generated to recognize the assigned movements based on the rules. We thus implemented both fuzzy and adaptive neuro-fuzzy inference systems in the model to distinguish static and dynamic movements. The proposed model can effectively reach the recognition scope of the assigned activity. Furthermore, two exercises of upper-limb flexion in physical therapy were applied for the model in which the recognition rate can stand for the passing rate of the assigned motions. Finally, a web-based interface was developed to help remotely measure movement in physical therapy for UHC. PMID:27918482

Cognitive function and the agreement between self-reported and accelerometer-accessed physical activity.

PubMed

Herbolsheimer, Florian; Riepe, Matthias W; Peter, Richard

2018-02-21

Numerous studies have reported weak or moderate correlations between self-reported and accelerometer-assessed physical activity. One explanation is that self-reported physical activity might be biased by demographic, cognitive or other factors. Cognitive function is one factor that could be associated with either overreporting or underreporting of daily physical activity. Difficulties in remembering past physical activities might result in recall bias. Thus, the current study examines whether the cognitive function is associated with differences between self-reported and accelerometer-assessed physical activity. Cross-sectional data from the population-based Activity and Function in the Elderly in Ulm study (ActiFE) were used. A total of 1172 community-dwelling older adults (aged 65-90 years) wore a uniaxial accelerometer (activPAL unit) for a week. Additionally, self-reported physical activity was assessed using the LASA Physical Activity Questionnaire (LAPAQ). Cognitive function was measured with four items (immediate memory, delayed memory, recognition memory, and semantic fluency) from the Consortium to Establish a Registry for Alzheimer's Disease Total Score (CERAD-TS). Mean differences of self-reported and accelerometer-assessed physical activity (MPA) were associated with cognitive function in men (r s  = -.12, p = .002) but not in women. Sex-stratified multiple linear regression analyses showed that MPA declined with high cognitive function in men (β = -.13; p = .015). Results suggest that self-reported physical activity should be interpreted with caution in older populations, as cognitive function was one factor that explained the differences between objective and subjective physical activity measurements.

Model driven mobile care for patients with type 1 diabetes.

PubMed

Skrøvseth, Stein Olav; Arsand, Eirik; Godtliebsen, Fred; Joakimsen, Ragnar M

2012-01-01

We gathered a data set from 30 patients with type 1 diabetes by giving the patients a mobile phone application, where they recorded blood glucose measurements, insulin injections, meals, and physical activity. Using these data as a learning data set, we describe a new approach of building a mobile feedback system for these patients based on periodicities, pattern recognition, and scale-space trends. Most patients have important patterns for periodicities and trends, though better resolution of input variables is needed to provide useful feedback using pattern recognition.

Embedding Positive Behavior Intervention and Supports in Afterschool Programs

ERIC Educational Resources Information Center

Farrell, Anne F.; Collier-Meek, Melissa A.; Pons, Shelby R.

2013-01-01

There is growing recognition that after-school programs (ASPs) provide opportunities for positive youth development. Many ASPs focus on behavior and socio-emotional challenges, provide evidence-based interventions to improve homework completion and academic skills, and offer physical activities and nutritious foods. Generally speaking, ASPs offer…

High-emulation mask recognition with high-resolution hyperspectral video capture system

NASA Astrophysics Data System (ADS)

Feng, Jiao; Fang, Xiaojing; Li, Shoufeng; Wang, Yongjin

2014-11-01

We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

Emotion recognition in fathers and mothers at high-risk for child physical abuse.

PubMed

Asla, Nagore; de Paúl, Joaquín; Pérez-Albéniz, Alicia

2011-09-01

The present study was designed to determine whether parents at high risk for physical child abuse, in comparison with parents at low risk, show deficits in emotion recognition, as well as to examine the moderator effect of gender and stress on the relationship between risk for physical child abuse and emotion recognition. Based on their scores on the Abuse Scale of the CAP Inventory (Milner, 1986), 64 parents at high risk (24 fathers and 40 mothers) and 80 parents at low risk (40 fathers and 40 mothers) for physical child abuse were selected. The Subtle Expression Training Tool/Micro Expression Training Tool (Ekman, 2004a, 2004b) and the Diagnostic Analysis of Nonverbal Accuracy II (Nowicki & Carton, 1993) were used to assess emotion recognition. As expected, parents at high risk, in contrast to parents at low risk, showed deficits in emotion recognition. However, differences between high- and low-risk participants were observed only for fathers, but not for mothers. Whereas fathers at high risk for physical child abuse made more errors than mothers at high risk, no differences between mothers at low risk and fathers at low risk were found. No interaction between stress, gender, and risk status was observed for errors in emotion recognition. The present findings, if confirmed with physical abusers, could be helpful to further our understanding of deficits in processing information of physically abusive parents and to develop treatment strategies specifically focused on emotion recognition. Moreover, if gender differences can be confirmed, the findings could be helpful to develop specific treatment programs for abusive fathers. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effect of physical workload and modality of information presentation on pattern recognition and navigation task performance by high-fit young males.

PubMed

Zahabi, Maryam; Zhang, Wenjuan; Pankok, Carl; Lau, Mei Ying; Shirley, James; Kaber, David

2017-11-01

Many occupations require both physical exertion and cognitive task performance. Knowledge of any interaction between physical demands and modalities of cognitive task information presentation can provide a basis for optimising performance. This study examined the effect of physical exertion and modality of information presentation on pattern recognition and navigation-related information processing. Results indicated males of equivalent high fitness, between the ages of 18 and 34, rely more on visual cues vs auditory or haptic for pattern recognition when exertion level is high. We found that navigation response time was shorter under low and medium exertion levels as compared to high intensity. Navigation accuracy was lower under high level exertion compared to medium and low levels. In general, findings indicated that use of the haptic modality for cognitive task cueing decreased accuracy in pattern recognition responses. Practitioner Summary: An examination was conducted on the effect of physical exertion and information presentation modality in pattern recognition and navigation. In occupations requiring information presentation to workers, who are simultaneously performing a physical task, the visual modality appears most effective under high level exertion while haptic cueing degrades performance.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Physical activity is associated with the physical, psychological, social and environmental quality of life in people with mental health problems in a low resource setting.

PubMed

Vancampfort, Davy; Van Damme, Tine; Probst, Michel; Firth, Joseph; Stubbs, Brendon; Basangwa, David; Mugisha, James

2017-12-01

There is a growing recognition of the importance of encouraging patients with mental health problems to become more active as an efficacious strategy to reduce the disability-associated burden. The aim of the current study was to investigate if there are differences in quality of life (QoL) outcomes between people with mental health problems that do and do not meet the recommendations of 150min per week of physical activity. 109 (36♀) Ugandan in- and outpatients (mean age = 34.2 ± 10.2 years) (depression = 7, bipolar disorder = 31, schizophrenia = 21, alcohol use disorder = 50) completed the Physical Activity Vital Sign (PAVS) method and World Health Organization Quality of Life Assessment brief version. Those who did not achieve the minimum physical activity recommendations as assessed by the PAVS (n = 63) had a lower physical, psychological, social and environmental QoL. The current data offer further evidence that the PAVS method might be an important risk identification tool in people with mental health problems. The feasibility and acceptability of the PAVS may help promote the importance of physical activity assessment and prescription as a core part of the treatment of mental health problems in LMICs. Copyright © 2017 Elsevier B.V. All rights reserved.

Potentially Modifiable Factors Associated With Physical Activity in Individuals With Multiple Sclerosis.

PubMed

Reider, Nadia; Salter, Amber R; Cutter, Gary R; Tyry, Tuula; Marrie, Ruth Ann

2017-04-01

Physical activity levels among persons with multiple sclerosis (MS) are worryingly low. We aimed to identify the factors associated with physical activity for people with MS, with an emphasis on factors that have not been studied previously (bladder and hand dysfunction) and are potentially modifiable. This study was a secondary analysis of data collected in the spring of 2012 during the North American Research Committee on Multiple Sclerosis (NARCOMS) Registry. NARCOMS participants were surveyed regarding smoking using questions from the Behavioral Risk Factor Surveillance Survey; disability using the Patient Determined Disease Steps; fatigue, cognition, spasticity, sensory, bladder, vision and hand function using self-reported Performance Scales; health literacy using the Medical Term Recognition Test; and physical activity using questions from the Health Information National Trends Survey. We used a forward binary logistic regression to develop a predictive model in which physical activity was the outcome variable. Of 8,755 respondents, 1,707 (19.5%) were classified as active and 7,068 (80.5%) as inactive. In logistic regression, being a current smoker, moderate or severe level of disability, depression, fatigue, hand, or bladder dysfunction and minimal to mild spasticity were associated with lower odds of meeting physical activity guidelines. MS type was not linked to activity level. Several modifiable clinical and lifestyle factors influenced physical activity in MS. Prospective studies are needed to evaluate whether modification of these factors can increase physical activity participation in persons with MS. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Place of residence as a factor differentiating physical activity in the life style of Ukrainian students.

PubMed

Bergier, Józef; Bergier, Barbara; Tsos, Anatolii

2016-12-23

Determining the state of physical activity of societies as an important component of a health promoting life style is a very up-to-date problem. Studies of physical activity among students, the future elites in their environments, become of increasing importance. An important problem is the recognition of factors differentiating this activity on the example of place of residence. For this purpose, the study covered 2,125 students (60.8% females and 39.2% males) from the National Institute in Lutsk, Ukraine, aged 17-22 (mean age: 20.4). The method of a diagnostic survey was applied which included the International Physical Activity Questionnaire (IPAQ). The following measures of physical activity according to the place of residence (rural area, small town with a population up to 100,000; medium-size town - 100,000-200,000 inhabitants; large city - over 200,000) were taken into consideration: level of physical activity, self-reported physical fitness, sports disciplines practiced by the respondents, and those which they would like to practice, and the BMI, and leisure time possessed. The study showed that the place of residence positively differentiated physical activity among students from medium-size towns and rural areas, compared to their contemporaries from small towns and large cities. Significant differences were also found with respect to the BMI, which was significantly less favourable among respondents from the rural environment. However, no differences were observed between the place of residence for leisure time, self-reported physical activity, and forms of physical activity practiced, and those which the respondents would like to practice.

Low-Cost, Scalable Classroom-Based Approach to Promoting Physical Activity in Preschool Children

PubMed Central

McCrady-Spitzer, Shelly K; Sagdalen, Vanessa; Manohar, Chinmay U; Levine, James A

2017-01-01

Background This study examined the impact of short activity breaks in preschool children. The hypotheses were that preschool children receiving three five-minute activity breaks per day would increase (a) school time physical activity and (b) education scores compared to a control group not receiving the intervention. Methods For 8 weeks, the Intervention Group (n = 13) incorporated three 5-minute activity breaks into their classroom time while the Control Group (n = 12) did not incorporate the activity breaks. Physical activity was measured using a triaxial accelerometer. Education was assessed using standardized methods. Findings After 8 weeks, the preschool children in the Intervention Group increased their school time physical activity from 11,641 ± (SD) 1,368 Acceleration Units (AU)/ hour to 16,058 ± 2,253 AU/hour (P < 0.001). The children in the control group did not increase their physical activity (11,379 ± 2,427 cf 11,624 ± 2,441; ns). Students in the Intervention Group improved their education scores more than students in the control group (18 ± 12 cf 8 ± 7 points, P = 0.01); Letter Recognition improved in particular (9 ± 6 cf 2 ± 4 points, P = 0.001). Conclusions The incorporation of three 5-minute activity breaks was associated with increased school time physical activity and improved learning. PMID:28936491

The role of chronic physical exercise and selective attention at encoding on implicit and explicit memory.

PubMed

Padilla, Concepción; Mayas, Julia; Ballesteros, Soledad; Andrés, Pilar

2017-09-01

Despite the evidence revealing benefits of chronic cardiovascular exercise on executive functions, little research has been conducted on long-term memory. We aimed to investigate the effect of physical exercise on implicit and explicit memory when attention was modulated at encoding in two groups of active and sedentary participants. With this purpose, attention was manipulated in a similar way in the implicit and explicit memory tasks by presenting picture outlines of two familiar objects, one in blue and the other in green, and participants were asked to pay attention only to one of them. Implicit memory was assessed through conceptual priming and explicit memory through a free recall task followed by recognition. The results did not reveal significant differences between groups in conceptual priming or free recall. However, in recognition, while both groups had similar discrimination for attended stimuli, active participants showed lower discrimination between unattended and new stimuli. These results suggested that exercise may have effects on specific cognitive processes, that is, that active participants may suppress non-relevant information better than sedentary participants, making the discrimination between unattended and new items more difficult.

Physical Principles of the Method for Determination of Geometrical Characteristics and Particle Recognition in Digital Holography

NASA Astrophysics Data System (ADS)

Dyomin, V. V.; Polovtsev, I. G.; Davydova, A. Yu.

2018-03-01

The physical principles of a method for determination of geometrical characteristics of particles and particle recognition based on the concepts of digital holography, followed by processing of the particle images reconstructed from the digital hologram, using the morphological parameter are reported. An example of application of this method for fast plankton particle recognition is given.

Step Detection and Activity Recognition Accuracy of Seven Physical Activity Monitors

PubMed Central

Storm, Fabio A.; Heller, Ben W.; Mazzà, Claudia

2015-01-01

The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration. The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications. PMID:25789630

Step detection and activity recognition accuracy of seven physical activity monitors.

PubMed

Storm, Fabio A; Heller, Ben W; Mazzà, Claudia

2015-01-01

The aim of this study was to compare the seven following commercially available activity monitors in terms of step count detection accuracy: Movemonitor (Mc Roberts), Up (Jawbone), One (Fitbit), ActivPAL (PAL Technologies Ltd.), Nike+ Fuelband (Nike Inc.), Tractivity (Kineteks Corp.) and Sensewear Armband Mini (Bodymedia). Sixteen healthy adults consented to take part in the study. The experimental protocol included walking along an indoor straight walkway, descending and ascending 24 steps, free outdoor walking and free indoor walking. These tasks were repeated at three self-selected walking speeds. Angular velocity signals collected at both shanks using two wireless inertial measurement units (OPAL, ADPM Inc) were used as a reference for the step count, computed using previously validated algorithms. Step detection accuracy was assessed using the mean absolute percentage error computed for each sensor. The Movemonitor and the ActivPAL were also tested within a nine-minute activity recognition protocol, during which the participants performed a set of complex tasks. Posture classifications were obtained from the two monitors and expressed as a percentage of the total task duration. The Movemonitor, One, ActivPAL, Nike+ Fuelband and Sensewear Armband Mini underestimated the number of steps in all the observed walking speeds, whereas the Tractivity significantly overestimated step count. The Movemonitor was the best performing sensor, with an error lower than 2% at all speeds and the smallest error obtained in the outdoor walking. The activity recognition protocol showed that the Movemonitor performed best in the walking recognition, but had difficulty in discriminating between standing and sitting. Results of this study can be used to inform choice of a monitor for specific applications.

The Association of Aging and Aerobic Fitness With Memory

PubMed Central

Bullock, Alexis M.; Mizzi, Allison L.; Kovacevic, Ana; Heisz, Jennifer J.

2018-01-01

The present study examined the differential effects of aging and fitness on memory. Ninety-five young adults (YA) and 81 older adults (OA) performed the Mnemonic Similarity Task (MST) to assess high-interference memory and general recognition memory. Age-related differences in high-interference memory were observed across the lifespan, with performance progressively worsening from young to old. In contrast, age-related differences in general recognition memory were not observed until after 60 years of age. Furthermore, OA with higher aerobic fitness had better high-interference memory, suggesting that exercise may be an important lifestyle factor influencing this aspect of memory. Overall, these findings suggest different trajectories of decline for high-interference and general recognition memory, with a selective role for physical activity in promoting high-interference memory. PMID:29593524

Mobile Health Advances in Physical Activity, Fitness, and Atrial Fibrillation: Moving Hearts.

PubMed

McConnell, Michael V; Turakhia, Mintu P; Harrington, Robert A; King, Abby C; Ashley, Euan A

2018-06-12

The growing recognition that "health" takes place outside of the hospital and clinic, plus recent advances in mobile and wearable devices, have propelled the field of mobile health (mHealth). Cardiovascular disease and prevention are major opportunities for mHealth, as mobile devices can monitor key physiological signals (e.g., physical activity, heart rate and rhythm) for promoting healthy behaviors, detecting disease, and aid in ongoing care. In this review, the authors provide an update on cardiovascular mHealth by highlighting recent progress and challenges with mobile and wearable devices for assessing and promoting physical activity and fitness, and for monitoring heart rate and rhythm for the detection and management of atrial fibrillation. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

APS Goes to ComicCon and Other Tales: Reaching out for Physics

NASA Astrophysics Data System (ADS)

Kirby, Kate

2012-10-01

Broadly interpreting the core mission of APS ``to advance and diffuse the knowledge of physics", APS carries out programmatic activities in Education, Outreach, International Affairs, Public Affairs, and Advocacy, which benefit the physics community as well as society at large. These programs are highly valued by APS members who know about them, but the challenge has been to find ways to effectively communicate to our members about all the good things we are doing. APS programs have also achieved significant recognition in the external community for their outstanding quality and success. I will describe several examples of how we ``reach out" to promote physics and physics education in a variety of venues.

The influence of rural home and neighborhood environments on healthy eating, physical activity, and weight.

PubMed

Kegler, Michelle C; Swan, Deanne W; Alcantara, Iris; Feldman, Lynne; Glanz, Karen

2014-02-01

Despite the recognition that environments play a role in shaping physical activity and healthy eating behaviors, relatively little research has focused on rural homes and neighborhoods as important settings for obesity prevention. This study, conducted through community-based participatory research, used a social ecological model to examine how home and neighborhood food and physical activity environments were associated with weight status among rural-dwelling adults. Data were from a cross-sectional survey of White and African American adults (n = 513) aged 40-70 years living in rural southwest Georgia. Data were analyzed using measured variable path analysis, a form of structural equation modeling. The results support a social ecological approach to obesity prevention. Physical activity had a direct effect on BMI; self-efficacy, family support for physical activity, and household inventory of physical activity equipment also had direct effects on physical activity. Neighborhood walkability had an indirect effect on physical activity through self-efficacy and family social support. Although neither fruit and vegetable intake nor fat intake had direct effects on BMI, self-efficacy and household food inventories had direct effects on dietary behavior. Perceived access to healthy foods in the neighborhood had an indirect effect on healthy eating and a direct effect on weight; neighborhood cohesion had an indirect effect on healthy eating through self-efficacy. Overall, individual factors and home environments tended to exhibit direct effects on behavior, and neighborhood variables more often exhibited an indirect effect.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

PubMed Central

Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

2012-01-01

Smart homes for the aging population have recently started attracting the attention of the research community. The “health state” of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario. PMID:26007727

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data.

PubMed

Nef, Tobias; Urwyler, Prabitha; Büchler, Marcel; Tarnanas, Ioannis; Stucki, Reto; Cazzoli, Dario; Müri, René; Mosimann, Urs

2015-05-21

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.

Getting to know the competition: a content analysis of publicly and corporate funded physical activity advertisements.

PubMed

Berry, Tanya R; McCarville, Ron E; Rhodes, Ryan E

2008-03-01

The purpose of this research was to conduct a content analysis of physical activity advertisements in an effort to determine which advertisements were more likely to include features that may attract and maintain attention levels. Fifty-seven advertisements were collected from top circulation Canadian magazines. The advertisements ranged from publicly funded health promotion pieces to corporate sponsored advertisements using physical activity to sell a product. Advertisements were examined for textual and pictorial factors thought to increase attention allocated to advertising of this nature. Only two public health advertisements were found, and the majority of advertisements (57.9%) were from commercial advertisers using physical activity images to sell products or to encourage brand recognition. The advertisements originating with the private sector tended to possess most of the characteristics thought to attract the attention of readers. Once this attention was gained, however, most of these advertisements failed to highlight the benefits of physical activity. As a result, the positive effect of these advertisements may have been compromised. Public health advertisements were so infrequent that we could not compare their characteristics with those originating with the private sector. The characteristics with those we did find were inconsistent with those thought to attract and maintain attention levels. Results are discussed in terms of potential implications for promoting physical activity.

Physicality and Language Learning

ERIC Educational Resources Information Center

Park, Jaeuk; Seedhouse, Paul; Seedhouse, Rob; Kiaer, Jieun

2016-01-01

The study draws on the digital technology which allows users to be able to learn both linguistic and non-linguistic skills at the same time. Activity recognition as well as wireless sensor technology, similar to a Nintendo Wii, is embedded or attached to the equipment and ingredients, allowing users to detect and evaluate progress as they carry…

Prevention, Recognition and Treatment of Common Recess Injuries

ERIC Educational Resources Information Center

Linker, Jenny M.; David, Shannon L.

2017-01-01

When examining recess within a school's comprehensive school physical activity program (CSPAP), stakeholders should consider that 30% to 70% of school injuries occur during this part of the school day (Posner, 2000). Thus, existing frameworks to prevent and manage recess injuries may require a thorough review. The purpose of this article is to…

Recognition of Values-Based Constructs in a Summer Physical Activity Program.

ERIC Educational Resources Information Center

Watson, Doris L.; Newton, Maria; Kim, Mi-Sook

2003-01-01

Examined the extent to which participants in a summer sports camp embraced values-based constructs, noting the relationship between perceptions of values-based constructs and affect and attitude. Data on ethnically diverse 10-13-year-olds indicated that care for others/goal setting, self-responsibility, and self-control/respect positively related…

National Athletic Trainers' Association Releases New Guidelines for Exertional Heat Illnesses: What School Nurses Need to Know.

PubMed

VanScoy, Rachel M; DeMartini, Julie K; Casa, Douglas J

2016-05-01

Exertional heat illnesses (EHI) occur in various populations and settings. Within a school setting, there are student athletes who take part in physical activity where the risk of EHI is increased. The National Athletic Trainers' Association (NATA) released an updated position statement on EHI in September of 2015. This article is a summary of the position statement. The sports medicine team, including school nurses and athletic trainers, provides quality health care to these physically active individuals. Thus, it is important for school nurses to understand the prevention, recognition, and treatment of EHI. © 2016 The Author(s).

Recognizing familiar objects by hand and foot: Haptic shape perception generalizes to inputs from unusual locations and untrained body parts.

PubMed

Lawson, Rebecca

2014-02-01

The limits of generalization of our 3-D shape recognition system to identifying objects by touch was investigated by testing exploration at unusual locations and using untrained effectors. In Experiments 1 and 2, people found identification by hand of real objects, plastic 3-D models of objects, and raised line drawings placed in front of themselves no easier than when exploration was behind their back. Experiment 3 compared one-handed, two-handed, one-footed, and two-footed haptic object recognition of familiar objects. Recognition by foot was slower (7 vs. 13 s) and much less accurate (9 % vs. 47 % errors) than recognition by either one or both hands. Nevertheless, item difficulty was similar across hand and foot exploration, and there was a strong correlation between an individual's hand and foot performance. Furthermore, foot recognition was better with the largest 20 of the 80 items (32 % errors), suggesting that physical limitations hampered exploration by foot. Thus, object recognition by hand generalized efficiently across the spatial location of stimuli, while object recognition by foot seemed surprisingly good given that no prior training was provided. Active touch (haptics) thus efficiently extracts 3-D shape information and accesses stored representations of familiar objects from novel modes of input.

Recognition of Time Stamps on Full-Disk Hα Images Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Xu, Y.; Huang, N.; Jing, J.; Liu, C.; Wang, H.; Fu, G.

2016-12-01

Observation and understanding of the physics of the 11-year solar activity cycle and 22-year magnetic cycle are among the most important research topics in solar physics. The solar cycle is responsible for magnetic field and particle fluctuation in the near-earth environment that have been found increasingly important in affecting the living of human beings in the modern era. A systematic study of large-scale solar activities, as made possible by our rich data archive, will further help us to understand the global-scale magnetic fields that are closely related to solar cycles. The long-time-span data archive includes both full-disk and high-resolution Hα images. Prior to the widely use of CCD cameras in 1990s, 35-mm films were the major media to store images. The research group at NJIT recently finished the digitization of film data obtained by the National Solar Observatory (NSO) and Big Bear Solar Observatory (BBSO) covering the period of 1953 to 2000. The total volume of data exceeds 60 TB. To make this huge database scientific valuable, some processing and calibration are required. One of the most important steps is to read the time stamps on all of the 14 million images, which is almost impossible to be done manually. We implemented three different methods to recognize the time stamps automatically, including Optical Character Recognition (OCR), Classification Tree and TensorFlow. The latter two are known as machine learning algorithms which are very popular now a day in pattern recognition area. We will present some sample images and the results of clock recognition from all three methods.

Performance and Usage of Biometrics in a Testbed Environment for Tactical Purposes

DTIC Science & Technology

2006-12-01

19 c. Facial Recognition ..................................................................20...geometry, iris recognition, and facial recognition (Layman’s, 2005). Behavioral biometrics can be described not as a physical characteristic, but are...are at: • Correction facilities • Department of Motor Vehicle • Military checkpoints • POW facilities c. Facial Recognition Facial recognition is

Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers.

PubMed

García-Massó, X; Serra-Añó, P; Gonzalez, L M; Ye-Lin, Y; Prats-Boluda, G; Garcia-Casado, J

2015-10-01

This was a cross-sectional study. The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI). The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, chest and waist. The activities were grouped into five categories: sedentary, locomotion, housework, body transfers and moderate physical activity. Different machine learning algorithms were used to develop individual and group activity classifiers from the acceleration data for different combinations of number and position of the accelerometers. We found that although the accuracy of the classifiers for individual activities was moderate (55-72%), with higher values for a greater number of accelerometers, grouped activities were correctly classified in a high percentage of cases (83.2-93.6%). With only two accelerometers and the quadratic discriminant analysis algorithm we achieved a reasonably accurate group activity recognition system (>90%). Such a system with the minimum of intervention would be a valuable tool for studying physical activity in individuals with SCI.

Physical Activity Programs in Long Day Care and Family Day Care Settings

ERIC Educational Resources Information Center

Lawlis, Tanya; Mikhailovich, Katja; Morrison, Paul

2008-01-01

In the past 10 years the prevalence of childhood obesity has increased considerably and there is growing recognition of the need to establish positive attitudes to healthy lifestyle practices from an early age if this trend is to be reversed. Childcare centres provide ideal environments from which to develop these positive attitudes. A literature…

Determinants of exercise among children. II. A longitudinal analysis.

PubMed

DiLorenzo, T M; Stucky-Ropp, R C; Vander Wal, J S; Gotham, H J

1998-01-01

Research has demonstrated that physical activity serves an important preventive function against the development of cardiovascular disease. The recognition that U.S. children are often sedentary, coupled with the observation that physical activity habits tend to persist into adulthood, has prompted the investigation of exercise determinants consistent with social learning theory. The purposes of the present study were to identify social learning variables relevant to children's exercise and to explore the longitudinal predictive value of the determinants. Data were collected from 111 families (N = 54 girls, N = 57 boys) who were interviewed in both Phase 1 (fifth and sixth grades) and Phase 2 (eight and ninth grades) of this study. Data from mothers (N = 111) were collected during both phases; data from 80 fathers were collected at Phase 2 only. The results of simultaneous stepwise regression analyses indicated that child's enjoyment of physical activity was the only consistent predictor of physical activity during Phase 1. At Phase 2, child's exercise knowledge, mother's physical activity, and child's and mother's friend modeling/support emerged as predictors for girls. For boys, child's self-efficacy for physical activity, exercise knowledge, parental modeling, and interest in sports media were important. Longitudinally, mother's self-efficacy, barriers to exercise, enjoyment of physical activity, and child's self-efficacy for physical activity were important for girls. Only child's exercise knowledge predicted boys' physical activity. The addition of information from fathers nearly doubled the explanatory power of the predictors for both genders. Socialization in the family unit exerts a tremendous influence on health-related behaviors such as exercise. The relative importance of determinants seems to differ for girls and boys and the pattern of these determinants appears to change over time.

Classification of physical activities based on body-segments coordination.

PubMed

Fradet, Laetitia; Marin, Frederic

2016-09-01

Numerous innovations based on connected objects and physical activity (PA) monitoring have been proposed. However, recognition of PAs requires robust algorithm and methodology. The current study presents an innovative approach for PA recognition. It is based on the heuristic definition of postures and the use of body-segments coordination obtained through external sensors. The first part of this study presents the methodology required to define the set of accelerations which is the most appropriate to represent the particular body-segments coordination involved in the chosen PAs (here walking, running, and cycling). For that purpose, subjects of different ages and heterogeneous physical conditions walked, ran, cycled, and performed daily activities at different paces. From the 3D motion capture, vertical and horizontal accelerations of 8 anatomical landmarks representative of the body were computed. Then, the 680 combinations from up to 3 accelerations were compared to identify the most appropriate set of acceleration to discriminate the PAs in terms of body segment coordinations. The discrimination was based on the maximal Hausdorff Distance obtained between the different set of accelerations. The vertical accelerations of both knees demonstrated the best PAs discrimination. The second step was the proof of concept, implementing the proposed algorithm to classify PAs of new group of subjects. The originality of the proposed algorithm is the possibility to use the subject's specific measures as reference data. With the proposed algorithm, 94% of the trials were correctly classified. In conclusion, our study proposed a flexible and extendable methodology. At the current stage, the algorithm has been shown to be valid for heterogeneous subjects, which suggests that it could be deployed in clinical or health-related applications regardless of the subjects' physical abilities or characteristics. Copyright © 2016 Elsevier Ltd. All rights reserved.

"You can't just jump on a bike and go": a qualitative study exploring parents' perceptions of physical activity in children with type 1 diabetes.

PubMed

Quirk, Helen; Blake, Holly; Dee, Beatrice; Glazebrook, Cris

2014-12-20

Parents of children with Type 1 Diabetes Mellitus (T1DM) have an important role in supporting diabetes management behaviours and helping to maintain their child's healthy lifestyle. Physical activity has known benefits for children with T1DM [Diabet Med 31: 1163-1173], but children with chronic health conditions typically have low levels of physical activity. Research is needed to build an understanding of the experience of physical activity for children with T1DM. The purpose of this study was to understand parents' perceptions of what influences physical activity for children with T1DM and to inform the practice of those working with children who have T1DM. Data were collected through semi-structured interviews with 20 parents (18 mothers, 2 fathers) who had a child aged 7 - 13 years with T1DM in the UK. Interviews were recorded, transcribed verbatim and data were analysed using thematic analysis [Qual Res Psychol 3: 77-101, 2006]). Factors believed to influence participation in physical activity are presented as 7 major themes and 15 subthemes. Themes that emerged included the conflict between planning and spontaneous activity, struggles to control blood glucose, recognition of the importance of physical activity, the determination of parents, children relying on their parents to manage physical activity, the importance of a good support system and individual factors about the children that influence physical activity participation. This study highlights that parents serve as gate-keepers for children's physical activity. The findings provide insight into the need for T1DM knowledge and competence in personnel involved in the supervision of children's physical activities. Healthcare providers should collaborate with families to ensure understanding of how to manage physical activity. The findings sensitise professionals to the issues confronted by children with T1DM and their parents, as well as the methods used by children and their families to overcome obstacles to physical activity. The implications for further research, clinical practice, and physical activity promotion with children with T1DM are discussed.

The Importance of High School Physics Teachers for Female Students' Physics Identity and Persistence

NASA Astrophysics Data System (ADS)

Hazari, Zahra; Brewe, Eric; Goertzen, Renee Michelle; Hodapp, Theodore

2017-02-01

Given the historic and continued underrepresentation of women in physics, it is important to understand the role that high school physics might play in attracting female students to physics careers. Drawing on data from over 900 female undergraduates in physics, we examine when these women became interested in physics careers and different sources of recognition (important for physics identity development) that may have affected their choices at certain time points. The results provide optimism since many of these female students, even those not previously intending science careers, began to intend physics careers in high school and recognition from high school physics teachers had a significant effect on predicting these intentions.

The Effect of Jigsaw Technique on the Students' Laboratory Material Recognition and Usage Skills in General Physics Laboratory-I Course

ERIC Educational Resources Information Center

Aydin, Abdullah; Biyikli, Filiz

2017-01-01

This research aims to compare the effects of Jigsaw technique from the cooperative learning methods and traditional learning method on laboratory material recognition and usage skills of students in General Physics Lab-I Course. This study was conducted with 63 students who took general physics laboratory-I course in the department of science…

Improving activity recognition using a wearable barometric pressure sensor in mobility-impaired stroke patients.

PubMed

Massé, Fabien; Gonzenbach, Roman R; Arami, Arash; Paraschiv-Ionescu, Anisoara; Luft, Andreas R; Aminian, Kamiar

2015-08-25

Stroke survivors often suffer from mobility deficits. Current clinical evaluation methods, including questionnaires and motor function tests, cannot provide an objective measure of the patients' mobility in daily life. Physical activity performance in daily-life can be assessed using unobtrusive monitoring, for example with a single sensor module fixed on the trunk. Existing approaches based on inertial sensors have limited performance, particularly in detecting transitions between different activities and postures, due to the inherent inter-patient variability of kinematic patterns. To overcome these limitations, one possibility is to use additional information from a barometric pressure (BP) sensor. Our study aims at integrating BP and inertial sensor data into an activity classifier in order to improve the activity (sitting, standing, walking, lying) recognition and the corresponding body elevation (during climbing stairs or when taking an elevator). Taking into account the trunk elevation changes during postural transitions (sit-to-stand, stand-to-sit), we devised an event-driven activity classifier based on fuzzy-logic. Data were acquired from 12 stroke patients with impaired mobility, using a trunk-worn inertial and BP sensor. Events, including walking and lying periods and potential postural transitions, were first extracted. These events were then fed into a double-stage hierarchical Fuzzy Inference System (H-FIS). The first stage processed the events to infer activities and the second stage improved activity recognition by applying behavioral constraints. Finally, the body elevation was estimated using a pattern-enhancing algorithm applied on BP. The patients were videotaped for reference. The performance of the algorithm was estimated using the Correct Classification Rate (CCR) and F-score. The BP-based classification approach was benchmarked against a previously-published fuzzy-logic classifier (FIS-IMU) and a conventional epoch-based classifier (EPOCH). The algorithm performance for posture/activity detection, in terms of CCR was 90.4 %, with 3.3 % and 5.6 % improvements against FIS-IMU and EPOCH, respectively. The proposed classifier essentially benefits from a better recognition of standing activity (70.3 % versus 61.5 % [FIS-IMU] and 42.5 % [EPOCH]) with 98.2 % CCR for body elevation estimation. The monitoring and recognition of daily activities in mobility-impaired stoke patients can be significantly improved using a trunk-fixed sensor that integrates BP, inertial sensors, and an event-based activity classifier.

Enhanced cognitive activity – over and above social or physical activity – is required to protect Alzheimer’s mice against cognitive impairment, reduce Aβ deposition, and increase synaptic immunoreactivity

PubMed Central

Cracchiolo, Jennifer R.; Mori, Takashi; Nazian, Stanley J.; Tan, Jun; Potter, Huntington; Arendash, Gary W.

2007-01-01

Although social, physical, and cognitive activities have each been suggested to reduce the risk of Alzheimer’s Disease (AD), epidemiologic studies cannot determine which activity or combination of activities is most important. To address this question, mutant APP transgenic AD mice were reared long-term in one of four housing conditions (impoverished, social, social+physical, or complete enrichment) from 1½ through 9 months of age. Thus, a stepwise layering of social, physical, and enhanced cognitive activity was created. Behavioral evaluation in a full battery of sensorimotor, anxiety, and cognitive tasks was carried out during the final 5 weeks of housing. Only AD mice raised in complete enrichment (i.e., enhanced cognitive activity) showed: 1) protection against cognitive impairment, 2) decreased brain β-amyloid deposition, and 3) increased hippocampal synaptic immunoreactivity. The protection provided by enhanced cognitive activity spanned multiple cognitive domains (working memory, reference learning, and recognition/identification). Cognitive and neurohistologic benefits of complete enrichment occurred without any changes in blood cytokine or corticosterone levels, suggesting that enrichment-dependent mechanisms do not involve changes in the inflammatory response or stress levels, respectively. These results indicate that the enhanced cognitive activity of complete enrichment is required for cognitive and neurologic benefit to AD mice – physical and/or social activity are insufficient. Thus, our data suggest that humans who emphasize a high lifelong level of cognitive activity (over and above social and physical activities) will attain the maximal environmental protection against AD. PMID:17714960

Physical activity during pregnancy: impact of applying different physical activity guidelines.

PubMed

Smith, Katie M; Campbell, Christina G

2013-01-01

Multiple guidelines and definitions of physical activity (PA) have been used to study the benefits of activity during pregnancy. The different guidelines lead to a wide range of prevalence estimates and this has led to conflicting reports about activity patterns during pregnancy. A longitudinal study was conducted to assess PA using a pattern-recognition monitor for a 7-day period at week 18 (n = 55) and week 35 (n = 66) of pregnancy. The amount of activity performed and the number of women meeting six different PA guidelines were evaluated. Adherence to PA guidelines ranged from 5 to 100% and 9 to 100% at weeks 18 and 35, respectively. All women achieved the 500 MET-minute guideline and nearly all women accumulated ≥150 minutes of weekly moderate-vigorous physical activity (MVPA) at both time points. Only 22% and 26% participated in ≥3 sessions of MVPA lasting ≥30 minutes at both time points and this further declined to 5% and 9% when the guideline was increased to ≥5 sessions of 30 minutes. The amount of PA during pregnancy varied drastically depending on which guideline was used. Further research is warranted to clearly identify the patterns of activity that are associated with healthy pregnancy outcomes.

Physical Activity during Pregnancy: Impact of Applying Different Physical Activity Guidelines

PubMed Central

Smith, Katie M.; Campbell, Christina G.

2013-01-01

Multiple guidelines and definitions of physical activity (PA) have been used to study the benefits of activity during pregnancy. The different guidelines lead to a wide range of prevalence estimates and this has led to conflicting reports about activity patterns during pregnancy. A longitudinal study was conducted to assess PA using a pattern-recognition monitor for a 7-day period at week 18 (n = 55) and week 35 (n = 66) of pregnancy. The amount of activity performed and the number of women meeting six different PA guidelines were evaluated. Adherence to PA guidelines ranged from 5 to 100% and 9 to 100% at weeks 18 and 35, respectively. All women achieved the 500 MET-minute guideline and nearly all women accumulated ≥150 minutes of weekly moderate-vigorous physical activity (MVPA) at both time points. Only 22% and 26% participated in ≥3 sessions of MVPA lasting ≥30 minutes at both time points and this further declined to 5% and 9% when the guideline was increased to ≥5 sessions of 30 minutes. The amount of PA during pregnancy varied drastically depending on which guideline was used. Further research is warranted to clearly identify the patterns of activity that are associated with healthy pregnancy outcomes. PMID:23476778

Creating a movement for active living via a media campaign.

PubMed

Huberty, Jennifer; Dodge, Tammie; Peterson, Kerri R; Balluff, Mary

2012-11-01

Activate Omaha (AO), a community-wide health initiative, was awarded a grant by Active Living by Design in 2003. To establish credibility of the partners in AO and increase awareness of active living in the community by emphasizing promotions (branding, logo recognition). Media, including billboards, TV and radio ads, high-profile spokespersons, grassroots efforts, and worksite "toolkits" featuring tips and creative messaging on physical activity were combined to incentivize people to be physically active. Campaign surveys were conducted by the Market Survey Research Group each year from 2005 to 2008. Survey data based on the first campaign indicated that 86% of Omahans wanted to be part of an active community and to be active with younger generations. The second campaign focused on getting families physically active together, and this survey data showed that citizens wanted to be a part of an active community. A third campaign added practical examples of citizens being active within the community and efforts expanded to worksites with consistent messaging for employees. The final survey indicated that 78% of respondents found Omaha to be an active community compared to 63% who had that response 3 years earlier. Activate Omaha was successful in gaining credibility and leveraging additional funding to implement complementary programming and physical projects, and as a result, changing community perceptions and influencing policy decisions. Copyright © 2012 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

[Recognition of walking stance phase and swing phase based on moving window].

PubMed

Geng, Xiaobo; Yang, Peng; Wang, Xinran; Geng, Yanli; Han, Yu

2014-04-01

Wearing transfemoral prosthesis is the only way to complete daily physical activity for amputees. Motion pattern recognition is important for the control of prosthesis, especially in the recognizing swing phase and stance phase. In this paper, it is reported that surface electromyography (sEMG) signal is used in swing and stance phase recognition. sEMG signal of related muscles was sampled by Infiniti of a Canadian company. The sEMG signal was then filtered by weighted filtering window and analyzed by height permitted window. The starting time of stance phase and swing phase is determined through analyzing special muscles. The sEMG signal of rectus femoris was used in stance phase recognition and sEMG signal of tibialis anterior is used in swing phase recognition. In a certain tolerating range, the double windows theory, including weighted filtering window and height permitted window, can reach a high accuracy rate. Through experiments, the real walking consciousness of the people was reflected by sEMG signal of related muscles. Using related muscles to recognize swing and stance phase is reachable. The theory used in this paper is useful for analyzing sEMG signal and actual prosthesis control.

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition

PubMed Central

2017-01-01

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user’s location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively. PMID:28817094

Combined Dynamic Time Warping with Multiple Sensors for 3D Gesture Recognition.

PubMed

Choi, Hyo-Rim; Kim, TaeYong

2017-08-17

Cyber-physical systems, which closely integrate physical systems and humans, can be applied to a wider range of applications through user movement analysis. In three-dimensional (3D) gesture recognition, multiple sensors are required to recognize various natural gestures. Several studies have been undertaken in the field of gesture recognition; however, gesture recognition was conducted based on data captured from various independent sensors, which rendered the capture and combination of real-time data complicated. In this study, a 3D gesture recognition method using combined information obtained from multiple sensors is proposed. The proposed method can robustly perform gesture recognition regardless of a user's location and movement directions by providing viewpoint-weighted values and/or motion-weighted values. In the proposed method, the viewpoint-weighted dynamic time warping with multiple sensors has enhanced performance by preventing joint measurement errors and noise due to sensor measurement tolerance, which has resulted in the enhancement of recognition performance by comparing multiple joint sequences effectively.

The association between imitation recognition and socio-communicative competencies in chimpanzees (Pan troglodytes).

PubMed

Pope, Sarah M; Russell, Jamie L; Hopkins, William D

2015-01-01

Imitation recognition provides a viable platform from which advanced social cognitive skills may develop. Despite evidence that non-human primates are capable of imitation recognition, how this ability is related to social cognitive skills is unknown. In this study, we compared imitation recognition performance, as indicated by the production of testing behaviors, with performance on a series of tasks that assess social and physical cognition in 49 chimpanzees. In the initial analyses, we found that males were more responsive than females to being imitated and engaged in significantly greater behavior repetitions and testing sequences. We also found that subjects who consistently recognized being imitated performed better on social but not physical cognitive tasks, as measured by the Primate Cognitive Test Battery. These findings suggest that the neural constructs underlying imitation recognition are likely associated with or among those underlying more general socio-communicative abilities in chimpanzees. Implications regarding how imitation recognition may facilitate other social cognitive processes, such as mirror self-recognition, are discussed.

The association between imitation recognition and socio-communicative competencies in chimpanzees (Pan troglodytes)

PubMed Central

Pope, Sarah M.; Russell, Jamie L.; Hopkins, William D.

2015-01-01

Imitation recognition provides a viable platform from which advanced social cognitive skills may develop. Despite evidence that non-human primates are capable of imitation recognition, how this ability is related to social cognitive skills is unknown. In this study, we compared imitation recognition performance, as indicated by the production of testing behaviors, with performance on a series of tasks that assess social and physical cognition in 49 chimpanzees. In the initial analyses, we found that males were more responsive than females to being imitated and engaged in significantly greater behavior repetitions and testing sequences. We also found that subjects who consistently recognized being imitated performed better on social but not physical cognitive tasks, as measured by the Primate Cognitive Test Battery. These findings suggest that the neural constructs underlying imitation recognition are likely associated with or among those underlying more general socio-communicative abilities in chimpanzees. Implications regarding how imitation recognition may facilitate other social cognitive processes, such as mirror self-recognition, are discussed. PMID:25767454

Evidence for the activation of sensorimotor information during visual word recognition: the body-object interaction effect.

PubMed

Siakaluk, Paul D; Pexman, Penny M; Aguilera, Laura; Owen, William J; Sears, Christopher R

2008-01-01

We examined the effects of sensorimotor experience in two visual word recognition tasks. Body-object interaction (BOI) ratings were collected for a large set of words. These ratings assess perceptions of the ease with which a human body can physically interact with a word's referent. A set of high BOI words (e.g., mask) and a set of low BOI words (e.g., ship) were created, matched on imageability and concreteness. Facilitatory BOI effects were observed in lexical decision and phonological lexical decision tasks: responses were faster for high BOI words than for low BOI words. We discuss how our findings may be accounted for by (a) semantic feedback within the visual word recognition system, and (b) an embodied view of cognition (e.g., Barsalou's perceptual symbol systems theory), which proposes that semantic knowledge is grounded in sensorimotor interactions with the environment.

Physical attractiveness stereotype and memory.

PubMed

Rohner, Jean-Christophe; Rasmussen, Anders

2011-08-01

Three experiments examined explicit and implicit memory for information that is congruent with the physical attractiveness stereotype (i.e. attractive-positive and unattractive-negative) and information that is incongruent with the physical attractiveness stereotype (i.e. attractive-negative and unattractive-positive). Measures of explicit recognition sensitivity and implicit discriminability revealed a memorial advantage for congruent compared to incongruent information, as evident from hit and false alarm rates and reaction times, respectively. Measures of explicit memory showed a recognition bias toward congruent compared to incongruent information, where participants tended to call congruent information old, independently of whether the information had been shown previously or not. This recognition bias was unrelated to reports of subjective confidence in retrieval. The present findings shed light on the cognitive mechanisms that might mediate discriminatory behavior towards physically attractive and physically unattractive individuals. © 2011 The Authors. Scandinavian Journal of Psychology © 2011 The Scandinavian Psychological Associations.

Calibration and validation of wearable monitors.

PubMed

Bassett, David R; Rowlands, Alex; Trost, Stewart G

2012-01-01

Wearable monitors are increasingly being used to objectively monitor physical activity in research studies within the field of exercise science. Calibration and validation of these devices are vital to obtaining accurate data. This article is aimed primarily at the physical activity measurement specialist, although the end user who is conducting studies with these devices also may benefit from knowing about this topic. Initially, wearable physical activity monitors should undergo unit calibration to ensure interinstrument reliability. The next step is to simultaneously collect both raw signal data (e.g., acceleration) from the wearable monitors and rates of energy expenditure, so that algorithms can be developed to convert the direct signals into energy expenditure. This process should use multiple wearable monitors and a large and diverse subject group and should include a wide range of physical activities commonly performed in daily life (from sedentary to vigorous). New methods of calibration now use "pattern recognition" approaches to train the algorithms on various activities, and they provide estimates of energy expenditure that are much better than those previously available with the single-regression approach. Once a method of predicting energy expenditure has been established, the next step is to examine its predictive accuracy by cross-validating it in other populations. In this article, we attempt to summarize the best practices for calibration and validation of wearable physical activity monitors. Finally, we conclude with some ideas for future research ideas that will move the field of physical activity measurement forward.

A robust two-way switching control system for remote piloting and stabilization of low-cost quadrotor UAVs

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Vivani, Andrea

2015-04-01

The aim of this paper is to present two control logics and an attitude estimator for UAV stabilization and remote piloting, that are as robust as possible to physical parameters variation and to other external disturbances. Moreover, they need to be implemented on low-cost micro-controllers, in order to be attractive for commercial drones. As an example, possible applications of the two switching control logics could be area surveillance and facial recognition by means of a camera mounted on the drone: the high computational speed logic is used to reach the target, when the high-stability one is activated, in order to complete the recognition tasks.

News Conference: The Big Bangor Day Meeting Lecture: Charterhouse plays host to a physics day Festival: Science on Stage festival 2013 arrives in Poland Event: Scottish Physics Teachers' Summer School Meeting: Researchers and educators meet at Lund University Conference: Exeter marks the spot Recognition: European Physical Society uncovers an historic site Education: Initial teacher education undergoes big changes Forthcoming events

NASA Astrophysics Data System (ADS)

2013-09-01

Conference: The Big Bangor Day Meeting Lecture: Charterhouse plays host to a physics day Festival: Science on Stage festival 2013 arrives in Poland Event: Scottish Physics Teachers' Summer School Meeting: Researchers and educators meet at Lund University Conference: Exeter marks the spot Recognition: European Physical Society uncovers an historic site Education: Initial teacher education undergoes big changes Forthcoming events

A feasibility study on smartphone accelerometer-based recognition of household activities and influence of smartphone position.

PubMed

Della Mea, Vincenzo; Quattrin, Omar; Parpinel, Maria

2017-12-01

Obesity and physical inactivity are the most important risk factors for chronic diseases. The present study aimed at (i) developing and testing a method for classifying household activities based on a smartphone accelerometer; (ii) evaluating the influence of smartphone position; and (iii) evaluating the acceptability of wearing a smartphone for activity recognition. An Android application was developed to record accelerometer data and calculate descriptive features on 5-second time blocks, then classified with nine algorithms. Household activities were: sitting, working at the computer, walking, ironing, sweeping the floor, going down stairs with a shopping bag, walking while carrying a large box, and climbing stairs with a shopping bag. Ten volunteers carried out the activities for three times, each one with a smartphone in a different position (pocket, arm, and wrist). Users were then asked to answer a questionnaire. 1440 time blocks were collected. Three algorithms demonstrated an accuracy greater than 80% for all smartphone positions. While for some subjects the smartphone was uncomfortable, it seems that it did not really affect activity. Smartphones can be used to recognize household activities. A further development is to measure metabolic equivalent tasks starting from accelerometer data only.

Biometrics Technology

DTIC Science & Technology

2012-03-13

aspects associated with the use of fingerprinting. Another form of physical biometrics is facial recognition . ― Facial recognition unlike other...have originated back to the early 1960s. ―One of the leading pioneers in facial recognition biometrics was Woodrow W. Bledsoe who developed a...identified match. There are several advantages associated with Facial recognition . It is highly reliable, used extensively in security systems, and

Do Israeli health promoting schools contribute to students' healthy eating and physical activity habits?

PubMed

Hayek, Samah; Tessler, Riki; Bord, Shiran; Endevelt, Ronit; Satran, Carmit; Livne, Irit; Khatib, Mohammed; Harel-Fisch, Yosi; Baron-Epel, Orna

2017-10-04

The Israeli Health Promoting School Network (HPSN) is actively committed to enhancing a healthy lifestyle for the entire school population. This study aimed to explore the contribution of school participation in the HPSN and students' individual characteristics to healthy eating and physical activity habits among Israeli school children aged 10-12 years. A cross-sectional survey was conducted among 4166 students in grades 4-6 from 28 schools. The schools were selected from a sample of HPSN affiliated and non-HPSN schools. The contribution of individual characteristics (grade, gender and subjective self-reported health education activities at school) and school characteristics (school type, population group, deprivation score) to healthy eating and physical activity habits was analyzed using multi-level hierarchical models. Multi-level analysis indicated that student's individual characteristic was significantly associated with healthy eating and physical activity habits. The subjective self-reported health education received at school was statistically significant factor associated with students' health behaviors. The school's affiliation with the HPSN was not associated with higher healthy eating and physical activity scores after adjusting for individual factors. These findings suggest that Israeli HPSN schools do not contribute to children's health behaviors more than other schools. Therefore, health promoting activities in HPSN schools need to be improved to justify their recognition as members of the HPS network and to fulfill their mission. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

DTIC Science & Technology

2009-07-01

Evanseck JD, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 102...dimensional (3-D) protein structures are critical for the understanding of molecular mechanisms of living systems. Traditionally, X-ray crystallography...disordered proteins are often responsible for molecular recognition, molecular assembly, protein modifica- tion, and entropic chain activities in organisms [26

Modes of Visual Recognition and Perceptually Relevant Sketch-based Coding for Images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1991-01-01

A review of visual recognition studies is used to define two levels of information requirements. These two levels are related to two primary subdivisions of the spatial frequency domain of images and reflect two distinct different physical properties of arbitrary scenes. In particular, pathologies in recognition due to cerebral dysfunction point to a more complete split into two major types of processing: high spatial frequency edge based recognition vs. low spatial frequency lightness (and color) based recognition. The former is more central and general while the latter is more specific and is necessary for certain special tasks. The two modes of recognition can also be distinguished on the basis of physical scene properties: the highly localized edges associated with reflectance and sharp topographic transitions vs. smooth topographic undulation. The extreme case of heavily abstracted images is pursued to gain an understanding of the minimal information required to support both modes of recognition. Here the intention is to define the semantic core of transmission. This central core of processing can then be fleshed out with additional image information and coding and rendering techniques.

Physical inactivity: the "Cinderella" risk factor for noncommunicable disease prevention.

PubMed

Bull, Fiona C; Bauman, Adrian E

2011-08-01

There is strong evidence demonstrating the direct and indirect pathways by which physical activity prevents many of the major noncommunicable diseases (NCD) responsible for premature death and disability. Physical inactivity was identified as the 4th leading risk factor for the prevention of NCD, preceded only by tobacco use, hypertension, and high blood glucose levels, and accounting for more than 3 million preventable deaths globally in 2010. Physical inactivity is a global public health priority but, in most countries, this has not yet resulted in widespread recognition nor specific physical activity-related policy action at the necessary scale. Instead, physical inactivity could be described as the Cinderella of NCD risk factors, defined as "poverty of policy attention and resourcing proportionate to its importance." The pressing question is "Why is this so?" The authors identify and discuss 8 possible explanations and the need for more effective communication on the importance of physical activity in the NCD prevention context. Although not all of the issues identified will be relevant for any 1 country, it is likely that at different times and in different combinations these 8 problems continue to delay national-level progress on addressing physical inactivity in many countries. The authors confirm that there is sufficient evidence to act, and that much better use of well-planned, coherent communication strategies are needed in most countries and at the international level. Significant opportunities exist. The Toronto Charter on Physical Activity and the Seven Investments that Work are 2 useful tools to support increased advocacy on physical activity within and beyond the context of the crucial 2011 UN High-Level Meeting on NCDs.

Transfer Learning for Activity Recognition: A Survey

PubMed Central

Cook, Diane; Feuz, Kyle D.; Krishnan, Narayanan C.

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities being performed by the human. At the core of this capability is activity recognition, which is a challenging and well-researched problem. Activity recognition algorithms require substantial amounts of labeled training data yet need to perform well under very diverse circumstances. As a result, researchers have been designing methods to identify and utilize subtle connections between activity recognition datasets, or to perform transfer-based activity recognition. In this paper we survey the literature to highlight recent advances in transfer learning for activity recognition. We characterize existing approaches to transfer-based activity recognition by sensor modality, by differences between source and target environments, by data availability, and by type of information that is transferred. Finally, we present some grand challenges for the community to consider as this field is further developed. PMID:24039326

Posture Allocation Revisited: Breaking the Sedentary Threshold of Energy Expenditure for Obesity Management

PubMed Central

Miles-Chan, Jennifer L.; Dulloo, Abdul G.

2017-01-01

There is increasing recognition that low-intensity physical activities of daily life play an important role in achieving energy balance and that their societal erosion through substitution with sedentary (mostly sitting) behaviors, whether occupational or for leisure, impact importantly on the obesity epidemic. This has generated considerable interest for better monitoring, characterizing, and promoting countermeasures to sedentariness through a plethora of low-level physical activities (e.g., active workstations, standing desks, sitting breaks), amid the contention that altering posture allocation (lying, sitting, standing) can modify energy expenditure to impact upon body weight regulation and health. In addressing this contention, this paper first revisits the past and more recent literature on postural energetics, with particular emphasis on potential determinants of the large inter-individual variability in the energy cost of standing and the impact of posture on fat oxidation. It subsequently analyses the available data pertaining to various strategies by which posture allocations, coupled with light physical activity, may increase energy expenditure beyond the sedentary threshold, and their relevance as potential targets for obesity management. PMID:28690547

National Athletic Trainers' Association position statement: environmental cold injuries.

PubMed

Cappaert, Thomas A; Stone, Jennifer A; Castellani, John W; Krause, Bentley Andrew; Smith, Daniel; Stephens, Bradford A

2008-01-01

To present recommendations for the prevention, recognition, and treatment of environmental cold injuries. Individuals engaged in sport-related or work-related physical activity in cold, wet, or windy conditions are at risk for environmental cold injuries. An understanding of the physiology and pathophysiology, risk management, recognition, and immediate care of environmental cold injuries is an essential skill for certified athletic trainers and other health care providers working with individuals at risk. These recommendations are intended to provide certified athletic trainers and others participating in athletic health care with the specific knowledge and problem-solving skills needed to address environmental cold injuries. Each recommendation has been graded (A, B, or C) according to the Strength of Recommendation Taxonomy criterion scale.

National Athletic Trainers' Association Position Statement: Environmental Cold Injuries

PubMed Central

Cappaert, Thomas A; Stone, Jennifer A; Castellani, John W; Krause, Bentley Andrew; Smith, Daniel; Stephens, Bradford A

2008-01-01

Objective: To present recommendations for the prevention, recognition, and treatment of environmental cold injuries. Background: Individuals engaged in sport-related or work-related physical activity in cold, wet, or windy conditions are at risk for environmental cold injuries. An understanding of the physiology and pathophysiology, risk management, recognition, and immediate care of environmental cold injuries is an essential skill for certified athletic trainers and other health care providers working with individuals at risk. Recommendations: These recommendations are intended to provide certified athletic trainers and others participating in athletic health care with the specific knowledge and problem-solving skills needed to address environmental cold injuries. Each recommendation has been graded (A, B, or C) according to the Strength of Recommendation Taxonomy criterion scale. PMID:19030143

A sensor and video based ontology for activity recognition in smart environments.

PubMed

Mitchell, D; Morrow, Philip J; Nugent, Chris D

2014-01-01

Activity recognition is used in a wide range of applications including healthcare and security. In a smart environment activity recognition can be used to monitor and support the activities of a user. There have been a range of methods used in activity recognition including sensor-based approaches, vision-based approaches and ontological approaches. This paper presents a novel approach to activity recognition in a smart home environment which combines sensor and video data through an ontological framework. The ontology describes the relationships and interactions between activities, the user, objects, sensors and video data.

Where Are the Women? The Underrepresentation of Women Physicians Among Recognition Award Recipients From Medical Specialty Societies.

PubMed

Silver, Julie K; Slocum, Chloe S; Bank, Anna M; Bhatnagar, Saurabha; Blauwet, Cheri A; Poorman, Julie A; Villablanca, Amparo; Parangi, Sareh

2017-08-01

Membership in medical societies is associated with a number of benefits to members that may include professional education, opportunities to present research, scientific and/or leadership training, networking, and others. In this perspective article, the authors address the value that medical specialty society membership and inclusion have in the development of an academic physician's career and how underrepresentation of women may pose barriers to their career advancement. Because society membership itself is not likely sufficient to support the advancement of academic physicians, this report focuses on one key component of advancement that also can be used as a measure of inclusion in society activities-the representation of women physicians among recipients of recognition awards. Previous reports demonstrated underrepresentation of women physicians among recognition award recipients from 2 physical medicine and rehabilitation specialty organizations, including examples of zero or near-zero results. This report investigated whether zero or near-zero representation of women physicians among recognition award recipients from medical specialty societies extended beyond the field of physical medicine and rehabilitation. Examples of the underrepresentation of women physicians, as compared with their presence in the respective field, was found across a range of additional specialties, including dermatology, neurology, anesthesiology, orthopedic surgery, head and neck surgery, and plastic surgery. The authors propose a call for action across the entire spectrum of medical specialty societies to: (1) examine gender diversity and inclusion data through the lens of the organization's mission, values, and culture; (2) transparently report the results to members and other stakeholders including medical schools and academic medical centers; (3) investigate potential causes of less than proportionate representation of women; (4) implement strategies designed to improve inclusion; (5) track outcomes as a means to measure progress and inform future strategies; and (6) publish the results to engage community members in conversation about the equitable representation of women. Copyright © 2017 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Traversing myths and mountains: addressing socioeconomic inequities in the promotion of nutrition and physical activity behaviours.

PubMed

Ball, Kylie

2015-11-14

In developed countries, individuals experiencing socioeconomic disadvantage - whether a low education level, low income, low-status occupation, or living in a socioeconomically disadvantaged neighbourhood - are less likely than those more advantaged to engage in eating and physical activity behaviours conducive to optimal health. These socioeconomic inequities in nutrition and physical activity (and some sedentary) behaviours are graded, persistent, and evident across multiple populations and studies. They are concerning in that they mirror socioeconomic inequities in obesity and in health outcomes. Yet there remains a dearth of evidence of the most effective means of addressing these inequities. People experiencing disadvantage face multiple challenges to healthy behaviours that can appear insurmountable. With increasing recognition of the role of underlying structural and societal factors as determinants of nutrition and physical activity behaviours and inequities in these behaviours, and the limited success of behaviour change approaches in addressing these inequities, we might wonder whether there remains a role for behavioural scientists to tackle these challenges. This debate piece argues that behavioural scientists can play an important role in addressing socioeconomic inequities in nutrition, physical activity and sedentary behaviours, and that this will involve challenging myths and taking on new perspectives. There are successful models for doing so from which we can learn. Addressing socioeconomic inequities in eating, physical activity and sedentary behaviours is challenging. However, successful examples demonstrate that overcoming such challenges is possible, and provide guidance for doing so. Given the disproportionate burden of ill health carried by people experiencing socioeconomic disadvantage, all our nutrition and physical activity interventions, programs and policies should be designed to reach and positively impact these individuals at greatest need.

Emotion Recognition Abilities and Empathy of Victims of Bullying

ERIC Educational Resources Information Center

Woods, Sarah; Wolke, Dieter; Nowicki, Stephen; Hall, Lynne

2009-01-01

Objectives: Bullying is a form of systematic abuse by peers with often serious consequences for victims. Few studies have considered the role of emotion recognition abilities and empathic behaviour for different bullying roles. This study investigated physical and relational bullying involvement in relation to basic emotion recognition abilities,…

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Physics career intentions: The effect of physics identity, math identity, and gender

NASA Astrophysics Data System (ADS)

Lock, Robynne M.; Hazari, Zahra; Potvin, Geoff

2013-01-01

Although nearly half of high school physics students are female, only 21% of physics bachelor's degrees are earned by women. Using data from a national survey of college students in introductory English courses (on science-related experiences, particularly in high school), we examine the influence of students' physics and math identities on their choice to pursue a physics career. Males have higher math and physics identities than females in all three dimensions of our identity framework. These dimensions include: performance/competence (perceptions of ability to perform/understand), recognition (perception of recognition by others), and interest (desire to learn more). A regression model predicting students' intentions to pursue physics careers shows, as expected, that males are significantly more likely to choose physics than females. Surprisingly, however, when physics and math identity are included in the model, females are shown to be equally likely to choose physics careers as compared to males.

Modeling meiotic chromosome pairing: nuclear envelope attachment, telomere-led active random motion, and anomalous diffusion

PubMed Central

Marshall, Wallace F.; Fung, Jennifer C.

2016-01-01

The recognition and pairing of homologous chromosomes during meiosis is a complex physical and molecular process involving a combination of polymer dynamics and molecular recognition events. Two highly conserved features of meiotic chromosome behavior are the attachment of telomeres to the nuclear envelope and the active random motion of telomeres driven by their interaction with cytoskeletal motor proteins. Both of these features have been proposed to facilitate the process of homolog pairing, but exactly what role these features play in meiosis remains poorly understood. Here we investigate the roles of active motion and nuclear envelope tethering using a Brownian dynamics simulation in which meiotic chromosomes are represented by a Rouse polymer model subjected to tethering and active forces at the telomeres. We find that tethering telomeres to the nuclear envelope slows down pairing relative to the rates achieved by un-attached chromosomes, but that randomly-directed active forces applied to the telomeres speeds up pairing dramatically in a manner that depends on the statistical properties of the telomere force fluctuations. The increased rate of initial pairing cannot be explained by stretching out of the chromosome conformation but instead seems to correlate with anomalous diffusion of sub-telomeric regions. PMID:27046097

Modeling meiotic chromosome pairing: nuclear envelope attachment, telomere-led active random motion, and anomalous diffusion

NASA Astrophysics Data System (ADS)

Marshall, Wallace F.; Fung, Jennifer C.

2016-04-01

The recognition and pairing of homologous chromosomes during meiosis is a complex physical and molecular process involving a combination of polymer dynamics and molecular recognition events. Two highly conserved features of meiotic chromosome behavior are the attachment of telomeres to the nuclear envelope and the active random motion of telomeres driven by their interaction with cytoskeletal motor proteins. Both of these features have been proposed to facilitate the process of homolog pairing, but exactly what role these features play in meiosis remains poorly understood. Here we investigate the roles of active motion and nuclear envelope tethering using a Brownian dynamics simulation in which meiotic chromosomes are represented by a Rouse polymer model subjected to tethering and active forces at the telomeres. We find that tethering telomeres to the nuclear envelope slows down pairing relative to the rates achieved by unattached chromosomes, but that randomly directed active forces applied to the telomeres speed up pairing dramatically in a manner that depends on the statistical properties of the telomere force fluctuations. The increased rate of initial pairing cannot be explained by stretching out of the chromosome conformation but instead seems to correlate with anomalous diffusion of sub-telomeric regions.

Auditory emotion recognition impairments in Schizophrenia: Relationship to acoustic features and cognition

PubMed Central

Gold, Rinat; Butler, Pamela; Revheim, Nadine; Leitman, David; Hansen, John A.; Gur, Ruben; Kantrowitz, Joshua T.; Laukka, Petri; Juslin, Patrik N.; Silipo, Gail S.; Javitt, Daniel C.

2013-01-01

Objective Schizophrenia is associated with deficits in ability to perceive emotion based upon tone of voice. The basis for this deficit, however, remains unclear and assessment batteries remain limited. We evaluated performance in schizophrenia on a novel voice emotion recognition battery with well characterized physical features, relative to impairments in more general emotional and cognitive function. Methods We studied in a primary sample of 92 patients relative to 73 controls. Stimuli were characterized according to both intended emotion and physical features (e.g., pitch, intensity) that contributed to the emotional percept. Parallel measures of visual emotion recognition, pitch perception, general cognition, and overall outcome were obtained. More limited measures were obtained in an independent replication sample of 36 patients, 31 age-matched controls, and 188 general comparison subjects. Results Patients showed significant, large effect size deficits in voice emotion recognition (F=25.4, p<.00001, d=1.1), and were preferentially impaired in recognition of emotion based upon pitch-, but not intensity-features (group X feature interaction: F=7.79, p=.006). Emotion recognition deficits were significantly correlated with pitch perception impairments both across (r=56, p<.0001) and within (r=.47, p<.0001) group. Path analysis showed both sensory-specific and general cognitive contributions to auditory emotion recognition deficits in schizophrenia. Similar patterns of results were observed in the replication sample. Conclusions The present study demonstrates impairments in auditory emotion recognition in schizophrenia relative to acoustic features of underlying stimuli. Furthermore, it provides tools and highlights the need for greater attention to physical features of stimuli used for study of social cognition in neuropsychiatric disorders. PMID:22362394

Changing predictions, stable recognition: Children's representations of downward incline motion.

PubMed

Hast, Michael; Howe, Christine

2017-11-01

Various studies to-date have demonstrated children hold ill-conceived expressed beliefs about the physical world such as that one ball will fall faster than another because it is heavier. At the same time, they also demonstrate accurate recognition of dynamic events. How these representations relate is still unresolved. This study examined 5- to 11-year-olds' (N = 130) predictions and recognition of motion down inclines. Predictions were typically in error, matching previous work, but children largely recognized correct events as correct and rejected incorrect ones. The results also demonstrate while predictions change with increasing age, recognition shows signs of stability. The findings provide further support for a hybrid model of object representations and argue in favour of stable core cognition existing alongside developmental changes. Statement of contribution What is already known on this subject? Children's predictions of physical events show limitations in accuracy Their recognition of such events suggests children may use different knowledge sources in their reasoning What the present study adds? Predictions fluctuate more strongly than recognition, suggesting stable core cognition But recognition also shows some fluctuation, arguing for a hybrid model of knowledge representation. © 2017 The British Psychological Society.

High intralocus variability and interlocus recombination promote immunological diversity in a minimal major histocompatibility system.

PubMed

Wilson, Anthony B; Whittington, Camilla M; Bahr, Angela

2014-12-20

The genes of the major histocompatibility complex (MHC/MH) have attracted considerable scientific interest due to their exceptional levels of variability and important function as part of the adaptive immune system. Despite a large number of studies on MH class II diversity of both model and non-model organisms, most research has focused on patterns of genetic variability at individual loci, failing to capture the functional diversity of the biologically active dimeric molecule. Here, we take a systematic approach to the study of MH variation, analyzing patterns of genetic variation at MH class IIα and IIβ loci of the seahorse, which together form the immunologically active peptide binding cleft of the MH class II molecule. The seahorse carries a minimal class II system, consisting of single copies of both MH class IIα and IIβ, which are physically linked and inherited in a Mendelian fashion. Both genes are ubiquitously expressed and detectible in the brood pouch of male seahorses throughout pregnancy. Genetic variability of the two genes is high, dominated by non-synonymous variation concentrated in their peptide-binding regions. Coding variation outside these regions is negligible, a pattern thought to be driven by intra- and interlocus recombination. Despite the tight physical linkage of MH IIα and IIβ loci, recombination has produced novel composite alleles, increasing functional diversity at sites responsible for antigen recognition. Antigen recognition by the adaptive immune system of the seahorse is enhanced by high variability at both MH class IIα and IIβ loci. Strong positive selection on sites involved in pathogen recognition, coupled with high levels of intra- and interlocus recombination, produce a patchwork pattern of genetic variation driven by genetic hitchhiking. Studies focusing on variation at individual MH loci may unintentionally overlook an important component of ecologically relevant variation.

Prior automatic posture and activity identification improves physical activity energy expenditure prediction from hip-worn triaxial accelerometry.

PubMed

Garnotel, M; Bastian, T; Romero-Ugalde, H M; Maire, A; Dugas, J; Zahariev, A; Doron, M; Jallon, P; Charpentier, G; Franc, S; Blanc, S; Bonnet, S; Simon, C

2018-03-01

Accelerometry is increasingly used to quantify physical activity (PA) and related energy expenditure (EE). Linear regression models designed to derive PAEE from accelerometry-counts have shown their limits, mostly due to the lack of consideration of the nature of activities performed. Here we tested whether a model coupling an automatic activity/posture recognition (AAR) algorithm with an activity-specific count-based model, developed in 61 subjects in laboratory conditions, improved PAEE and total EE (TEE) predictions from a hip-worn triaxial-accelerometer (ActigraphGT3X+) in free-living conditions. Data from two independent subject groups of varying body mass index and age were considered: 20 subjects engaged in a 3-h urban-circuit, with activity-by-activity reference PAEE from combined heart-rate and accelerometry monitoring (Actiheart); and 56 subjects involved in a 14-day trial, with PAEE and TEE measured using the doubly-labeled water method. PAEE was estimated from accelerometry using the activity-specific model coupled to the AAR algorithm (AAR model), a simple linear model (SLM), and equations provided by the companion-software of used activity-devices (Freedson and Actiheart models). AAR-model predictions were in closer agreement with selected references than those from other count-based models, both for PAEE during the urban-circuit (RMSE = 6.19 vs 7.90 for SLM and 9.62 kJ/min for Freedson) and for EE over the 14-day trial, reaching Actiheart performances in the latter (PAEE: RMSE = 0.93 vs. 1.53 for SLM, 1.43 for Freedson, 0.91 MJ/day for Actiheart; TEE: RMSE = 1.05 vs. 1.57 for SLM, 1.70 for Freedson, 0.95 MJ/day for Actiheart). Overall, the AAR model resulted in a 43% increase of daily PAEE variance explained by accelerometry predictions. NEW & NOTEWORTHY Although triaxial accelerometry is widely used in free-living conditions to assess the impact of physical activity energy expenditure (PAEE) on health, its precision and accuracy are often debated. Here we developed and validated an activity-specific model which, coupled with an automatic activity-recognition algorithm, improved the variance explained by the predictions from accelerometry counts by 43% of daily PAEE compared with models relying on a simple relationship between accelerometry counts and EE.

The relationship between physical activity and self-image and problem behaviour among adolescents.

PubMed

Kirkcaldy, B D; Shephard, R J; Siefen, R G

2002-11-01

Although there are a vast array of studies which have demonstrated the psychological and physical health benefits of regular aerobic exercise for adults, few studies have focussed on children and adolescents. The current study examined associations between the extent of participation in endurance sport, and self-report data on self-image, physical and psychological health and overall lifestyle in a large representative sample of German high-school students. Almost 1000 German adolescents (aged 14-18 years) were administered a comprehensive series of questionnaires aimed at assessing anxiety-depression, trait addiction, smoking and drinking behaviour, physical ill-health reports, and self-perception of self-image, parental acceptance and educational attainment. Regular practice of endurance exercise was related to a more favourable self-image. There was a strong association between participation in sports and the type of personality that tends to be resistant to drug and alcohol addiction. Physical exercise was further significantly related to scores for physical and psychological well-being. Adolescents who engaged regularly in physical activity were characterised by lower anxiety-depression scores, and displayed much less social behavioural inhibition than their less active counterparts. It is likely that discussion of recreational or exercise involvement may provide a useful point of entry for facilitating dialogue among adolescents about concerns relating to body image and self-esteem. In terms of psychotherapeutic applications, physical activity has many additional rewards for adolescents. It is probable that by promoting physical fitness, increased physical performance, lessening body mass and promoting a more favourable body shape and structure, exercise will provide more positive social feedback and recognition from peer groups, and this will subsequently lead to improvement in an individual's self-image.

Posture and activity recognition and energy expenditure prediction in a wearable platform.

PubMed

Sazonova, Nadezhda; Browning, Raymond; Melanson, Edward; Sazonov, Edward

2014-01-01

The use of wearable sensors coupled with the processing power of mobile phones may be an attractive way to provide real-time feedback about physical activity and energy expenditure (EE). Here we describe use of a shoe-based wearable sensor system (SmartShoe) with a mobile phone for real-time prediction and display of time spent in various postures/physical activities and the resulting EE. To deal with processing power and memory limitations of the phone, we introduce new algorithms that require substantially less computational power. The algorithms were validated using data from 15 subjects who performed up to 15 different activities of daily living during a four-hour stay in a room calorimeter. Use of Multinomial Logistic Discrimination (MLD) for posture and activity classification resulted in an accuracy comparable to that of Support Vector Machines (SVM) (90% vs. 95%-98%) while reducing the running time by a factor of 190 and reducing the memory requirement by a factor of 104. Per minute EE estimation using activity-specific models resulted in an accurate EE prediction (RMSE of 0.53 METs vs. RMSE of 0.69 METs using previously reported SVM-branched models). These results demonstrate successful implementation of real-time physical activity monitoring and EE prediction system on a wearable platform.

Activity recognition from minimal distinguishing subsequence mining

NASA Astrophysics Data System (ADS)

Iqbal, Mohammad; Pao, Hsing-Kuo

2017-08-01

Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

A Lightweight Hierarchical Activity Recognition Framework Using Smartphone Sensors

PubMed Central

Han, Manhyung; Bang, Jae Hun; Nugent, Chris; McClean, Sally; Lee, Sungyoung

2014-01-01

Activity recognition for the purposes of recognizing a user's intentions using multimodal sensors is becoming a widely researched topic largely based on the prevalence of the smartphone. Previous studies have reported the difficulty in recognizing life-logs by only using a smartphone due to the challenges with activity modeling and real-time recognition. In addition, recognizing life-logs is difficult due to the absence of an established framework which enables the use of different sources of sensor data. In this paper, we propose a smartphone-based Hierarchical Activity Recognition Framework which extends the Naïve Bayes approach for the processing of activity modeling and real-time activity recognition. The proposed algorithm demonstrates higher accuracy than the Naïve Bayes approach and also enables the recognition of a user's activities within a mobile environment. The proposed algorithm has the ability to classify fifteen activities with an average classification accuracy of 92.96%. PMID:25184486

Infrared sensing of non-observable human biometrics

NASA Astrophysics Data System (ADS)

Willmore, Michael R.

2005-05-01

Interest and growth of biometric recognition technologies surged after 9/11. Once a technology mainly used for identity verification in law enforcement, biometrics are now being considered as a secure means of providing identity assurance in security related applications. Biometric recognition in law enforcement must, by necessity, use attributes of human uniqueness that are both observable and vulnerable to compromise. Privacy and protection of an individual's identity is not assured during criminal activity. However, a security system must rely on identity assurance for access control to physical or logical spaces while not being vulnerable to compromise and protecting the privacy of an individual. The solution resides in the use of non-observable attributes of human uniqueness to perform the biometric recognition process. This discussion will begin by presenting some key perspectives about biometric recognition and the characteristic differences between observable and non-observable biometric attributes. An introduction to the design, development, and testing of the Thermo-ID system will follow. The Thermo-ID system is an emerging biometric recognition technology that uses non-observable patterns of infrared energy naturally emanating from within the human body. As with all biometric systems, the infrared patterns recorded and compared within the Thermo-ID system are unique and individually distinguishable permitting a link to be confirmed between an individual and a claimed or previously established identity. The non-observable characteristics of infrared patterns of human uniqueness insure both the privacy and protection of an individual using this type of biometric recognition system.

The software peculiarities of pattern recognition in track detectors

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

Starkov, N.

The different kinds of nuclear track recognition algorithms are represented. Several complicated samples of use them in physical experiments are considered. The some processing methods of complicated images are described.

Incongruence Between Observers’ and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli

PubMed Central

Wingenbach, Tanja S. H.; Brosnan, Mark; Pfaltz, Monique C.; Plichta, Michael M.; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others’ facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others’ facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others’ faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions’ order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed. PMID:29928240

Incongruence Between Observers' and Observed Facial Muscle Activation Reduces Recognition of Emotional Facial Expressions From Video Stimuli.

PubMed

Wingenbach, Tanja S H; Brosnan, Mark; Pfaltz, Monique C; Plichta, Michael M; Ashwin, Chris

2018-01-01

According to embodied cognition accounts, viewing others' facial emotion can elicit the respective emotion representation in observers which entails simulations of sensory, motor, and contextual experiences. In line with that, published research found viewing others' facial emotion to elicit automatic matched facial muscle activation, which was further found to facilitate emotion recognition. Perhaps making congruent facial muscle activity explicit produces an even greater recognition advantage. If there is conflicting sensory information, i.e., incongruent facial muscle activity, this might impede recognition. The effects of actively manipulating facial muscle activity on facial emotion recognition from videos were investigated across three experimental conditions: (a) explicit imitation of viewed facial emotional expressions (stimulus-congruent condition), (b) pen-holding with the lips (stimulus-incongruent condition), and (c) passive viewing (control condition). It was hypothesised that (1) experimental condition (a) and (b) result in greater facial muscle activity than (c), (2) experimental condition (a) increases emotion recognition accuracy from others' faces compared to (c), (3) experimental condition (b) lowers recognition accuracy for expressions with a salient facial feature in the lower, but not the upper face area, compared to (c). Participants (42 males, 42 females) underwent a facial emotion recognition experiment (ADFES-BIV) while electromyography (EMG) was recorded from five facial muscle sites. The experimental conditions' order was counter-balanced. Pen-holding caused stimulus-incongruent facial muscle activity for expressions with facial feature saliency in the lower face region, which reduced recognition of lower face region emotions. Explicit imitation caused stimulus-congruent facial muscle activity without modulating recognition. Methodological implications are discussed.

Interpreting Chicken-Scratch: Lexical Access for Handwritten Words

PubMed Central

Barnhart, Anthony S.; Goldinger, Stephen D.

2014-01-01

Handwritten word recognition is a field of study that has largely been neglected in the psychological literature, despite its prevalence in society. Whereas studies of spoken word recognition almost exclusively employ natural, human voices as stimuli, studies of visual word recognition use synthetic typefaces, thus simplifying the process of word recognition. The current study examined the effects of handwriting on a series of lexical variables thought to influence bottom-up and top-down processing, including word frequency, regularity, bidirectional consistency, and imageability. The results suggest that the natural physical ambiguity of handwritten stimuli forces a greater reliance on top-down processes, because almost all effects were magnified, relative to conditions with computer print. These findings suggest that processes of word perception naturally adapt to handwriting, compensating for physical ambiguity by increasing top-down feedback. PMID:20695708

Obesity determinants in Mexican preschool children: parental perceptions and practices related to feeding and physical activity.

PubMed

Rodríguez-Oliveros, Guadalupe; Haines, Jess; Ortega-Altamirano, Doris; Power, Elaine; Taveras, Elsie M; González-Unzaga, Marco A; Reyes-Morales, Hortensia

2011-08-01

Obesity represents a major public health problem worldwide. In Mexico, overweight and obesity have increased dramatically, affecting 26% of school-aged children. The aim of this study was to explore perceptions and practices of key obesity determinants among parents of preschool children attending child care centers. We conducted five focus groups with 38 parents from six Mexico City child care centers. Inquiry topics were 1) childhood obesity causes and consequences; 2) child feeding practices at the child care center and home; 3) healthful and unhealthful foods for young children; 4) significance of physical activity in childhood; and 5) physical activity-promoting factors and barriers. We analyzed these data using content analysis. We identified a number of barriers to healthful eating, including parental time constraints, permissive feeding styles, unhealthful food preparation practices, lack of knowledge about nutrition, food advertisement, and high availability of unhealthful foods in public places. Facilitators to healthful eating included recognition of childhood overweight prevention and consequences, and healthy food choices. Main barriers to childhood physical activity included influence of young family members to play video games, parental time constraints, street safety, low access to sports facilities, and insufficient communication with child care centers. Understanding parental views and perceptions of the main factors influencing preschoolers' weight-related behavior can inform home-based or environmental interventions that support healthful eating and regular physical activity. Copyright © 2011 IMSS. Published by Elsevier Inc. All rights reserved.

Kinome signaling through regulated protein-protein interactions in normal and cancer cells.

PubMed

Pawson, Tony; Kofler, Michael

2009-04-01

The flow of molecular information through normal and oncogenic signaling pathways frequently depends on protein phosphorylation, mediated by specific kinases, and the selective binding of the resulting phosphorylation sites to interaction domains present on downstream targets. This physical and functional interplay of catalytic and interaction domains can be clearly seen in cytoplasmic tyrosine kinases such as Src, Abl, Fes, and ZAP-70. Although the kinase and SH2 domains of these proteins possess similar intrinsic properties of phosphorylating tyrosine residues or binding phosphotyrosine sites, they also undergo intramolecular interactions when linked together, in a fashion that varies from protein to protein. These cooperative interactions can have diverse effects on substrate recognition and kinase activity, and provide a variety of mechanisms to link the stimulation of catalytic activity to substrate recognition. Taken together, these data have suggested how protein kinases, and the signaling pathways in which they are embedded, can evolve complex properties through the stepwise linkage of domains within single polypeptides or multi-protein assemblies.

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

PubMed

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Physical exercise prevents short and long-term deficits on aversive and recognition memory and attenuates brain oxidative damage induced by maternal deprivation.

PubMed

Neves, Ben-Hur; Menezes, Jefferson; Souza, Mauren Assis; Mello-Carpes, Pâmela B

2015-12-01

It is known from previous research that physical exercise prevents long-term memory deficits induced by maternal deprivation in rats. But we could not assume similar effects of physical exercise on short-term memory, as short- and long-term memories are known to result from some different memory consolidation processes. Here we demonstrated that, in addition to long-term memory deficit, the short-term memory deficit resultant from maternal deprivation in object recognition and aversive memory tasks is also prevented by physical exercise. Additionally, one of the mechanisms by which the physical exercise influences the memory processes involves its effects attenuating the oxidative damage in the maternal deprived rats' hippocampus and prefrontal cortex.

Managing diabetes at high altitude: personal experience with support from a Multidisciplinary Physical Activity and Diabetes Clinic.

PubMed

Malcolm, Gary; Rilstone, Sian; Sivasubramaniyam, Sivasujan; Jairam, Carol; Chew, Stephen; Oliver, Nick; Hill, Neil E

2017-01-01

Physical activity is important for well-being but can be challenging for people with diabetes. Data informing support of specialist activities such as climbing and high-altitude trekking are limited. A 42-year-old man with type 1 diabetes (duration 30 years) attended a Multidisciplinary Physical Activity and Diabetes Clinic planning to climb Mont Blanc during the summer and trek to Everest Base Camp in the autumn. His aims were to complete these adventures without his diabetes impacting on their success. We report the information provided that enabled him to safely facilitate his objectives, in particular, the requirement for frequent checking of blood glucose levels, the effects of altitude on insulin dose requirements, and recognition that acute mountain sickness may mimic the symptoms of hypoglycaemia and vice versa. Real-time continuous glucose monitoring was made available for his treks. The effects of high altitude on blood glucose results and glycaemic variability while treated on multiple daily injections of insulin are reported. In addition, we present a first-person account of his experience and lessons learnt from managing diabetes at high altitude. A dedicated Multidisciplinary Physical Activity and Diabetes Clinic delivering individualised, evidence-based, patient-focused advice on the effects of altitude on blood glucose levels, and provision of real-time continuous glucose monitoring enabled uneventful completion of a trek to Everest Base Camp in a person with type 1 diabetes.

Material recognition based on thermal cues: Mechanisms and applications.

PubMed

Ho, Hsin-Ni

2018-01-01

Some materials feel colder to the touch than others, and we can use this difference in perceived coldness for material recognition. This review focuses on the mechanisms underlying material recognition based on thermal cues. It provides an overview of the physical, perceptual, and cognitive processes involved in material recognition. It also describes engineering domains in which material recognition based on thermal cues have been applied. This includes haptic interfaces that seek to reproduce the sensations associated with contact in virtual environments and tactile sensors aim for automatic material recognition. The review concludes by considering the contributions of this line of research in both science and engineering.

Material recognition based on thermal cues: Mechanisms and applications

PubMed Central

Ho, Hsin-Ni

2018-01-01

ABSTRACT Some materials feel colder to the touch than others, and we can use this difference in perceived coldness for material recognition. This review focuses on the mechanisms underlying material recognition based on thermal cues. It provides an overview of the physical, perceptual, and cognitive processes involved in material recognition. It also describes engineering domains in which material recognition based on thermal cues have been applied. This includes haptic interfaces that seek to reproduce the sensations associated with contact in virtual environments and tactile sensors aim for automatic material recognition. The review concludes by considering the contributions of this line of research in both science and engineering. PMID:29687043

Maternal Eating and Physical Activity Strategies and their Relation with Children's Nutritional Status.

PubMed

Flores-Peña, Yolanda; Ortiz-Félix, Rosario Edith; Cárdenas-Villarreal, Velia Margarita; Ávila-Alpirez, Hermelinda; Alba-Alba, Corina Mariela; Hernández-Carranco, Roandy Gaspar

2014-01-01

to describe the maternal eating and physical activity strategies (monitoring, discipline, control, limits and reinforcement) [MEES]; to determine the relation between MEES and the child's nutritional status [body mass index (BMI) and body fat percentage (BFP)]; to verify whether the MEES differ according to the child's nutritional status. participants were 558 mothers and children (3 to 11 years of age) who studied at public schools. The Parental Strategies for Eating and Activity Scale (PEAS) was applied and the child's weight, height and BFP were measured. For analysis purposes, descriptive statistics were obtained, using multiple linear regression and the Kruskal-Wallis test. the highest mean score was found for reinforcement (62.72) and the lowest for control (50.07). Discipline, control and limits explained 12% of the BMI, while discipline and control explained 6% of the BFP. Greater control is found for obese children (χ²=38.36, p=0.001) and greater reinforcement for underweight children (χ²=7.19, p<0.05). the mothers exert greater control (pressure to eat) over obese children and greater recognition (congratulating due to healthy eating) in underweight children. Modifications in parental strategies are recommended with a view to strengthening healthy eating and physical activity habits.

Which Stratum of Urban Elderly Is Most Vulnerable for Dementia?

PubMed Central

2016-01-01

Many factors associated with a patient's lifestyle may disrupt timely access to dementia diagnosis and management. The aim of this study was to compare characteristics of lifestyle factors at the time of initial evaluation for dementia across degrees of dementia, and to identify risk factors relating to late detection of dementia, in order to understand the various lifestyle barriers to timely recognition of the disease. We reviewed medical records of 1,409 subjects who were diagnosed as dementia among 35,723 inhabitants of Gwangjin-gu. Dementia severity was divided into three degrees. Age, sex, education, income, smoking, heavy drinking, physical activity, religion, and living conditions were evaluated. There was a significantly greater proportion of individuals who were old age, female, less educated, who had never smoked or drank heavily, without physical activity, with no religious activity and living with family other than spouse in the severe dementia group. The lifestyle risks of late detection were old age, lower education, less social interactions, less physical activity or living with family. We can define this group of patients as the vulnerable stratum to dementia evaluation. Health policy or community health services might find ways to better engage patients in this vulnerable stratum to dementia. PMID:27550494

Potential Collaborative Research topics with Korea’s Agency for Defense Development

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

Farrar, Charles R.; Todd, Michael D.

2012-08-23

This presentation provides a high level summary of current research activities at the Los Alamos National Laboratory (LANL)-University of California Jacobs School of Engineering (UCSD) Engineering Institute that will be presented at Korea's Agency for Defense Development (ADD). These research activities are at the basic engineering science level with different level of maturity ranging from initial concepts to field proof-of-concept demonstrations. We believe that all of these activities are appropriate for collaborative research activities with ADD subject to approval by each institution. All the activities summarized herein have the common theme that they are multi-disciplinary in nature and typically involvedmore » the integration of high-fidelity predictive modeling, advanced sensing technologies and new development in information technology. These activities include: Wireless Sensor Systems, Swarming Robot sensor systems, Advanced signal processing (compressed sensing) and pattern recognition, Model Verification and Validation, Optimal/robust sensor system design, Haptic systems for large-scale data processing, Cyber-physical security for robots, Multi-source energy harvesting, Reliability-based approaches to damage prognosis, SHMTools software development, and Cyber-physical systems advanced study institute.« less

Calibration of raw accelerometer data to measure physical activity: A systematic review.

PubMed

de Almeida Mendes, Márcio; da Silva, Inácio C M; Ramires, Virgílio V; Reichert, Felipe F; Martins, Rafaela C; Tomasi, Elaine

2018-03-01

Most of calibration studies based on accelerometry were developed using count-based analyses. In contrast, calibration studies based on raw acceleration signals are relatively recent and their evidences are incipient. The aim of the current study was to systematically review the literature in order to summarize methodological characteristics and results from raw data calibration studies. The review was conducted up to May 2017 using four databases: PubMed, Scopus, SPORTDiscus and Web of Science. Methodological quality of the included studies was evaluated using the Landis and Koch's guidelines. Initially, 1669 titles were identified and, after assessing titles, abstracts and full-articles, 20 studies were included. All studies were conducted in high-income countries, most of them with relatively small samples and specific population groups. Physical activity protocols were different among studies and the indirect calorimetry was the criterion measure mostly used. High mean values of sensitivity, specificity and accuracy from the intensity thresholds of cut-point-based studies were observed (93.7%, 91.9% and 95.8%, respectively). The most frequent statistical approach applied was machine learning-based modelling, in which the mean coefficient of determination was 0.70 to predict physical activity energy expenditure. Regarding the recognition of physical activity types, the mean values of accuracy for sedentary, household and locomotive activities were 82.9%, 55.4% and 89.7%, respectively. In conclusion, considering the construct of physical activity that each approach assesses, linear regression, machine-learning and cut-point-based approaches presented promising validity parameters. Copyright © 2017 Elsevier B.V. All rights reserved.

Perceptual and affective mechanisms in facial expression recognition: An integrative review.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2016-09-01

Facial expressions of emotion involve a physical component of morphological changes in a face and an affective component conveying information about the expresser's internal feelings. It remains unresolved how much recognition and discrimination of expressions rely on the perception of morphological patterns or the processing of affective content. This review of research on the role of visual and emotional factors in expression recognition reached three major conclusions. First, behavioral, neurophysiological, and computational measures indicate that basic expressions are reliably recognized and discriminated from one another, albeit the effect may be inflated by the use of prototypical expression stimuli and forced-choice responses. Second, affective content along the dimensions of valence and arousal is extracted early from facial expressions, although this coarse affective representation contributes minimally to categorical recognition of specific expressions. Third, the physical configuration and visual saliency of facial features contribute significantly to expression recognition, with "emotionless" computational models being able to reproduce some of the basic phenomena demonstrated in human observers. We conclude that facial expression recognition, as it has been investigated in conventional laboratory tasks, depends to a greater extent on perceptual than affective information and mechanisms.

A Qualitative Examination of Situational Risk Recognition Among Female Victims of Physical Intimate Partner Violence.

PubMed

Sherrill, Andrew M; Bell, Kathryn M; Wyngarden, Nicole

2016-07-01

Little is known about intimate partner violence (IPV) victims' situational risk recognition, defined as the ability to identify situational factors that signal imminent risk of victimization. Using semi-structured interviews, qualitative data were collected from a community sample of 31 female victims of IPV episodes involving substance use. Thirteen themes were identified, the most prevalent being related to the partner's verbal behavior, tone of voice, motor behavior, alcohol or drug use, and facial expression. Participants reporting at least some anticipation of physical aggression (61.3% of the sample) tended to identify multiple factors (M = 3.47), suggesting numerous situational features often contribute to situational risk recognition. © The Author(s) 2015.

Selected Cutaneous Disorders in Athletes

PubMed Central

Walker, James D.

1988-01-01

The author discusses selected cutaneous diseases seen in the athlete. These diseases may be caused by interaction with the elements, the playing surface, other athletes, or the clothing or equipment worn during sport. All of these dermatological conditions are relatively common, but the physically active individual can suffer from these maladies and their complications more often than the inactive person. The emphasis in caring for the participant is on prevention, early recognition and practical aspects of management of cutaneous diseases. PMID:21264034

``We're all unisex anyway'': The persistent discourse of gender neutrality in physics

NASA Astrophysics Data System (ADS)

Gonsalves, Allison

2015-03-01

Doctoral physics students have stories about the kinds of actions, behaviours and ways of doing physics that enable them to be recognized as physicists. This presentation will illuminate some of these stories through a lens that scrutinizes how discourses about gender can shape both the stories that students tell and the behaviours they practice to achieve recognition in their field. Through observations, photo-elicitation, and life history interviews, eleven men and women shared stories about their experiences with physics, and the contexts that have enabled or constrained their participation in doctoral physics. The results of this study revealed that recognition was often achieved through the reproduction or reworking of persistent discourses of gender norms. This presentation will explore the particularly persistent discourse of gender neutrality in physics. I will explore how this discourse is constructed, how it can be contested, and how it may be constraining for both men and women students. The construction of physics as gender neutral can pose conflicts of identity for students who feel the need to refigure their gender performances in ways that permit recognition as ``physics people.'' This presentation will look at two case studies that demonstrate the conflict students experience between expressions of femininity and doing physics against the backdrop of gender neutrality. I will discuss the problematic of gender neutrality, and I will also discuss some of the creative solutions doctoral students adopt to navigate discourses of gender in this neutral terrain.

[Analysis of the factors related to the needs of patients with cancer].

PubMed

Lee, Jung A; Lee, Sun Hee; Park, Jong Hyock; Park, Jae Hyun; Kim, Sung Gyeong; Seo, Ju Hyun

2010-05-01

Limited research has investigated the specific needs of patients with cancer. This study was performed to explore patients needs and the related factors. The data were collected by 1 National Cancer Center and 9 regional cancer centers in Korea. An interview survey was performed with using a structured questionnaire for the subjects (2,661 patients who gave written informed consent to participate) survey 4 months after diagnosis and review of medical records. Data were analyzed using t-test, ANOVA and multiple regression analysis. When comparing the relating factors related with patient needs to the sociodemographic characteristics, the female group showed a higher level of recognition for physical symptoms, social support needs. The younger group showed a significantly higher level of recognition for health care staff, psychological problems, information and education, social support, hospital services needs. In addition, the higher educated group showed a higher level of recognition for health care staff, physical symptoms, social support needs. The higher income and office workers group showed a higher level of recognition for hospital services needs. When comparing the relating factors related with patient needs to the cancer, the breast cancer group showed a higher level of recognition for all needs excluding physical symptoms, accessibility and financial support needs. The combined radiotherapy with surgery and chemotherapy group showed a higher level of recognition for psychological problems, information and education, social support needs. This study showed that needs on patient with cancer was significantly influenced by female, higher education, lower income, having religion, office worker, liver cancer, breast cancer, colon cancer, chemotherapy, and combined therapy.

Transgenerational effects of maternal depression on affect recognition in children.

PubMed

Kluczniok, Dorothea; Hindi Attar, Catherine; Fydrich, Thomas; Fuehrer, Daniel; Jaite, Charlotte; Domes, Gregor; Winter, Sibylle; Herpertz, Sabine C; Brunner, Romuald; Boedeker, Katja; Bermpohl, Felix

2016-01-01

The association between maternal depression and adverse emotional and behavioral outcomes in children is well established. One associated factor might be altered affect recognition which may be transmitted transgenerationally. Individuals with history of depression show biased recognition of sadness. Our aim was to investigate parallels in maternal and children's affect recognition with remitted depressed mothers. 60 Mother-child dyads completed an affect recognition morphing task. We examined two groups of remitted depressed mothers, with and without history of physical or sexual abuse, and a group of healthy mothers without history of physical or sexual abuse. Children were between 5 and 12 years old. Across groups, mothers identified happy faces fastest. Mothers with remitted depression showed a higher accuracy and response bias for sadness. We found corresponding results in their children. Maternal and children's bias and accuracy for sadness were positively correlated. Effects of remitted depression were found independent of maternal history of physical or sexual abuse. Our sample size was relatively small and further longitudinal research is needed to investigate how maternal and children's affect recognition are associated with behavioral and emotional outcomes in the long term. Our data suggest a negative processing bias in mothers with remitted depression which might represent both the perpetuation of and vulnerability to depression. Children of remitted depressed mothers appear to be exposed to this processing bias outside acute depressive episodes. This may promote the development of a corresponding processing bias in the children and could make children of depressed mothers more vulnerable to depressive disorders themselves. Copyright © 2015 Elsevier B.V. All rights reserved.

The evaluation of a mental health facilitator in general practice: effects on recognition, management, and outcome of mental illness.

PubMed

Bashir, K; Blizard, B; Bosanquet, A; Bosanquet, N; Mann, A; Jenkins, R

2000-08-01

Facilitation uses personal contact between the facilitator and the professional to encourage good practice and better service organisation. The model has been applied to physical illness but not to psychiatric disorders. To determine if a non-specialist facilitator can improve the recognition, management, and outcome of psychiatric illness presenting to general practitioners (GPs). Six practices were visited over an 18-month period by a facilitator whose activities included providing guidelines and organising training initiatives. Six other practices acted as controls. Recognition (identification index of family doctors), management (psychotropic prescribing, psychological consultations with the GP, specialist mental health treatment, and the use of medical interventions and investigations), and patient outcome at four months were assessed before and after intervention. The mean identification index of facilitator GPs rose from 0.51 to 0.64 following intervention, while that of the control GPs fell from 0.67 to 0.59 (P = 0.046). The facilitator had no detectable effect on management or patient outcome. The facilitator improved recognition of psychiatric illness by GPs. Generic facilitators can be trained to take on a mental health role; however, the failure to achieve more fundamental changes in treatment and outcome implies that facilitator intervention requires development.

Interprofessional, simulation-based technology-enhanced learning to improve physical health care in psychiatry: The recognition and assessment of medical problems in psychiatric settings course.

PubMed

Akroyd, Mike; Jordan, Gary; Rowlands, Paul

2016-06-01

People with serious mental illness have reduced life expectancy compared with a control population, much of which is accounted for by significant physical comorbidity. Frontline clinical staff in mental health often lack confidence in recognition, assessment and management of such 'medical' problems. Simulation provides one way for staff to practise these skills in a safe setting. We produced a multidisciplinary simulation course around recognition and assessment of medical problems in psychiatric settings. We describe an audit of strategic and design aspects of the recognition and assessment of medical problems in psychiatric settings course, using the Department of Health's 'Framework for Technology Enhanced Learning' as our audit standards. At the same time as highlighting areas where recognition and assessment of medical problems in psychiatric settings adheres to these identified principles, such as the strategic underpinning of the approach, and the means by which information is collected, reviewed and shared, it also helps us to identify areas where we can improve. © The Author(s) 2014.

An adaptive Hidden Markov Model for activity recognition based on a wearable multi-sensor device

USDA-ARS?s Scientific Manuscript database

Human activity recognition is important in the study of personal health, wellness and lifestyle. In order to acquire human activity information from the personal space, many wearable multi-sensor devices have been developed. In this paper, a novel technique for automatic activity recognition based o...

Consumer response to healthy eating, physical activity and weight-related recommendations: a systematic review.

PubMed

Boylan, S; Louie, J C Y; Gill, T P

2012-07-01

Strong evidence linking poor diet and lack of physical activity to risk of obesity and related chronic disease has supported the development and promotion of guidelines to improve population health. Still, obesity continues to escalate as a major health concern, and so the impact of weight-related guidelines on behaviour is unclear. The aim of this review was to examine consumer response to weight-related guidelines. A systematic literature search was performed using Medline, PsycInfo, ProQuest Central and additional searches using Google and reference lists. Of the 1,765 articles identified, 46 relevant titles were included. Most studies examined attitudes towards content, source, tailoring and comprehension of dietary guidelines. Many respondents reported that guidelines were confusing, and that simple, clear, specific, realistic, and in some cases, tailored guidelines are required. Recognition of guidelines did not signify understanding nor did perceived credibility of a source guarantee utilization of guidelines. There was a lack of studies assessing: the impact of guidelines on behaviour; responses to physical activity guidelines; responses among males and studies undertaken in developing countries. Further research is needed, in particular regarding responses to physical activity guidelines and guidelines in different populations. Communication professionals should assist health professionals in the development of accurate and effective weight-related guidelines. © 2012 The Authors. obesity reviews © 2012 International Association for the Study of Obesity.

A Novel Energy-Efficient Approach for Human Activity Recognition.

PubMed

Zheng, Lingxiang; Wu, Dihong; Ruan, Xiaoyang; Weng, Shaolin; Peng, Ao; Tang, Biyu; Lu, Hai; Shi, Haibin; Zheng, Huiru

2017-09-08

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper.

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2014 CFR

2014-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2013 CFR

2013-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

33 CFR 104.210 - Company Security Officer (CSO).

Code of Federal Regulations, 2012 CFR

2012-07-01

... operational limitations; (vi) Methods of conducting audits, inspection and control and monitoring techniques... threats and patterns; (ix) Recognition and detection of dangerous substances and devices; (x) Recognition...) Techniques used to circumvent security measures; (xii) Methods of physical screening and non-intrusive...

Comparing mental health literacy and physical health literacy: an exploratory study.

PubMed

Wickstead, Robert; Furnham, Adrian

2017-10-01

This study compared mental health and physical health literacy using five health problems from each area. The aim was to determine whether the same group had better physical than mental health literacy Method: A sample of 263 participants completed an online questionnaire requiring them to name a problem/illness described in 10 vignettes and suggest treatment options. Five vignettes described mental health problems (anxiety, bipolar-disorder, depression, OCPD and schizophrenia) and five physical problems (angina, COPD, diabetes, a heart attack, and sinusitis). Participants were also asked to rate their sympathy and estimates of prevalence for each disorder. Recognition of the mental health disorders was superior compared recognition of the physical disorders. Analysis of treatment beliefs, sympathy and prevalence ratings also showed significant differences between disorders. Results highlight the importance of education and the lack of public knowledge regarding major physical health conditions.

Neuroanatomical substrates involved in unrelated false facial recognition.

PubMed

Ronzon-Gonzalez, Eliane; Hernandez-Castillo, Carlos R; Pasaye, Erick H; Vaca-Palomares, Israel; Fernandez-Ruiz, Juan

2017-11-22

Identifying faces is a process central for social interaction and a relevant factor in eyewitness theory. False recognition is a critical mistake during an eyewitness's identification scenario because it can lead to a wrongful conviction. Previous studies have described neural areas related to false facial recognition using the standard Deese/Roediger-McDermott (DRM) paradigm, triggering related false recognition. Nonetheless, misidentification of faces without trying to elicit false memories (unrelated false recognition) in a police lineup could involve different cognitive processes, and distinct neural areas. To delve into the neural circuitry of unrelated false recognition, we evaluated the memory and response confidence of participants while watching faces photographs in an fMRI task. Functional activations of unrelated false recognition were identified by contrasting the activation on this condition vs. the activations related to recognition (hits) and correct rejections. The results identified the right precentral and cingulate gyri as areas with distinctive activations during false recognition events suggesting a conflict resulting in a dysfunction during memory retrieval. High confidence suggested that about 50% of misidentifications may be related to an unconscious process. These findings add to our understanding of the construction of facial memories and its biological basis, and the fallibility of the eyewitness testimony.

Response-related fMRI of veridical and false recognition of words.

PubMed

Heun, Reinhard; Jessen, Frank; Klose, Uwe; Erb, Michael; Granath, Dirk-Oliver; Grodd, Wolfgang

2004-02-01

Studies on the relation between local cerebral activation and retrieval success usually compared high and low performance conditions, and thus showed performance-related activation of different brain areas. Only a few studies directly compared signal intensities of different response categories during retrieval. During verbal recognition, we recently observed increased parieto-occipital activation related to false alarms. The present study intends to replicate and extend this observation by investigating common and differential activation by veridical and false recognition. Fifteen healthy volunteers performed a verbal recognition paradigm using 160 learned target and 160 new distractor words. The subjects had to indicate whether they had learned the word before or not. Echo-planar MRI of blood-oxygen-level-dependent signal changes was performed during this recognition task. Words were classified post hoc according to the subjects' responses, i.e. hits, false alarms, correct rejections and misses. Response-related fMRI-analysis was used to compare activation associated with the subjects' recognition success, i.e. signal intensities related to the presentation of words were compared by the above-mentioned four response types. During recognition, all word categories showed increased bilateral activation of the inferior frontal gyrus, the inferior temporal gyrus, the occipital lobe and the brainstem in comparison with the control condition. Hits and false alarms activated several areas including the left medial and lateral parieto-occipital cortex in comparison with subjectively unknown items, i.e. correct rejections and misses. Hits showed more pronounced activation in the medial, false alarms in the lateral parts of the left parieto-occipital cortex. Veridical and false recognition show common as well as different areas of cerebral activation in the left parieto-occipital lobe: increased activation of the medial parietal cortex by hits may correspond to true recognition, increased activation of the parieto-occipital cortex by false alarms may correspond to familiarity decisions. Further studies are needed to investigate the reasons for false decisions in healthy subjects and patients with memory problems.

Modifying Resilience Mechanisms in At-Risk Individuals: A Controlled Study of Mindfulness Training in Marines Preparing for Deployment

DTIC Science & Technology

2014-01-01

remains unclear whether self - referential FIGURE 3. Activation of the Right Insula and Anterior Cingulate Cortex During Emotion Recognition in Marines...and envi- ronment. The brain is the central organ of stress response and recovery, and essential to these processes is an individual’s awareness of his...traditional “five senses” (8), is a process through which the brain monitors and updates the body about its overall physical state, including its

Innate immunity of fish (overview).

PubMed

Magnadóttir, Bergljót

2006-02-01

The innate immune system is the only defence weapon of invertebrates and a fundamental defence mechanism of fish. The innate system also plays an instructive role in the acquired immune response and homeostasis and is therefore equally important in higher vertebrates. The innate system's recognition of non-self and danger signals is served by a limited number of germ-line encoded pattern recognition receptors/proteins, which recognise pathogen associated molecular patterns like bacterial and fungal glycoproteins and lipopolysaccharides and intracellular components released through injury or infection. The innate immune system is divided into physical barriers, cellular and humoral components. Humoral parameters include growth inhibitors, various lytic enzymes and components of the complement pathways, agglutinins and precipitins (opsonins, primarily lectins), natural antibodies, cytokines, chemokines and antibacterial peptides. Several external and internal factors can influence the activity of innate immune parameters. Temperature changes, handling and crowding stress can have suppressive effects on innate parameters, whereas several food additives and immunostimulants can enhance different innate factors. There is limited data available about the ontogenic development of the innate immunological system in fish. Active phagocytes, complement components and enzyme activity, like lysozyme and cathepsins, are present early in the development, before or soon after hatching.

Multiview human activity recognition system based on spatiotemporal template for video surveillance system

NASA Astrophysics Data System (ADS)

Kushwaha, Alok Kumar Singh; Srivastava, Rajeev

2015-09-01

An efficient view invariant framework for the recognition of human activities from an input video sequence is presented. The proposed framework is composed of three consecutive modules: (i) detect and locate people by background subtraction, (ii) view invariant spatiotemporal template creation for different activities, (iii) and finally, template matching is performed for view invariant activity recognition. The foreground objects present in a scene are extracted using change detection and background modeling. The view invariant templates are constructed using the motion history images and object shape information for different human activities in a video sequence. For matching the spatiotemporal templates for various activities, the moment invariants and Mahalanobis distance are used. The proposed approach is tested successfully on our own viewpoint dataset, KTH action recognition dataset, i3DPost multiview dataset, MSR viewpoint action dataset, VideoWeb multiview dataset, and WVU multiview human action recognition dataset. From the experimental results and analysis over the chosen datasets, it is observed that the proposed framework is robust, flexible, and efficient with respect to multiple views activity recognition, scale, and phase variations.

Model and algorithmic framework for detection and correction of cognitive errors.

PubMed

Feki, Mohamed Ali; Biswas, Jit; Tolstikov, Andrei

2009-01-01

This paper outlines an approach that we are taking for elder-care applications in the smart home, involving cognitive errors and their compensation. Our approach involves high level modeling of daily activities of the elderly by breaking down these activities into smaller units, which can then be automatically recognized at a low level by collections of sensors placed in the homes of the elderly. This separation allows us to employ plan recognition algorithms and systems at a high level, while developing stand-alone activity recognition algorithms and systems at a low level. It also allows the mixing and matching of multi-modality sensors of various kinds that go to support the same high level requirement. Currently our plan recognition algorithms are still at a conceptual stage, whereas a number of low level activity recognition algorithms and systems have been developed. Herein we present our model for plan recognition, providing a brief survey of the background literature. We also present some concrete results that we have achieved for activity recognition, emphasizing how these results are incorporated into the overall plan recognition system.

The cingulo-opercular network provides word-recognition benefit.

PubMed

Vaden, Kenneth I; Kuchinsky, Stefanie E; Cute, Stephanie L; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2013-11-27

Recognizing speech in difficult listening conditions requires considerable focus of attention that is often demonstrated by elevated activity in putative attention systems, including the cingulo-opercular network. We tested the prediction that elevated cingulo-opercular activity provides word-recognition benefit on a subsequent trial. Eighteen healthy, normal-hearing adults (10 females; aged 20-38 years) performed word recognition (120 trials) in multi-talker babble at +3 and +10 dB signal-to-noise ratios during a sparse sampling functional magnetic resonance imaging (fMRI) experiment. Blood oxygen level-dependent (BOLD) contrast was elevated in the anterior cingulate cortex, anterior insula, and frontal operculum in response to poorer speech intelligibility and response errors. These brain regions exhibited significantly greater correlated activity during word recognition compared with rest, supporting the premise that word-recognition demands increased the coherence of cingulo-opercular network activity. Consistent with an adaptive control network explanation, general linear mixed model analyses demonstrated that increased magnitude and extent of cingulo-opercular network activity was significantly associated with correct word recognition on subsequent trials. These results indicate that elevated cingulo-opercular network activity is not simply a reflection of poor performance or error but also supports word recognition in difficult listening conditions.

Changing the individual to promote health-enhancing physical activity: the difficulties of producing evidence and translating it into practice.

PubMed

Blamey, Avril; Mutrie, Nanette

2004-08-01

This paper presents conclusions from recent systematic reviews and highlights individually targeted interventions that are effective at increasing physical activity. It discusses the limitations of currently available evidence, considers what factors lead to these limitations and what barriers exist in terms of implementing the evidence as part of local and national policy and practice. Barriers present themselves in terms of getting evidence into practice and in terms of ensuring that practice informs the evidence base. These barriers include difficulties in conducting systematic reviews, disaggregating knowledge from complex interventions, making local adaptations to existing evidence, the lack of an evaluation culture, ethical and pragmatic difficulties in designing interventions, selecting appropriate outcome measures, poor designs and implementation of evidence and, finally, a recognition that policy making is not only based on the available evidence. New and more integrated approaches to evaluation and to practice are needed.

Connecting High School Physics Experiences, Outcome Expectations, Physics Identity, and Physics Career Choice: A Gender Study

ERIC Educational Resources Information Center

Hazari, Zahra; Sonnert, Gerhard; Sadler, Philip M.; Shanahan, Marie-Claire

2010-01-01

This study explores how students' physics identities are shaped by their experiences in high school physics classes and by their career outcome expectations. The theoretical framework focuses on physics identity and includes the dimensions of student performance, competence, recognition by others, and interest. Drawing data from the Persistence…

Voluntary running depreciates the requirement of Ca2+-stimulated cAMP signaling in synaptic potentiation and memory formation

PubMed Central

Zheng, Fei; Zhang, Ming; Ding, Qi; Sethna, Ferzin; Yan, Lily; Moon, Changjong; Yang, Miyoung

2016-01-01

Mental health and cognitive functions are influenced by both genetic and environmental factors. Although having active lifestyle with physical exercise improves learning and memory, how it interacts with the specific key molecular regulators of synaptic plasticity is largely unknown. Here, we examined the effects of voluntary running on long-term potentiation (LTP) and memory formation in mice lacking type 1 adenylyl cyclase (AC1), a neurospecific synaptic enzyme that contributes to Ca2+-stimulated cAMP production. Following 1 mo of voluntary running-wheel exercise, the impaired LTP and object recognition memory in AC1 knockout (KO) mice were significantly attenuated. Running up-regulated exon II mRNA level of BDNF (brain-derived neurotrophic factor), though it failed to increase exon I and IV mRNAs in the hippocampus of AC1 KO mice. Intrahippocampal infusion of recombinant BDNF was sufficient to rescue LTP and object recognition memory defects in AC1 KO mice. Therefore, voluntary running and exogenous BDNF application overcome the defective Ca2+-stimulated cAMP signaling. Our results also demonstrate that alteration in Ca2+-stimulated cAMP can affect the molecular outcome of physical exercise. PMID:27421897

Productive activity and life satisfaction in Korean elderly women.

PubMed

Kim, Ju-Hyun

2013-01-01

The purpose of this study is to explain the effect of participation in productive activities on life satisfaction and its implications for social evaluation of productive aging. This study uses data collected from 1,250 elderly women living in urban areas. The regression model was used to examine the influence of elderly women's participation in productive activities on their life satisfaction. Elderly women who participate in volunteer work, learning, and social group activities commonly recognized their activities as meaningful, feeling like worthwhile members of society, and evaluated such activities as very positive. In contrast, elderly women who participated in household chores and family care activities expressed a negative life satisfaction. The difference in life satisfaction regarding productive activities stems not only from the physical and environmental differences but also from the gap between the official social value underpinned by the recognition of surrounding people, their support, and the value of productive activities.

Wearable motion sensors to continuously measure real-world physical activities.

PubMed

Dobkin, Bruce H

2013-12-01

Rehabilitation for sensorimotor impairments aims to improve daily activities, walking, exercise, and motor skills. Monitoring of practice and measuring outcomes, however, is usually restricted to laboratory-based procedures and self-reports. Mobile health devices may reverse these confounders of daily care and research trials. Wearable, wireless motion sensor data, analyzed by activity pattern-recognition algorithms, can describe the type, quantity, and quality of mobility-related activities in the community. Data transmission from the sensors to a cell phone and the Internet enable continuous monitoring. Remote access to laboratory quality data about walking speed, duration and distance, gait asymmetry and smoothness of movements, as well as cycling, exercise, and skills practice, opens new opportunities to engage patients in progressive, personalized therapies with feedback about the performance. Clinical trial designs will be able to include remote verification of the integrity of complex physical interventions and compliance with practice, as well as capture repeated, ecologically sound, ratio scale outcome measures. Given the progressively falling cost of miniaturized wearable gyroscopes, accelerometers, and other physiologic sensors, as well as inexpensive data transmission, sensing systems may become as ubiquitous as cell phones for healthcare. Neurorehabilitation can develop these mobile health platforms for daily care and clinical trials to improve exercise and fitness, skills learning, and physical functioning.

The involvement of emotion recognition in affective theory of mind.

PubMed

Mier, Daniela; Lis, Stefanie; Neuthe, Kerstin; Sauer, Carina; Esslinger, Christine; Gallhofer, Bernd; Kirsch, Peter

2010-11-01

This study was conducted to explore the relationship between emotion recognition and affective Theory of Mind (ToM). Forty subjects performed a facial emotion recognition and an emotional intention recognition task (affective ToM) in an event-related fMRI study. Conjunction analysis revealed overlapping activation during both tasks. Activation in some of these conjunctly activated regions was even stronger during affective ToM than during emotion recognition, namely in the inferior frontal gyrus, the superior temporal sulcus, the temporal pole, and the amygdala. In contrast to previous studies investigating ToM, we found no activation in the anterior cingulate, commonly assumed as the key region for ToM. The results point to a close relationship of emotion recognition and affective ToM and can be interpreted as evidence for the assumption that at least basal forms of ToM occur by an embodied, non-cognitive process. Copyright © 2010 Society for Psychophysiological Research.

Crucial aspects promoting meaning and purpose in life: perceptions of nursing home residents.

PubMed

Drageset, Jorunn; Haugan, Gørill; Tranvåg, Oscar

2017-10-30

Meaning and purpose in life are fundamental to human beings. In changing times, with an aging population and increased life expectancy, the need for health care services and long-term care is likely to grow. More deeply understanding how older long-term care residents perceive meaning and purpose in life is critical for improving the quality of care and the residents' quality of life. The purpose of this study was to explore crucial aspects promoting nursing home residents' experience of meaning and purpose in everyday life. An exploratory hermeneutical design with qualitative interviews for collecting data. Four key experiences were found to promote meaning and purpose in life: 1) physical and mental well-being, 2) belonging and recognition, 3) personally treasured activities and 4) spiritual closeness and connectedness. In supporting meaning and purpose in life of nursing home residents, the residents' everyday well-being should be a central focus of care and facilitate personally treasured activities. Focused attention should also be given to the meaning-making power of experiencing belonging, recognition and spiritual connectedness.

Interprofessional, simulation-based technology-enhanced learning to improve physical healthcare in psychiatry: The RAMPPS course.

PubMed

Akroyd, Mike; Jordan, Gary; Rowlands, Paul

2016-06-01

People with serious mental illness have reduced life expectancy compared with a control population, much of which is accounted for by significant physical comorbidity. Frontline clinical staff in mental health often lack confidence in recognition, assessment and management of such 'medical' problems. Simulation provides one way for staff to practise these skills in a safe setting. We produced a multidisciplinary simulation course around recognition and assessment of medical problems in psychiatric settings. We describe an audit of strategic and design aspects of the recognition and assessment of medical problems in psychiatric settings, using the Department of Health's 'Framework for Technology Enhanced Learning' as our audit standards. At the same time, as highlighting areas where recognition and assessment of medical problems in psychiatric settings adheres to these identified principles, such as the strategic underpinning of the approach, and the means by which information is collected, reviewed and shared, it also helps us to identify areas where we can improve. © The Author(s) 2014.

Social Goals in Urban Physical Education: Relationships with Effort and Disruptive Behavior

ERIC Educational Resources Information Center

Garn, Alex; McCaughtry, Nate; Shen, Bo; Martin, Jeffrey J.; Fahlman, Mariane M.

2011-01-01

This study investigated the relationships among four distinct types of social goals, effort, and disruptive behavior in urban physical education. Social responsibility, affiliation, recognition, status goals, along with effort and disruptive behavior in physical education were reported by high school physical education students (N = 314) from…

Quantifying the bystander-effect of 2.5G mobile telephones on the speech perception of digital hearing aid users.

PubMed

Vlastarakos, P V; Nikolopoulos, T P; Manolopoulos, L; Stamou, A; Halkiotis, K K; Ferekidis, E; Georgiou, E

2012-01-01

To quantify the bystander-effect of 2.5G mobile telephones (2.5G-MTs) on the speech perception of digital hearing-aid (dHA) users. Differences in the susceptibility of behind-the-ear (BTE) compared to in-to-the-ear (ITE) dHAs were also assessed. Prospective-comparative study conducted at a tertiary referral centre (ENT Department) and a HA-fitting laboratory. Key-word recognition scores from open-sentence lists were calculated. Power-analysis determined that a minimum of 60 subjects with SNHL (30 in each group), using either BTE or ITE dHAs, were required for reliable study outcomes. Sixty-four adults were tested with a functioning 2.5G-MT at almost physical contact with their ear; thirty subjects used BTE and 34 ITE dHAs. Aided word recognition score differences between studied groups and within each group, while a 2.5G-MT was activated. Cut-off inclusion criterion regarding baseline aided word recognition score was 75%. Baseline aided word recognition scores for ITE dHAs were better compared to BTE ones (p < 0.01). Following the 2.5G-MT activation, this difference disappeared. No statistically significant difference in word recognition was observed between the examined groups, or within the BTE group, from the bystander-effect of the 2.5G-MT. ITE dHAs proved more susceptible to electromagnetic interference (p < 0.05). The bystander-effect of 2.5G-MTs on the speech perception of dHA users is either minimal, or not significant. The observed compatibility has a positive impact on the lives of millions of people worldwide. The long-standing theory of more interference in BTE compared to ITE HAs is not confirmed by the results of the present study. EBM level of evidence: 2c.

A Novel Energy-Efficient Approach for Human Activity Recognition

PubMed Central

Zheng, Lingxiang; Wu, Dihong; Ruan, Xiaoyang; Weng, Shaolin; Tang, Biyu; Lu, Hai; Shi, Haibin

2017-01-01

In this paper, we propose a novel energy-efficient approach for mobile activity recognition system (ARS) to detect human activities. The proposed energy-efficient ARS, using low sampling rates, can achieve high recognition accuracy and low energy consumption. A novel classifier that integrates hierarchical support vector machine and context-based classification (HSVMCC) is presented to achieve a high accuracy of activity recognition when the sampling rate is less than the activity frequency, i.e., the Nyquist sampling theorem is not satisfied. We tested the proposed energy-efficient approach with the data collected from 20 volunteers (14 males and six females) and the average recognition accuracy of around 96.0% was achieved. Results show that using a low sampling rate of 1Hz can save 17.3% and 59.6% of energy compared with the sampling rates of 5 Hz and 50 Hz. The proposed low sampling rate approach can greatly reduce the power consumption while maintaining high activity recognition accuracy. The composition of power consumption in online ARS is also investigated in this paper. PMID:28885560

Neural substrates of interpreting actions and emotions from body postures.

PubMed

Kana, Rajesh K; Travers, Brittany G

2012-04-01

Accurately reading the body language of others may be vital for navigating the social world, and this ability may be influenced by factors, such as our gender, personality characteristics and neurocognitive processes. This fMRI study examined the brain activation of 26 healthy individuals (14 women and 12 men) while they judged the action performed or the emotion felt by stick figure characters appearing in different postures. In both tasks, participants activated areas associated with visual representation of the body, motion processing and emotion recognition. Behaviorally, participants demonstrated greater ease in judging the physical actions of the characters compared to judging their emotional states, and participants showed more activation in areas associated with emotion processing in the emotion detection task, whereas they showed more activation in visual, spatial and action-related areas in the physical action task. Gender differences emerged in brain responses, such that men showed greater activation than women in the left dorsal premotor cortex in both tasks. Finally, participants higher in self-reported empathy demonstrated greater activation in areas associated with self-referential processing and emotion interpretation. These results suggest that empathy levels and sex of the participant may affect neural responses to emotional body language.

Neural substrates of interpreting actions and emotions from body postures

PubMed Central

Travers, Brittany G.

2012-01-01

Accurately reading the body language of others may be vital for navigating the social world, and this ability may be influenced by factors, such as our gender, personality characteristics and neurocognitive processes. This fMRI study examined the brain activation of 26 healthy individuals (14 women and 12 men) while they judged the action performed or the emotion felt by stick figure characters appearing in different postures. In both tasks, participants activated areas associated with visual representation of the body, motion processing and emotion recognition. Behaviorally, participants demonstrated greater ease in judging the physical actions of the characters compared to judging their emotional states, and participants showed more activation in areas associated with emotion processing in the emotion detection task, whereas they showed more activation in visual, spatial and action-related areas in the physical action task. Gender differences emerged in brain responses, such that men showed greater activation than women in the left dorsal premotor cortex in both tasks. Finally, participants higher in self-reported empathy demonstrated greater activation in areas associated with self-referential processing and emotion interpretation. These results suggest that empathy levels and sex of the participant may affect neural responses to emotional body language. PMID:21504992

Intersectoral collaboration for physical activity in Korean Healthy Cities.

PubMed

Kang, Eunjeong

2016-09-01

Intersectoral collaboration (ISC) is important in the health field because the complexity of determinants of health makes it difficult for one institution to resolve all health issues. Promotion of physical activity can especially benefit from a multi-sectoral approach. Despite so much emphasis on its importance in both primary health and health promotion, ISC has been underachieved in the field. This study aimed to examine the characteristics and level of ISC among physical activity programs in Healthy Cities as compared to non-Healthy Cities. I conducted a postal survey where 24 people from Healthy Cities and 72 people from non-Healthy Cities participated. The survey included questions to measure the level of ISC as well as to determine ISC partners and activities. Among the entire 393 physical activity programs, 336 (85.5%) had some kind of collaboration with one or more partners. The percentage having one or more partners was greater in Healthy Cities than in non-Healthy Cities. However, there were no statistical differences between the two groups in terms of the level of ISC within a municipal organization. Collaboration activities of the other departments were mostly supportive, such as providing a venue, recruiting participants and publicizing, and other kinds of administrative support. To strengthen ISC in Korean Healthy Cities, various actions including providing a legal basis, specific and substantive supports, financial incentives, and organizational recognitions will be helpful as well as the development of partnerships with other departments in urban planning, transport, urban design, and communication. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The role of recognition and interest in physics identity development

NASA Astrophysics Data System (ADS)

Lock, Robynne

2016-03-01

While the number of students earning bachelor's degrees in physics has increased in recent years, this number has only recently surpassed the peak value of the 1960s. Additionally, the percentage of women earning bachelor's degrees in physics has stagnated for the past 10 years and may even be declining. We use a physics identity framework consisting of three dimensions to understand how students make their initial career decisions at the end of high school and the beginning of college. The three dimensions consist of recognition (perception that teachers, parents, and peers see the student as a ``physics person''), interest (desire to learn more about physics), and performance/competence (perception of abilities to complete physics related tasks and to understand physics). Using data from the Sustainability and Gender in Engineering survey administered to a nationally representative sample of college students, we built a regression model to determine which identity dimensions have the largest effect on physics career choice and a structural equation model to understand how the identity dimensions are related. Additionally, we used regression models to identify teaching strategies that predict each identity dimension.

Neural Mechanisms of Context Effects on Face Recognition: Automatic Binding and Context Shift Decrements

PubMed Central

Hayes, Scott M.; Baena, Elsa; Truong, Trong-Kha; Cabeza, Roberto

2011-01-01

Although people do not normally try to remember associations between faces and physical contexts, these associations are established automatically, as indicated by the difficulty of recognizing familiar faces in different contexts (“butcher-on-the-bus” phenomenon). The present functional MRI (fMRI) study investigated the automatic binding of faces and scenes. In the Face-Face (F-F) condition, faces were presented alone during both encoding and retrieval, whereas in the Face/Scene-Face (FS-F) condition, they were presented overlaid on scenes during encoding but alone during retrieval (context change). Although participants were instructed to focus only on the faces during both encoding and retrieval, recognition performance was worse in the FS-F than the F-F condition (“context shift decrement”—CSD), confirming automatic face-scene binding during encoding. This binding was mediated by the hippocampus as indicated by greater subsequent memory effects (remembered > forgotten) in this region for the FS-F than the F-F condition. Scene memory was mediated by the right parahippocampal cortex, which was reactivated during successful retrieval when the faces were associated with a scene during encoding (FS-F condition). Analyses using the CSD as a regressor yielded a clear hemispheric asymmetry in medial temporal lobe activity during encoding: left hippocampal and parahippocampal activity was associated with a smaller CSD, indicating more flexible memory representations immune to context changes, whereas right hippocampal/rhinal activity was associated with a larger CSD, indicating less flexible representations sensitive to context change. Taken together, the results clarify the neural mechanisms of context effects on face recognition. PMID:19925208

Neurobiological mechanisms associated with facial affect recognition deficits after traumatic brain injury.

PubMed

Neumann, Dawn; McDonald, Brenna C; West, John; Keiski, Michelle A; Wang, Yang

2016-06-01

The neurobiological mechanisms that underlie facial affect recognition deficits after traumatic brain injury (TBI) have not yet been identified. Using functional magnetic resonance imaging (fMRI), study aims were to 1) determine if there are differences in brain activation during facial affect processing in people with TBI who have facial affect recognition impairments (TBI-I) relative to people with TBI and healthy controls who do not have facial affect recognition impairments (TBI-N and HC, respectively); and 2) identify relationships between neural activity and facial affect recognition performance. A facial affect recognition screening task performed outside the scanner was used to determine group classification; TBI patients who performed greater than one standard deviation below normal performance scores were classified as TBI-I, while TBI patients with normal scores were classified as TBI-N. An fMRI facial recognition paradigm was then performed within the 3T environment. Results from 35 participants are reported (TBI-I = 11, TBI-N = 12, and HC = 12). For the fMRI task, TBI-I and TBI-N groups scored significantly lower than the HC group. Blood oxygenation level-dependent (BOLD) signals for facial affect recognition compared to a baseline condition of viewing a scrambled face, revealed lower neural activation in the right fusiform gyrus (FG) in the TBI-I group than the HC group. Right fusiform gyrus activity correlated with accuracy on the facial affect recognition tasks (both within and outside the scanner). Decreased FG activity suggests facial affect recognition deficits after TBI may be the result of impaired holistic face processing. Future directions and clinical implications are discussed.

Getting the Gist of Events: Recognition of Two-Participant Actions from Brief Displays

PubMed Central

Hafri, Alon; Papafragou, Anna; Trueswell, John C.

2013-01-01

Unlike rapid scene and object recognition from brief displays, little is known about recognition of event categories and event roles from minimal visual information. In three experiments, we displayed naturalistic photographs of a wide range of two-participant event scenes for 37 ms and 73 ms followed by a mask, and found that event categories (the event gist, e.g., ‘kicking’, ‘pushing’, etc.) and event roles (i.e., Agent and Patient) can be recognized rapidly, even with various actor pairs and backgrounds. Norming ratings from a subsequent experiment revealed that certain physical features (e.g., outstretched extremities) that correlate with Agent-hood could have contributed to rapid role recognition. In a final experiment, using identical twin actors, we then varied these features in two sets of stimuli, in which Patients had Agent-like features or not. Subjects recognized the roles of event participants less accurately when Patients possessed Agent-like features, with this difference being eliminated with two-second durations. Thus, given minimal visual input, typical Agent-like physical features are used in role recognition but, with sufficient input from multiple fixations, people categorically determine the relationship between event participants. PMID:22984951

An Investigation of the Role of Grapheme Units in Word Recognition

ERIC Educational Resources Information Center

Lupker, Stephen J.; Acha, Joana; Davis, Colin J.; Perea, Manuel

2012-01-01

In most current models of word recognition, the word recognition process is assumed to be driven by the activation of letter units (i.e., that letters are the perceptual units in reading). An alternative possibility is that the word recognition process is driven by the activation of grapheme units, that is, that graphemes, rather than letters, are…

The Role of Active Exploration of 3D Face Stimuli on Recognition Memory of Facial Information

ERIC Educational Resources Information Center

Liu, Chang Hong; Ward, James; Markall, Helena

2007-01-01

Research on face recognition has mainly relied on methods in which observers are relatively passive viewers of face stimuli. This study investigated whether active exploration of three-dimensional (3D) face stimuli could facilitate recognition memory. A standard recognition task and a sequential matching task were employed in a yoked design.…

The impact and process of a community-led intervention on reducing environmental inequalities related to physical activity and healthy eating - a pilot study.

PubMed

Davey, Rachel C; Hurst, Gemma L; Smith, Graham R; Grogan, Sarah C; Kurth, Judy

2011-09-12

There is growing recognition that a sedentary lifestyle is being driven, at least in part, by environmental factors that affect individuals' physical activity choices and health behaviours. In other words, the environments in which we live, and with which we interact, have become ones that encourage lifestyle choices that decrease physical activity and encourage over-consumption of foods. However, evidence from community-led interventions to change local neighbourhood environments to support physical activity and healthy eating is lacking. This article summarises the research protocol developed to evaluate a community-led intervention "My Health Matters" aimed at reducing health inequalities relating to increasing physical activity and healthy eating as defined by community members themselves. This study includes three of the most deprived electoral wards in Stoke-on-Trent. In each of these areas, environmental factors including proximity of physical activity spaces, greenspace and leisure facilities, neighbourhood connectivity and walkability, land-use-mix and population density, traffic, safety and crime, and food outlets will be mapped using Geographical Information Systems (GIS). A community postal survey of randomly selected addresses assessing environmental characteristics relating to physical activity, perceived health status, social capital, fruit and vegetable consumption and levels of physical activity will be undertaken (baseline and at 2 year follow-up). Based on baseline findings an intervention will be designed and implemented over a 2 year period that includes the following; use of community participatory research to build effective community partnerships; use of partnership consensus to identify, prioritise and design intervention(s) related to specific health disparities; recruitment of local residents to help with the delivery and sustainability of target intervention(s); and the development of local systems for ongoing monitoring and evaluation of the intervention(s). A community-led and multidisciplinary approach to modifying environmental factors that support and reinforce healthful behaviours may be more successful than focusing on individual behaviour change as this approach does not exclusively rely upon individual will and capacity.Study findings will be collated in 2012 and, if successful in improving levels of physical activity and healthy eating, will help to inform the design of a larger area-based, cluster randomized controlled trial to determine effectiveness.

Rationale, design and methods for a staggered-entry, waitlist controlled clinical trial of the impact of a community-based, family-centred, multidisciplinary program focussed on activity, food and attitude habits (Curtin University's Activity, Food and Attitudes Program--CAFAP) among overweight adolescents.

PubMed

Straker, Leon M; Smith, Kyla L; Fenner, Ashley A; Kerr, Deborah A; McManus, Alexandra; Davis, Melissa C; Fielding, Angela M; Olds, Tim S; Hagger, Martin S; Smith, Anne J; Abbott, Rebecca A

2012-06-21

Current estimates place just under one quarter of adolescents in Australia as overweight or obese. Adolescence has been identified as a critical period for the development of obesity, yet despite this recognition, there is limited systematic research into or evaluation of interventions for overweight adolescents. Reviews have concluded that there is a substantive evidence gap for effective intervention, but physical activity, lifestyle change and family involvement have been identified as promising foci for treatment. This paper reports on the development of a staggered-entry, waitlist controlled clinical trial to assess the impact of a multidisciplinary intervention aiming to change the poor health trajectory of overweight adolescents and help them avoid morbid obesity in adulthood-Curtin University's Activity, Food and Attitudes Program (CAFAP). 96 adolescents, aged 11-16 years, and parents, will attend twice weekly during an 8 week intensive multidisciplinary program with maintenance follow-up focussed on improving activity, food and attitude habits. Follow-up assessments will be conducted immediately after completing the intensive program, and at 3, 6 and 12 months post intensive program. Main outcomes will be objectively-measured physical activity, sedentary behaviour and activity behaviours; food intake (measured by 3 day diary) and food behaviours; body composition, fitness and physical function; mental and social well-being (quality of life, mood and attitudes), and family functioning. This trial will provide important information to understand whether a community based multidisciplinary intervention can have short and medium term effects on activity and food habits, attitudes, and physical and mental health status of overweight adolescents. Australian New Zealand Clinical Trials Registry ACTRN12611001187932.

Understanding selective molecular recognition in integrated carbon nanotube-polymer sensors by simulating physical analyte binding on carbon nanotube-polymer scaffolds.

PubMed

Lin, Shangchao; Zhang, Jingqing; Strano, Michael S; Blankschtein, Daniel

2014-08-28

Macromolecular scaffolds made of polymer-wrapped single-walled carbon nanotubes (SWCNTs) have been explored recently (Zhang et al., Nature Nanotechnology, 2013) as a new class of molecular-recognition motifs. However, selective analyte recognition is still challenging and lacks the underlying fundamental understanding needed for its practical implementation in biological sensors. In this report, we combine coarse-grained molecular dynamics (CGMD) simulations, physical adsorption/binding theories, and photoluminescence (PL) experiments to provide molecular insight into the selectivity of such sensors towards a large set of biologically important analytes. We find that the physical binding affinities of the analytes on a bare SWCNT partially correlate with their distribution coefficients in a bulk water/octanol system, suggesting that the analyte hydrophobicity plays a key role in determining the binding affinities of the analytes considered, along with the various specific interactions between the analytes and the polymer anchor groups. Two distinct categories of analytes are identified to demonstrate a complex picture for the correlation between optical sensor signals and the simulated binding affinities. Specifically, a good correlation was found between the sensor signals and the physical binding affinities of the three hormones (estradiol, melatonin, and thyroxine), the neurotransmitter (dopamine), and the vitamin (riboflavin) to the SWCNT-polymer scaffold. The four amino acids (aspartate, glycine, histidine, and tryptophan) and the two monosaccharides (fructose and glucose) considered were identified as blank analytes which are unable to induce sensor signals. The results indicate great success of our physical adsorption-based model in explaining the ranking in sensor selectivities. The combined framework presented here can be used to screen and select polymers that can potentially be used for creating synthetic molecular recognition motifs.

Recognizing emotion in faces: developmental effects of child abuse and neglect.

PubMed

Pollak, Seth D; Cicchetti, Dante; Hornung, Katherine; Reed, Alex

2000-09-01

The contributions to the recognition of emotional signals of (a) experience and learning versus (b) internal predispositions are difficult to investigate because children are virtually always exposed to complex emotional experiences from birth. The recognition of emotion among physically abused and physically neglected preschoolers was assessed in order to examine the effects of atypical experience on emotional development. In Experiment 1, children matched a facial expression to an emotional situation. Neglected children had more difficulty discriminating emotional expressions than did control or physically abused children. Physically abused children displayed a response bias for angry facial expressions. In Experiment 2, children rated the similarity of facial expressions. Control children viewed discrete emotions as dissimilar, neglected children saw fewer distinctions between emotions, and physically abused children showed the most variance across emotions. These results suggest that to the extent that children's experience with the world varies, so too will their interpretation and understanding of emotional signals.

One-single physical exercise session after object recognition learning promotes memory persistence through hippocampal noradrenergic mechanisms.

PubMed

da Silva de Vargas, Liane; Neves, Ben-Hur Souto das; Roehrs, Rafael; Izquierdo, Iván; Mello-Carpes, Pâmela

2017-06-30

Previously we showed the involvement of the hippocampal noradrenergic system in the consolidation and persistence of object recognition (OR) memory. Here we show that one-single physical exercise session performed immediately after learning promotes OR memory persistence and increases norepinephrine levels in the hippocampus. Additionally, effects of exercise on memory are avoided by an intra-hippocampal beta-adrenergic antagonist infusion. Taken together, these results suggest that exercise effects on memory can be related to noradrenergic mechanisms and acute physical exercise can be a non-pharmacological intervention to assist memory consolidation and persistence, with few or no side effects. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential Effects of Acute and Regular Physical Exercise on Cognition and Affect

PubMed Central

Hopkins, Michael E.; Davis, F. Caroline; VanTieghem, Michelle R.; Whalen, Paul J.; Bucci, David J.

2012-01-01

The effects of regular exercise versus a single bout of exercise on cognition, anxiety, and mood were systematically examined in healthy, sedentary young adults who were genotyped to determine brain-derived neurotrophic factor (BDNF) allelic status (i.e., Val-Val or Val66Met polymorphism). Participants were evaluated on novel object recognition (NOR) memory and a battery of mental health surveys before and after engaging in either a) a four-week exercise program, with exercise on the final test day, b) a four-week exercise program, without exercise on the final test day, c) a single bout of exercise on the final test day, or d) remaining sedentary between test days. Exercise enhanced object recognition memory and produced a beneficial decrease in perceived stress, but only in participants who exercised for four weeks including the final day of testing. In contrast, a single bout of exercise did not affect recognition memory and resulted in increased perceived stress levels. An additional novel finding was that the improvements on the NOR task were observed exclusively in participants who were homozygous for the BDNF Val allele, indicating that altered activity-dependent release of BDNF in Met allele carriers may attenuate the cognitive benefits of exercise. Importantly, exercise-induced changes in cognition were not correlated with changes in mood/anxiety, suggesting that separate neural systems mediate these effects. These data in humans mirror recent data from our group in rodents. Taken together, these current findings provide new insights into the behavioral and neural mechanisms that mediate the effects of physical exercise on memory and mental health in humans. PMID:22554780

Using the automata processor for fast pattern recognition in high energy physics experiments. A proof of concept

DOE PAGES

Michael H. L. S. Wang; Cancelo, Gustavo; Green, Christopher; ...

2016-06-25

Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.

Using the automata processor for fast pattern recognition in high energy physics experiments. A proof of concept

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

Michael H. L. S. Wang; Cancelo, Gustavo; Green, Christopher

Here, we explore the Micron Automata Processor (AP) as a suitable commodity technology that can address the growing computational needs of pattern recognition in High Energy Physics (HEP) experiments. A toy detector model is developed for which an electron track confirmation trigger based on the Micron AP serves as a test case. Although primarily meant for high speed text-based searches, we demonstrate a proof of concept for the use of the Micron AP in a HEP trigger application.

A reciprocal model of face recognition and autistic traits: evidence from an individual differences perspective.

PubMed

Halliday, Drew W R; MacDonald, Stuart W S; Scherf, K Suzanne; Sherf, Suzanne K; Tanaka, James W

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals.

A Reciprocal Model of Face Recognition and Autistic Traits: Evidence from an Individual Differences Perspective

PubMed Central

Halliday, Drew W. R.; MacDonald, Stuart W. S.; Sherf, Suzanne K.; Tanaka, James W.

2014-01-01

Although not a core symptom of the disorder, individuals with autism often exhibit selective impairments in their face processing abilities. Importantly, the reciprocal connection between autistic traits and face perception has rarely been examined within the typically developing population. In this study, university participants from the social sciences, physical sciences, and humanities completed a battery of measures that assessed face, object and emotion recognition abilities, general perceptual-cognitive style, and sub-clinical autistic traits (the Autism Quotient (AQ)). We employed separate hierarchical multiple regression analyses to evaluate which factors could predict face recognition scores and AQ scores. Gender, object recognition performance, and AQ scores predicted face recognition behaviour. Specifically, males, individuals with more autistic traits, and those with lower object recognition scores performed more poorly on the face recognition test. Conversely, university major, gender and face recognition performance reliably predicted AQ scores. Science majors, males, and individuals with poor face recognition skills showed more autistic-like traits. These results suggest that the broader autism phenotype is associated with lower face recognition abilities, even among typically developing individuals. PMID:24853862

A Robust and Device-Free System for the Recognition and Classification of Elderly Activities.

PubMed

Li, Fangmin; Al-Qaness, Mohammed Abdulaziz Aide; Zhang, Yong; Zhao, Bihai; Luan, Xidao

2016-12-01

Human activity recognition, tracking and classification is an essential trend in assisted living systems that can help support elderly people with their daily activities. Traditional activity recognition approaches depend on vision-based or sensor-based techniques. Nowadays, a novel promising technique has obtained more attention, namely device-free human activity recognition that neither requires the target object to wear or carry a device nor install cameras in a perceived area. The device-free technique for activity recognition uses only the signals of common wireless local area network (WLAN) devices available everywhere. In this paper, we present a novel elderly activities recognition system by leveraging the fluctuation of the wireless signals caused by human motion. We present an efficient method to select the correct data from the Channel State Information (CSI) streams that were neglected in previous approaches. We apply a Principle Component Analysis method that exposes the useful information from raw CSI. Thereafter, Forest Decision (FD) is adopted to classify the proposed activities and has gained a high accuracy rate. Extensive experiments have been conducted in an indoor environment to test the feasibility of the proposed system with a total of five volunteer users. The evaluation shows that the proposed system is applicable and robust to electromagnetic noise.

INTRODUCTION TO THE MOVEMENT SYSTEM AS THE FOUNDATION FOR PHYSICAL THERAPIST PRACTICE EDUCATION AND RESEARCH.

PubMed

Saladin, Lisa; Voight, Michael

2017-11-01

In 2013, the American Physical Therapy Association (APTA) adopted an inspiring new vision, "Transforming society by optimizing movement to improve the human experience." This new vision for our profession calls us to action as physical therapists to transform society by using our skills, knowledge, and expertise related to the movement system in order to optimize movement, promote health and wellness, mitigate the progression of impairments, and prevent the development of (additional) disability. The guiding principle of the new vision is "identity," which can be summarized as "The physical therapy profession will define and promote the movement system as the foundation for optimizing movement to improve the health of society." Recognition and validation of the movement system is essential to understand the structure, function, and potential of the human body. As currently defined, the "movement system" represents the collection of systems (cardiovascular, pulmonary, endocrine, integumentary, nervous, and musculoskeletal) that interact to move the body or its component parts. By better characterizing physical therapists as movement system experts, we seek to solidify our professional identity within the medical community and society. The physical therapist will be responsible for evaluating and managing an individual's movement system across the lifespan to promote optimal development; diagnose impairments, activity limitations, and participation restrictions; and provide interventions targeted at preventing or ameliorating activity limitations and participation restrictions. 5.

Exploring Techniques for Vision Based Human Activity Recognition: Methods, Systems, and Evaluation

PubMed Central

Xu, Xin; Tang, Jinshan; Zhang, Xiaolong; Liu, Xiaoming; Zhang, Hong; Qiu, Yimin

2013-01-01

With the wide applications of vision based intelligent systems, image and video analysis technologies have attracted the attention of researchers in the computer vision field. In image and video analysis, human activity recognition is an important research direction. By interpreting and understanding human activities, we can recognize and predict the occurrence of crimes and help the police or other agencies react immediately. In the past, a large number of papers have been published on human activity recognition in video and image sequences. In this paper, we provide a comprehensive survey of the recent development of the techniques, including methods, systems, and quantitative evaluation of the performance of human activity recognition. PMID:23353144

Dynamic detection of window starting positions and its implementation within an activity recognition framework.

PubMed

Ni, Qin; Patterson, Timothy; Cleland, Ian; Nugent, Chris

2016-08-01

Activity recognition is an intrinsic component of many pervasive computing and ambient intelligent solutions. This has been facilitated by an explosion of technological developments in the area of wireless sensor network, wearable and mobile computing. Yet, delivering robust activity recognition, which could be deployed at scale in a real world environment, still remains an active research challenge. Much of the existing literature to date has focused on applying machine learning techniques to pre-segmented data collected in controlled laboratory environments. Whilst this approach can provide valuable ground truth information from which to build recognition models, these techniques often do not function well when implemented in near real time applications. This paper presents the application of a multivariate online change detection algorithm to dynamically detect the starting position of windows for the purposes of activity recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

Influences of Lexical Processing on Reading.

ERIC Educational Resources Information Center

Yang, Yu-Fen; Kuo, Hsing-Hsiu

2003-01-01

Investigates how early lexical processing (word recognition) could influence reading. Finds that less-proficient readers could not finish the task of word recognition within time limits and their accuracy rates were quite low, whereas the proficient readers processed the physical words immediately and translated them into meanings quickly in order…

Microcomputers: Independence and Information Access for the Physically Handicapped.

ERIC Educational Resources Information Center

Regen, Shari S.; Chen, Ching-chih

1984-01-01

Provides overview of recent technological developments in microcomputer technology for the physically disabled, including discussion of view expansion, "talking terminals," voice recognition, and price and convenience of micro-based products. Equipment manufacturers and training centers for the physically disabled are listed and microcomputer…

Bilingual Word Recognition in Deaf and Hearing Signers: Effects of Proficiency and Language Dominance on Cross-Language Activation

ERIC Educational Resources Information Center

Morford, Jill P.; Kroll, Judith F.; Piñar, Pilar; Wilkinson, Erin

2014-01-01

Recent evidence demonstrates that American Sign Language (ASL) signs are active during print word recognition in deaf bilinguals who are highly proficient in both ASL and English. In the present study, we investigate whether signs are active during print word recognition in two groups of unbalanced bilinguals: deaf ASL-dominant and hearing…

A system for activity recognition using multi-sensor fusion.

PubMed

Gao, Lei; Bourke, Alan K; Nelson, John

2011-01-01

This paper proposes a system for activity recognition using multi-sensor fusion. In this system, four sensors are attached to the waist, chest, thigh, and side of the body. In the study we present two solutions for factors that affect the activity recognition accuracy: the calibration drift and the sensor orientation changing. The datasets used to evaluate this system were collected from 8 subjects who were asked to perform 8 scripted normal activities of daily living (ADL), three times each. The Naïve Bayes classifier using multi-sensor fusion is adopted and achieves 70.88%-97.66% recognition accuracies for 1-4 sensors.

Encoding-related brain activity dissociates between the recollective processes underlying successful recall and recognition: a subsequent-memory study.

PubMed

Sadeh, Talya; Maril, Anat; Goshen-Gottstein, Yonatan

2012-07-01

The subsequent-memory (SM) paradigm uncovers brain mechanisms that are associated with mnemonic activity during encoding by measuring participants' neural activity during encoding and classifying the encoding trials according to performance in the subsequent retrieval phase. The majority of these studies have converged on the notion that the mechanism supporting recognition is mediated by familiarity and recollection. The process of recollection is often assumed to be a recall-like process, implying that the active search for the memory trace is similar, if not identical, for recall and recognition. Here we challenge this assumption and hypothesize - based on previous findings obtained in our lab - that the recollective processes underlying recall and recognition might show dissociative patterns of encoding-related brain activity. To this end, our design controlled for familiarity, thereby focusing on contextual, recollective processes. We found evidence for dissociative neurocognitive encoding mechanisms supporting subsequent-recall and subsequent-recognition. Specifically, the contrast of subsequent-recognition versus subsequent-recall revealed activation in the Parahippocampal cortex (PHc) and the posterior hippocampus--regions associated with contextual processing. Implications of our findings and their relation to current cognitive models of recollection are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons.

PubMed

Filippoupolitis, Avgoustinos; Oliff, William; Takand, Babak; Loukas, George

2017-05-27

Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE) beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation.

Human activities recognition by head movement using partial recurrent neural network

NASA Astrophysics Data System (ADS)

Tan, Henry C. C.; Jia, Kui; De Silva, Liyanage C.

2003-06-01

Traditionally, human activities recognition has been achieved mainly by the statistical pattern recognition methods or the Hidden Markov Model (HMM). In this paper, we propose a novel use of the connectionist approach for the recognition of ten simple human activities: walking, sitting down, getting up, squatting down and standing up, in both lateral and frontal views, in an office environment. By means of tracking the head movement of the subjects over consecutive frames from a database of different color image sequences, and incorporating the Elman model of the partial recurrent neural network (RNN) that learns the sequential patterns of relative change of the head location in the images, the proposed system is able to robustly classify all the ten activities performed by unseen subjects from both sexes, of different race and physique, with a recognition rate as high as 92.5%. This demonstrates the potential of employing partial RNN to recognize complex activities in the increasingly popular human-activities-based applications.

Role of fusiform and anterior temporal cortical areas in facial recognition.

PubMed

Nasr, Shahin; Tootell, Roger B H

2012-11-15

Recent fMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus ('AT'; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. Copyright © 2012 Elsevier Inc. All rights reserved.

Role of Fusiform and Anterior Temporal Cortical Areas in Facial Recognition

PubMed Central

Nasr, Shahin; Tootell, Roger BH

2012-01-01

Recent FMRI studies suggest that cortical face processing extends well beyond the fusiform face area (FFA), including unspecified portions of the anterior temporal lobe. However, the exact location of such anterior temporal region(s), and their role during active face recognition, remain unclear. Here we demonstrate that (in addition to FFA) a small bilateral site in the anterior tip of the collateral sulcus (‘AT’; the anterior temporal face patch) is selectively activated during recognition of faces but not houses (a non-face object). In contrast to the psychophysical prediction that inverted and contrast reversed faces are processed like other non-face objects, both FFA and AT (but not other visual areas) were also activated during recognition of inverted and contrast reversed faces. However, response accuracy was better correlated to recognition-driven activity in AT, compared to FFA. These data support a segregated, hierarchical model of face recognition processing, extending to the anterior temporal cortex. PMID:23034518

Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM)

NASA Astrophysics Data System (ADS)

Iqtait, M.; Mohamad, F. S.; Mamat, M.

2018-03-01

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

Older People’s Perspectives on Health, Physical Activity and Nutritional Behaviors

PubMed Central

Alizadeh, Leila; Salehi, Leili

2015-01-01

Background: Approaches for investigating health-promoting lifestyle generally focus on physical activity and regular diet. To explore the perspectives of Iranian elders regarding health, healthy eating and physical activity (PA) this study was conducted in 2012. Methods: Participants in this qualitative study were selected through purposeful sampling. Ten focus groups were conducted with 60 older adults in 3 elderly centers in Tehran. A moderator’s guideline that consisted of general and specific questions was used. Focus groups were audio recorded, transcribed verbatim and analysis was performed using conventional content analysis. Results: Participants explained their perspectives regarding health, healthy eating and PA in the following 5 categories: meaning of health was represented based on issues such as absence of pain and disorder, complete body wellbeing, staying away from hazards, complete individual satisfaction, experiencing positive events, effective communication, faithfulness and trust in God. The healthy eating category was featured by adequate eating, age balanced diet, refraining from under or over nutrition and sensible consumption of fruits and vegetables. The PA was described - according to the level of performing outdoor activities or household tasks. Expressions about the perceived benefits and barriers of healthy eating and PA were aligned the two remaining categories. Conclusions: Participants have referred to the association between both PA and dietary practices and health. Understanding how older people define physical activity and nutritional behavior and recognition of the most important perceived benefits and barriers that might contribute to have a healthy eating or adequate PA profile could procure insight into the type of interventions that are required to promote healthy lifestyle among Iranian older adults. PMID:26933648

An fMRI comparison of neural activity associated with recognition of familiar melodies in younger and older adults

PubMed Central

Sikka, Ritu; Cuddy, Lola L.; Johnsrude, Ingrid S.; Vanstone, Ashley D.

2015-01-01

Several studies of semantic memory in non-musical domains involving recognition of items from long-term memory have shown an age-related shift from the medial temporal lobe structures to the frontal lobe. However, the effects of aging on musical semantic memory remain unexamined. We compared activation associated with recognition of familiar melodies in younger and older adults. Recognition follows successful retrieval from the musical lexicon that comprises a lifetime of learned musical phrases. We used the sparse-sampling technique in fMRI to determine the neural correlates of melody recognition by comparing activation when listening to familiar vs. unfamiliar melodies, and to identify age differences. Recognition-related cortical activation was detected in the right superior temporal, bilateral inferior and superior frontal, left middle orbitofrontal, bilateral precentral, and left supramarginal gyri. Region-of-interest analysis showed greater activation for younger adults in the left superior temporal gyrus and for older adults in the left superior frontal, left angular, and bilateral superior parietal regions. Our study provides powerful evidence for these musical memory networks due to a large sample (N = 40) that includes older adults. This study is the first to investigate the neural basis of melody recognition in older adults and to compare the findings to younger adults. PMID:26500480

Factors that influence the performance of experienced speech recognition users.

PubMed

Koester, Heidi Horstmann

2006-01-01

Performance on automatic speech recognition (ASR) systems for users with physical disabilities varies widely between individuals. The goal of this study was to discover some key factors that account for that variation. Using data from 23 experienced ASR users with physical disabilities, the effect of 20 different independent variables on recognition accuracy and text entry rate with ASR was measured using bivariate and multivariate analyses. The results show that use of appropriate correction strategies had the strongest influence on user performance with ASR. The amount of time the user spent on his or her computer, the user's manual typing speed, and the speed with which the ASR system recognized speech were all positively associated with better performance. The amount or perceived adequacy of ASR training did not have a significant impact on performance for this user group.

Incorporating Duration Information in Activity Recognition

NASA Astrophysics Data System (ADS)

Chaurasia, Priyanka; Scotney, Bryan; McClean, Sally; Zhang, Shuai; Nugent, Chris

Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.

A Development of a System Enables Character Input and PC Operation via Voice for a Physically Disabled Person with a Speech Impediment

NASA Astrophysics Data System (ADS)

Tanioka, Toshimasa; Egashira, Hiroyuki; Takata, Mayumi; Okazaki, Yasuhisa; Watanabe, Kenzi; Kondo, Hiroki

We have designed and implemented a PC operation support system for a physically disabled person with a speech impediment via voice. Voice operation is an effective method for a physically disabled person with involuntary movement of the limbs and the head. We have applied a commercial speech recognition engine to develop our system for practical purposes. Adoption of a commercial engine reduces development cost and will contribute to make our system useful to another speech impediment people. We have customized commercial speech recognition engine so that it can recognize the utterance of a person with a speech impediment. We have restricted the words that the recognition engine recognizes and separated a target words from similar words in pronunciation to avoid misrecognition. Huge number of words registered in commercial speech recognition engines cause frequent misrecognition for speech impediments' utterance, because their utterance is not clear and unstable. We have solved this problem by narrowing the choice of input down in a small number and also by registering their ambiguous pronunciations in addition to the original ones. To realize all character inputs and all PC operation with a small number of words, we have designed multiple input modes with categorized dictionaries and have introduced two-step input in each mode except numeral input to enable correct operation with small number of words. The system we have developed is in practical level. The first author of this paper is physically disabled with a speech impediment. He has been able not only character input into PC but also to operate Windows system smoothly by using this system. He uses this system in his daily life. This paper is written by him with this system. At present, the speech recognition is customized to him. It is, however, possible to customize for other users by changing words and registering new pronunciation according to each user's utterance.

Medical physics is alive and well and growing in South East Asia.

PubMed

Ng, K; Pirabul, R; Peralta, A; Soejoko, D

1997-03-01

In recent years there has been a significant economic growth in South East Asia, along with it a concurrent development of medical physics. The status of four countries--Malaysia, Thailand, the Philippines and Indonesia are presented. Medical physicists in these countries have been experiencing the usual problems of lack of recognition, low salaries, and insufficient facilities for education and training opportunities. However the situation has improved recently through the initiative of local enthusiastic medical physicists who have started MS graduate programs in medical physics and begun organizing professional activities to raise the profile of medical physics. The tremendous support and catalytic roles of the American Association of Physicists in Medicine (AAPM) and international organizations such as International Organization for Medical Physics (IOMP), International Atomic Energy Agency (IAEA), World Health Organization (WHO), and International Center for Theoretical Physics (ICTP) have been instrumental in achieving progress. Contributions by these organizations include co-sponsorship of workshops and conferences, travel grants, medical physics libraries programs, and providing experts and educators. The demand for medical physicists is expected to rise in tandem with the increased emphasis on innovative technology for health care, stringent governmental regulation, and acceptance by the medical community of the important role of medical physicists.

A Novel Wearable Device for Food Intake and Physical Activity Recognition

PubMed Central

Farooq, Muhammad; Sazonov, Edward

2016-01-01

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure. PMID:27409622

The prevalence of physical activity and its associated effects among students in the São Paulo public school network, Brazil.

PubMed

Silva, Leonardo José; Matsudo, Victor Keihan Rodrigues; Andrade, Douglas Roque; Azevedo, Mário; Ferrari, Gerson Luis de Moraes; Oliveira, Luis Carlos; Araújo, Timóteo Leandro; Matsudo, Sandra Marcela Mahecha

2016-04-01

The current study evaluated physical activity (PA) level and its associated effects among students in the public network of São Paulo, Brazil. A cross-sectional study was taken using a representative sample of students in São Paulo public school system. International Physical Activity Questionnaire determined PA level. Students who reported at least 300 minutes/week of PA were considered active. The independente variables were: gender, age, body mass index, education, region, recognition of the Agita São Paulo program. The prevalence of regular PA was 71.7%. Males (PR = 1.09, 95% CIs = 1.04 -1.15) at least 17 years old (PR = 1.16, 95% CIs 1.09-1.24) in their 3rd year of high school (PR = 1.20, 95% CIs = 1.12-1.29) who resided in the Midwest region (PR = 1.27, 95% CIs 1.16-1.38) were most likely to be active. Males at least 17 years old in their 3rd year of high school who lived in the Midwest and recognized the Agita São Paulo/Agita Galera program had higher levels of PA. São Paulo students presented a high level of PA. Moreover, males older than 17 years, attending their 3rd year of high school, who lived in the Midwest region, and recognized the Agita São Paulo/Agita Galera program were the most likely to be more active.

A Novel Wearable Device for Food Intake and Physical Activity Recognition.

PubMed

Farooq, Muhammad; Sazonov, Edward

2016-07-11

Presence of speech and motion artifacts has been shown to impact the performance of wearable sensor systems used for automatic detection of food intake. This work presents a novel wearable device which can detect food intake even when the user is physically active and/or talking. The device consists of a piezoelectric strain sensor placed on the temporalis muscle, an accelerometer, and a data acquisition module connected to the temple of eyeglasses. Data from 10 participants was collected while they performed activities including quiet sitting, talking, eating while sitting, eating while walking, and walking. Piezoelectric strain sensor and accelerometer signals were divided into non-overlapping epochs of 3 s; four features were computed for each signal. To differentiate between eating and not eating, as well as between sedentary postures and physical activity, two multiclass classification approaches are presented. The first approach used a single classifier with sensor fusion and the second approach used two-stage classification. The best results were achieved when two separate linear support vector machine (SVM) classifiers were trained for food intake and activity detection, and their results were combined using a decision tree (two-stage classification) to determine the final class. This approach resulted in an average F1-score of 99.85% and area under the curve (AUC) of 0.99 for multiclass classification. With its ability to differentiate between food intake and activity level, this device may potentially be used for tracking both energy intake and energy expenditure.

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

Ubiquitous computing technology for just-in-time motivation of behavior change.

PubMed

Intille, Stephen S

2004-01-01

This paper describes a vision of health care where "just-in-time" user interfaces are used to transform people from passive to active consumers of health care. Systems that use computational pattern recognition to detect points of decision, behavior, or consequences automatically can present motivational messages to encourage healthy behavior at just the right time. Further, new ubiquitous computing and mobile computing devices permit information to be conveyed to users at just the right place. In combination, computer systems that present messages at the right time and place can be developed to motivate physical activity and healthy eating. Computational sensing technologies can also be used to measure the impact of the motivational technology on behavior.

The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

NASA Technical Reports Server (NTRS)

Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

2004-01-01

In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

Object, spatial and social recognition testing in a single test paradigm.

PubMed

Lian, Bin; Gao, Jun; Sui, Nan; Feng, Tingyong; Li, Ming

2018-07-01

Animals have the ability to process information about an object or a conspecific's physical features and location, and alter its behavior when such information is updated. In the laboratory, the object, spatial and social recognition are often studied in separate tasks, making them unsuitable to study the potential dissociations and interactions among various types of recognition memories. The present study introduced a single paradigm to detect the object and spatial recognition, and social recognition of a familiar and novel conspecific. Specifically, male and female Sprague-Dawley adult (>75 days old) or preadolescent (25-28 days old) rats were tested with two objects and one social partner in an open-field arena for four 10-min sessions with a 20-min inter-session interval. After the first sample session, a new object replaced one of the sampled objects in the second session, and the location of one of the old objects was changed in the third session. Finally, a new social partner was introduced in the fourth session and replaced the familiar one. Exploration time with each stimulus was recorded and measures for the three recognitions were calculated based on the discrimination ratio. Overall results show that adult and preadolescent male and female rats spent more time exploring the social partner than the objects, showing a clear preference for social stimulus over nonsocial one. They also did not differ in their abilities to discriminate a new object, a new location and a new social partner from a familiar one, and to recognize a familiar conspecific. Acute administration of MK-801 (a NMDA receptor antagonist, 0.025 and 0.10 mg/kg, i.p.) after the sample session dose-dependently reduced the total time spent on exploring the social partner and objects in the adult rats, and had a significantly larger effect in the females than in the males. MK-801 also dose-dependently increased motor activity. However, it did not alter the object, spatial and social recognitions. These findings indicate that the new triple recognition paradigm is capable of recording the object, spatial location and social recognition together and revealing potential sex and age differences. This paradigm is also useful for the study of object and social exploration concurrently and can be used to evaluate cognition-altering drugs in various stages of recognition memories. Copyright © 2018. Published by Elsevier Inc.

Validity of physical activity monitors for assessing lower intensity activity in adults.

PubMed

Calabró, M Andrés; Lee, Jung-Min; Saint-Maurice, Pedro F; Yoo, Hyelim; Welk, Gregory J

2014-09-28

Accelerometers can provide accurate estimates of moderate-to-vigorous physical activity (MVPA). However, one of the limitations of these instruments is the inability to capture light activity within an acceptable range of error. The purpose of the present study was to determine the validity of different activity monitors for estimating energy expenditure (EE) of light intensity, semi-structured activities. Forty healthy participants wore a SenseWear Pro3 Armband (SWA, v.6.1), the SenseWear Mini, the Actiheart, ActiGraph, and ActivPAL monitors, while being monitored with a portable indirect calorimetry (IC). Participants engaged in a variety of low intensity activities but no formalized scripts or protocols were used during these periods. The Mini and SWA overestimated total EE on average by 1.0% and 4.0%, respectively, while the AH, the GT3X, and the AP underestimated total EE on average by 7.8%, 25.5%, and 22.2%, respectively. The pattern-recognition monitors yielded non-significant differences in EE estimates during the semi-structured period (p = 0.66, p = 0.27, and p = 0.21 for the Mini, SWA, and AH, respectively). The SenseWear Mini provided more accurate estimates of EE during light to moderate intensity semi-structured activities compared to other activity monitors. This monitor should be considered when there is interest in tracking low intensity activities in groups of individuals.

Movement and Meaning-Making in Physical Education

ERIC Educational Resources Information Center

Brown, Trent D.

2008-01-01

In this paper I argue that the meaning of movement of which embodied knowing, somatic understanding and ecological subjectivity are central tenets, has not received due recognition in the current discourses of physical education. While the interest in the meaning and meaning-making of movement within the physical education discourse has existed…

A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time

PubMed Central

Wang, Zhihua; Yang, Zhaochu; Dong, Tao

2017-01-01

Rapid growth of the aged population has caused an immense increase in the demand for healthcare services. Generally, the elderly are more prone to health problems compared to other age groups. With effective monitoring and alarm systems, the adverse effects of unpredictable events such as sudden illnesses, falls, and so on can be ameliorated to some extent. Recently, advances in wearable and sensor technologies have improved the prospects of these service systems for assisting elderly people. In this article, we review state-of-the-art wearable technologies that can be used for elderly care. These technologies are categorized into three types: indoor positioning, activity recognition and real time vital sign monitoring. Positioning is the process of accurate localization and is particularly important for elderly people so that they can be found in a timely manner. Activity recognition not only helps ensure that sudden events (e.g., falls) will raise alarms but also functions as a feasible way to guide people’s activities so that they avoid dangerous behaviors. Since most elderly people suffer from age-related problems, some vital signs that can be monitored comfortably and continuously via existing techniques are also summarized. Finally, we discussed a series of considerations and future trends with regard to the construction of “smart clothing” system. PMID:28208620

A Review of Wearable Technologies for Elderly Care that Can Accurately Track Indoor Position, Recognize Physical Activities and Monitor Vital Signs in Real Time.

PubMed

Wang, Zhihua; Yang, Zhaochu; Dong, Tao

2017-02-10

Rapid growth of the aged population has caused an immense increase in the demand for healthcare services. Generally, the elderly are more prone to health problems compared to other age groups. With effective monitoring and alarm systems, the adverse effects of unpredictable events such as sudden illnesses, falls, and so on can be ameliorated to some extent. Recently, advances in wearable and sensor technologies have improved the prospects of these service systems for assisting elderly people. In this article, we review state-of-the-art wearable technologies that can be used for elderly care. These technologies are categorized into three types: indoor positioning, activity recognition and real time vital sign monitoring. Positioning is the process of accurate localization and is particularly important for elderly people so that they can be found in a timely manner. Activity recognition not only helps ensure that sudden events (e.g., falls) will raise alarms but also functions as a feasible way to guide people's activities so that they avoid dangerous behaviors. Since most elderly people suffer from age-related problems, some vital signs that can be monitored comfortably and continuously via existing techniques are also summarized. Finally, we discussed a series of considerations and future trends with regard to the construction of "smart clothing" system.

Scene recognition based on integrating active learning with dictionary learning

NASA Astrophysics Data System (ADS)

Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Activating the critical lure during study is unnecessary for false recognition.

PubMed

Zeelenberg, René; Boot, Inge; Pecher, Diane

2005-06-01

Participants studied lists of nonwords (e.g., froost, floost, stoost, etc.) that were orthographic-phonologically similar to a nonpresented critical lure, which was also a nonword (e.g., ploost). Experiment 1 showed a high level of false recognition for the critical lure. Experiment 2 showed that the false recognition effect was also present for forewarned participants who were informed about the nature of the false recognition effect and told to avoid making false recognition judgments. The present results show that false recognition effects can be obtained even when the critical lure itself is not stored during study. This finding is problematic for accounts that attribute false memories to implicit associative responses or spreading activation but is easily explained by global familiarity models of recognition memory.

A Human Activity Recognition System Using Skeleton Data from RGBD Sensors.

PubMed

Cippitelli, Enea; Gasparrini, Samuele; Gambi, Ennio; Spinsante, Susanna

2016-01-01

The aim of Active and Assisted Living is to develop tools to promote the ageing in place of elderly people, and human activity recognition algorithms can help to monitor aged people in home environments. Different types of sensors can be used to address this task and the RGBD sensors, especially the ones used for gaming, are cost-effective and provide much information about the environment. This work aims to propose an activity recognition algorithm exploiting skeleton data extracted by RGBD sensors. The system is based on the extraction of key poses to compose a feature vector, and a multiclass Support Vector Machine to perform classification. Computation and association of key poses are carried out using a clustering algorithm, without the need of a learning algorithm. The proposed approach is evaluated on five publicly available datasets for activity recognition, showing promising results especially when applied for the recognition of AAL related actions. Finally, the current applicability of this solution in AAL scenarios and the future improvements needed are discussed.

Do people's goals for mass participation sporting events matter? A self-determination theory perspective.

PubMed

Coleman, S J; Sebire, S J

2017-12-01

Non-elite mass participation sports events (MPSEs) may hold potential as a physical activity promotion tool. Research into why people participate in these events and what goals they are pursuing is lacking. Grounded in self-determination theory, this study examined the associations between MPSE participants' goals, event experiences and physical activity. A prospective cohort study was conducted; pre-event, participants reported their goals for the event. Four weeks post-event, participants reported their motivation for exercise, perceptions of their event achievement and moderate-to-vigorous intensity physical activity (MVPA). Bivariate correlations and path analysis were performed on data from 114 adults. Intrinsic goals (e.g. health, skill and social affiliation) for the event were positively associated with perceptions of event achievement, whereas extrinsic goals (e.g. appearance or social recognition) were not. Event achievement was positively associated with post-event autonomous motivation, which in turn was positively associated with MVPA. Pursuing intrinsic but not extrinsic goals for MPSEs is associated with greater perceptions of event achievement, which in turn is associated with post-event autonomous motivation and MVPA. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Activity Recognition in Social Media

DTIC Science & Technology

2015-12-29

AFRL-AFOSR-JP-TR-2016-0044 Activity Recognition in Social Media Subhasis Chaudhuri INDIAN INSTITUTE OF TECHNOLOGY BOMBAY Final Report 05/09/2016...DATES COVERED (From - To) 12 Aug 2013 to 30 Sep 2015 4. TITLE AND SUBTITLE Activity Recognition in Social Media 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER...PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) INDIAN INSTITUTE OF TECHNOLOGY BOMBAY POWAI MUMBAI, 400076 IN 8. PERFORMING ORGANIZATION REPORT NUMBER

The cost to successfully apply for level 3 medical home recognition

PubMed Central

Mottus, Kathleen; Reiter, Kristin; Mitchell, C. Madeline; Donahue, Katrina E.; Gabbard, Wilson M.; Gush, Kimberly

2016-01-01

BACKGROUND The NCQA Patient Centered Medical Home (PCMH) recognition program provides practices an opportunity to implement Medical home activities. Understanding the costs to apply for recognition may enable practices to plan their work. METHODS Practice coaches identified 5 exemplar practices that received level 3 recognition (3 pediatric and 2 family medicine practices). This analysis focuses on 4 that received 2011 recognition. Clinical, informatics and administrative staff participated in 2–3 hour interviews. We collected the time required to develop, implement and maintain required activities. We categorized costs as: 1) non-personnel, 2) developmental 3) those to implement activities 4) those to maintain activities, 5) those to document the work and 6) consultant costs. Only incremental costs were included and are presented as costs per full-time equivalent provider (pFTE) RESULTS Practice size ranged from 2.5 – 10.5 pFTE’s, payer mixes from 7–43 % Medicaid. There was variation in the distribution of costs by activity by practice; but the costs to apply were remarkably similar ($11,453–$15,977 pFTE). CONCLUSION The costs to apply for 2011 recognition were noteworthy. Work to enhance care coordination and close loops were highly valued. Financial incentives were key motivators. Future efforts to minimize the burden of low value activities could benefit practices. PMID:26769879

The role of the thalamic nuclei in recognition memory accompanied by recall during encoding and retrieval: an fMRI study.

PubMed

Pergola, Giulio; Ranft, Alexander; Mathias, Klaus; Suchan, Boris

2013-07-01

The present functional imaging study aimed at investigating the contribution of the mediodorsal nucleus and the anterior nuclei of the thalamus with their related cortical networks to recognition memory and recall. Eighteen subjects performed associative picture encoding followed by a single item recognition test during the functional magnetic resonance imaging session. After scanning, subjects performed a cued recall test using the formerly recognized pictures as cues. This post-scanning test served to classify recognition trials according to subsequent recall performance. In general, single item recognition accompanied by successful recall of the associations elicited stronger activation in the mediodorsal nucleus of the thalamus and in the prefrontal cortices both during encoding and retrieval compared to recognition without recall. In contrast, the anterior nuclei of the thalamus were selectively active during the retrieval phase of recognition followed by recall. A correlational analysis showed that activation of the anterior thalamus during retrieval as assessed by measuring the percent signal changes predicted lower rates of recognition without recall. These findings show that the thalamus is critical for recognition accompanied by recall, and provide the first evidence of a functional segregation of the thalamic nuclei with respect to the memory retrieval phase. In particular, the mediodorsal thalamic-prefrontal cortical network is activated during successful encoding and retrieval of associations, which suggests a role of this system in recall and recollection. The activity of the anterior thalamic-temporal network selectively during retrieval predicts better memory performances across subjects and this confirms the paramount role of this network in recall and recollection. Copyright © 2013 Elsevier Inc. All rights reserved.

The effect of word concreteness on recognition memory.

PubMed

Fliessbach, K; Weis, S; Klaver, P; Elger, C E; Weber, B

2006-09-01

Concrete words that are readily imagined are better remembered than abstract words. Theoretical explanations for this effect either claim a dual coding of concrete words in the form of both a verbal and a sensory code (dual-coding theory), or a more accessible semantic network for concrete words than for abstract words (context-availability theory). However, the neural mechanisms of improved memory for concrete versus abstract words are poorly understood. Here, we investigated the processing of concrete and abstract words during encoding and retrieval in a recognition memory task using event-related functional magnetic resonance imaging (fMRI). As predicted, memory performance was significantly better for concrete words than for abstract words. Abstract words elicited stronger activations of the left inferior frontal cortex both during encoding and recognition than did concrete words. Stronger activation of this area was also associated with successful encoding for both abstract and concrete words. Concrete words elicited stronger activations bilaterally in the posterior inferior parietal lobe during recognition. The left parietal activation was associated with correct identification of old stimuli. The anterior precuneus, left cerebellar hemisphere and the posterior and anterior cingulate cortex showed activations both for successful recognition of concrete words and for online processing of concrete words during encoding. Additionally, we observed a correlation across subjects between brain activity in the left anterior fusiform gyrus and hippocampus during recognition of learned words and the strength of the concreteness effect. These findings support the idea of specific brain processes for concrete words, which are reactivated during successful recognition.

Influence of time and length size feature selections for human activity sequences recognition.

PubMed

Fang, Hongqing; Chen, Long; Srinivasan, Raghavendiran

2014-01-01

In this paper, Viterbi algorithm based on a hidden Markov model is applied to recognize activity sequences from observed sensors events. Alternative features selections of time feature values of sensors events and activity length size feature values are tested, respectively, and then the results of activity sequences recognition performances of Viterbi algorithm are evaluated. The results show that the selection of larger time feature values of sensor events and/or smaller activity length size feature values will generate relatively better results on the activity sequences recognition performances. © 2013 ISA Published by ISA All rights reserved.

Activity and function recognition for moving and static objects in urban environments from wide-area persistent surveillance inputs

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Bobick, Aaron; Jones, Eric

2010-04-01

In this paper, we describe results from experimental analysis of a model designed to recognize activities and functions of moving and static objects from low-resolution wide-area video inputs. Our model is based on representing the activities and functions using three variables: (i) time; (ii) space; and (iii) structures. The activity and function recognition is achieved by imposing lexical, syntactic, and semantic constraints on the lower-level event sequences. In the reported research, we have evaluated the utility and sensitivity of several algorithms derived from natural language processing and pattern recognition domains. We achieved high recognition accuracy for a wide range of activity and function types in the experiments using Electro-Optical (EO) imagery collected by Wide Area Airborne Surveillance (WAAS) platform.

A Unified Framework for Activity Recognition-Based Behavior Analysis and Action Prediction in Smart Homes

PubMed Central

Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

2013-01-01

In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences. PMID:23435057

Neural correlates of incidental memory in mild cognitive impairment: an fMRI study.

PubMed

Mandzia, Jennifer L; McAndrews, Mary Pat; Grady, Cheryl L; Graham, Simon J; Black, Sandra E

2009-05-01

Behaviour and fMRI brain activation patterns were compared during encoding and recognition tasks in mild cognitive impairment (MCI) (n=14) and normal controls (NC) (n=14). Deep (natural vs. man-made) and shallow (color vs. black and white) decisions were made at encoding and pictures from each condition were presented for yes/no recognition 20 min later. MCI showed less inferior frontal activation during deep (left only) and superficial encoding (bilaterally) and in both medial temporal lobes (MTL). When performance was equivalent (recognition of words encoded superficially), MTL activation was similar for the two groups, but during recognition testing of deeply encoded items NC showed more activation in both prefrontal and left MTL region. In a region of interest analysis, the extent of activation during deep encoding in the parahippocampi bilaterally and in left hippocampus correlated with subsequent recognition accuracy for those items in controls but not in MCI, which may reflect the heterogeneity of activation responses in conjunction with different degrees of pathology burden and progression status in the MCI group.

Location-Enhanced Activity Recognition in Indoor Environments Using Off the Shelf Smart Watch Technology and BLE Beacons

PubMed Central

Filippoupolitis, Avgoustinos; Oliff, William; Takand, Babak; Loukas, George

2017-01-01

Activity recognition in indoor spaces benefits context awareness and improves the efficiency of applications related to personalised health monitoring, building energy management, security and safety. The majority of activity recognition frameworks, however, employ a network of specialised building sensors or a network of body-worn sensors. As this approach suffers with respect to practicality, we propose the use of commercial off-the-shelf devices. In this work, we design and evaluate an activity recognition system composed of a smart watch, which is enhanced with location information coming from Bluetooth Low Energy (BLE) beacons. We evaluate the performance of this approach for a variety of activities performed in an indoor laboratory environment, using four supervised machine learning algorithms. Our experimental results indicate that our location-enhanced activity recognition system is able to reach a classification accuracy ranging from 92% to 100%, while without location information classification accuracy it can drop to as low as 50% in some cases, depending on the window size chosen for data segmentation. PMID:28555022

Activity Recognition Invariant to Sensor Orientation with Wearable Motion Sensors.

PubMed

Yurtman, Aras; Barshan, Billur

2017-08-09

Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is of interest to develop wearable systems that operate invariantly to sensor position and orientation. We focus on invariance to sensor orientation and develop two alternative transformations to remove the effect of absolute sensor orientation from the raw sensor data. We test the proposed methodology in activity recognition with four state-of-the-art classifiers using five publicly available datasets containing various types of human activities acquired by different sensor configurations. While the ordinary activity recognition system cannot handle incorrectly oriented sensors, the proposed transformations allow the sensors to be worn at any orientation at a given position on the body, and achieve nearly the same activity recognition performance as the ordinary system for which the sensor units are not rotatable. The proposed techniques can be applied to existing wearable systems without much effort, by simply transforming the time-domain sensor data at the pre-processing stage.

Comparing physical and mental health literacy.

PubMed

Vimalanathan, Adshara; Furnham, Adrian

2018-04-27

This study attempted to ascertain whether people had better mental vs physical health literacy by comparing their knowledge of six conditions. The aim was to link two different literatures which have remained apart. In all, 186 young British participants (52% male) with an average age of 25 years completed an online questionnaire describing six vignettes characters. Three described mental health conditions (anorexia, bipolar disorder and schizophrenia) and three physical health conditions (asthma, diabetes and osteoarthritis). Participants were required to name the illness and rate how treatable and manageable they believed the condition is. They were also asked to rate how much the problem would affect an individual's daily life and suggest whether the individual should seek professional help. The recognition of specific mental health conditions (anorexia, borderline personality disorder, schizophrenia) was marginally higher than the recognition of physical health conditions (arthritis, asthma, diabetes). Ratings about treatment and the effect of each illness showed considerable variation. The results suggest that people are equally and relatively poorly informed about relatively common mental compared to physical illnesses.

Translating policies into practice: a framework to prevent childhood obesity in afterschool programs.

PubMed

Beets, Michael W; Webster, Collin; Saunders, Ruth; Huberty, Jennifer L

2013-03-01

Afterschool programs (3-6 p.m.) are positioned to play a critical role in combating childhood obesity. To this end, state and national organizations have developed policies related to promoting physical activity and guiding the nutritional quality of snacks served in afterschool programs. No conceptual frameworks, however, are available that describe the process of how afterschool programs will translate such policies into daily practice to reach eventual outcomes. Drawing from complex systems theory, this article describes the development of a framework that identifies critical modifiable levers within afterschool programs that can be altered and/or strengthened to reach policy goals. These include the policy environment at the national, state, and local levels; individual site, afterschool program leader, staff, and child characteristics; and existing outside organizational partnerships. Use of this framework and recognition of its constituent elements have the potential to lead to the successful and sustainable adoption and implementation of physical activity and nutrition policies in afterschool programs nationwide.

Assessing sustainability of InSHAPE participants' fitness activities in a community mental health setting.

PubMed

Lesley, Marsha L; Livingood, Kristi; Livingwood, Kristi

2015-02-01

InSHAPE (Self Help Action Plan for Empowerment), an exercise and nutrition wellness program, is gaining national recognition for its success in helping individuals with serious mental illness (SMI) improve physical fitness and dietary habits. Although gains have been reported in objective measures of fitness as participants progressed through the year-long program, there is little information about what happens with participants after program completion. To address this gap in knowledge, the authors conducted a longitudinal qualitative study in which 11 InSHAPE participants were interviewed both near the end of their year in the program and 9 months later. Participants identified the trainer's ability to contain their initial feelings of distress and form a working alliance as factors that contributed to their exercise persistence. Current findings suggest that individuals with SMI may need a longer period of time working closely with fitness trainers to sustain physical activity levels achieved during the program. Copyright 2015, SLACK Incorporated.

Face Encoding and Recognition in the Human Brain

NASA Astrophysics Data System (ADS)

Haxby, James V.; Ungerleider, Leslie G.; Horwitz, Barry; Maisog, Jose Ma.; Rapoport, Stanley I.; Grady, Cheryl L.

1996-01-01

A dissociation between human neural systems that participate in the encoding and later recognition of new memories for faces was demonstrated by measuring memory task-related changes in regional cerebral blood flow with positron emission tomography. There was almost no overlap between the brain structures associated with these memory functions. A region in the right hippocampus and adjacent cortex was activated during memory encoding but not during recognition. The most striking finding in neocortex was the lateralization of prefrontal participation. Encoding activated left prefrontal cortex, whereas recognition activated right prefrontal cortex. These results indicate that the hippocampus and adjacent cortex participate in memory function primarily at the time of new memory encoding. Moreover, face recognition is not mediated simply by recapitulation of operations performed at the time of encoding but, rather, involves anatomically dissociable operations.

Modeling Interval Temporal Dependencies for Complex Activities Understanding

DTIC Science & Technology

2013-10-11

ORGANIZATION NAMES AND ADDRESSES U.S. Army Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 15. SUBJECT TERMS Human activity modeling...computer vision applications: human activity recognition and facial activity recognition. The results demonstrate the superior performance of the

High-resolution physical and functional mapping of the template adjacent DNA binding site in catalytically active telomerase.

PubMed

Romi, Erez; Baran, Nava; Gantman, Marina; Shmoish, Michael; Min, Bosun; Collins, Kathleen; Manor, Haim

2007-05-22

Telomerase is a cellular reverse transcriptase, which utilizes an integral RNA template to extend single-stranded telomeric DNA. We used site-specific photocrosslinking to map interactions between DNA primers and the catalytic protein subunit (tTERT) of Tetrahymena thermophila telomerase in functional enzyme complexes. Our assays reveal contact of the single-stranded DNA adjacent to the primer-template hybrid and tTERT residue W187 at the periphery of the N-terminal domain. This contact was detected in complexes with three different registers of template in the active site, suggesting that it is maintained throughout synthesis of a complete telomeric repeat. Substitution of nearby residue Q168, but not W187, alters the K(m) for primer elongation, implying that it plays a role in the DNA recognition. These findings are the first to directly demonstrate the physical location of TERT-DNA contacts in catalytically active telomerase and to identify amino acid determinants of DNA binding affinity. Our data also suggest a movement of the TERT active site relative to the template-adjacent single-stranded DNA binding site within a cycle of repeat synthesis.

A single bout of resistance exercise can enhance episodic memory performance.

PubMed

Weinberg, Lisa; Hasni, Anita; Shinohara, Minoru; Duarte, Audrey

2014-11-01

Acute aerobic exercise can be beneficial to episodic memory. This benefit may occur because exercise produces a similar physiological response as physical stressors. When administered during consolidation, acute stress, both physical and psychological, consistently enhances episodic memory, particularly memory for emotional materials. Here we investigated whether a single bout of resistance exercise performed during consolidation can produce episodic memory benefits 48 h later. We used a one-leg knee extension/flexion task for the resistance exercise. To assess the physiological response to the exercise, we measured salivary alpha amylase (a biomarker of central norepinephrine), heart rate, and blood pressure. To test emotional episodic memory, we used a remember-know recognition memory paradigm with equal numbers of positive, negative, and neutral IAPS images as stimuli. The group that performed the exercise, the active group, had higher overall recognition accuracy than the group that did not exercise, the passive group. We found a robust effect of valence across groups, with better performance on emotional items as compared to neutral items and no difference between positive and negative items. This effect changed based on the physiological response to the exercise. Within the active group, participants with a high physiological response to the exercise were impaired for neutral items as compared to participants with a low physiological response to the exercise. Our results demonstrate that a single bout of resistance exercise performed during consolidation can enhance episodic memory and that the effect of valence on memory depends on the physiological response to the exercise. Copyright © 2014 Elsevier B.V. All rights reserved.

Overestimation of physical activity level is associated with lower BMI: a cross-sectional analysis.

PubMed

Watkinson, Clare; van Sluijs, Esther Mf; Sutton, Stephen; Hardeman, Wendy; Corder, Kirsten; Griffin, Simon J

2010-09-20

Poor recognition of physical inactivity may be an important barrier to healthy behaviour change, but little is known about this phenomenon. We aimed to characterize a high-risk population according to the discrepancies between objective and self-rated physical activity (PA), defined as awareness. An exploratory cross-sectional analysis of PA awareness using baseline data collected from 365 ProActive participants between 2001 and 2003 in East Anglia, England. Self-rated PA was defined as 'active' or 'inactive' (assessed via questionnaire). Objective PA was defined according to achievement of guideline activity levels (≥30 minutes or <30 minutes spent at least moderate intensity PA, assessed by heart rate monitoring). Four awareness groups were created: 'Realistic Actives', 'Realistic Inactives', 'Overestimators' and 'Underestimators'. Logistic regression was used to assess associations between awareness group and 17 personal, social and biological correlates. 63.3% of participants (N = 231) were inactive according to objective measurement. Of these, 45.9% rated themselves as active ('Overestimators'). In a multiple logistic regression model adjusted for age and smoking, males (OR = 2.11, 95% CI = 1.12, 3.98), those with lower BMI (OR = 0.89, 95% CI = 0.84, 0.95), younger age at completion of full-time education (OR = 0.83, 95% CI = 0.74, 0.93) and higher general health perception (OR = 1.02 CI = 1.00, 1.04) were more likely to overestimate their PA. Overestimation of PA is associated with favourable indicators of relative slimness and general health. Feedback about PA levels could help reverse misperceptions.

Activity Recognition for Personal Time Management

NASA Astrophysics Data System (ADS)

Prekopcsák, Zoltán; Soha, Sugárka; Henk, Tamás; Gáspár-Papanek, Csaba

We describe an accelerometer based activity recognition system for mobile phones with a special focus on personal time management. We compare several data mining algorithms for the automatic recognition task in the case of single user and multiuser scenario, and improve accuracy with heuristics and advanced data mining methods. The results show that daily activities can be recognized with high accuracy and the integration with the RescueTime software can give good insights for personal time management.

Feature Selection in Classification of Eye Movements Using Electrooculography for Activity Recognition

PubMed Central

Mala, S.; Latha, K.

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition. PMID:25574185

Feature selection in classification of eye movements using electrooculography for activity recognition.

PubMed

Mala, S; Latha, K

2014-01-01

Activity recognition is needed in different requisition, for example, reconnaissance system, patient monitoring, and human-computer interfaces. Feature selection plays an important role in activity recognition, data mining, and machine learning. In selecting subset of features, an efficient evolutionary algorithm Differential Evolution (DE), a very efficient optimizer, is used for finding informative features from eye movements using electrooculography (EOG). Many researchers use EOG signals in human-computer interactions with various computational intelligence methods to analyze eye movements. The proposed system involves analysis of EOG signals using clearness based features, minimum redundancy maximum relevance features, and Differential Evolution based features. This work concentrates more on the feature selection algorithm based on DE in order to improve the classification for faultless activity recognition.

Wide-threat detection: recognition of adversarial missions and activity patterns in Empire Challenge 2009

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Shabarekh, Charlotte; Furjanic, Caitlin

2011-06-01

In this paper, we present results of adversarial activity recognition using data collected in the Empire Challenge (EC 09) exercise. The EC09 experiment provided an opportunity to evaluate our probabilistic spatiotemporal mission recognition algorithms using the data from live air-born and ground sensors. Using ambiguous and noisy data about locations of entities and motion events on the ground, the algorithms inferred the types and locations of OPFOR activities, including reconnaissance, cache runs, IED emplacements, logistics, and planning meetings. In this paper, we present detailed summary of the validation study and recognition accuracy results. Our algorithms were able to detect locations and types of over 75% of hostile activities in EC09 while producing 25% false alarms.

Differential effects of acute and regular physical exercise on cognition and affect.

PubMed

Hopkins, M E; Davis, F C; Vantieghem, M R; Whalen, P J; Bucci, D J

2012-07-26

The effects of regular exercise versus a single bout of exercise on cognition, anxiety, and mood were systematically examined in healthy, sedentary young adults who were genotyped to determine brain-derived neurotrophic factor (BDNF) allelic status (i.e., Val-Val or Val66Met polymorphism). Participants were evaluated on novel object recognition (NOR) memory and a battery of mental health surveys before and after engaging in either (a) a 4-week exercise program, with exercise on the final test day, (b) a 4-week exercise program, without exercise on the final test day, (c) a single bout of exercise on the final test day, or (d) remaining sedentary between test days. Exercise enhanced object recognition memory and produced a beneficial decrease in perceived stress, but only in participants who exercised for 4 weeks including the final day of testing. In contrast, a single bout of exercise did not affect recognition memory and resulted in increased perceived stress levels. An additional novel finding was that the improvements on the NOR task were observed exclusively in participants who were homozygous for the BDNF Val allele, indicating that altered activity-dependent release of BDNF in Met allele carriers may attenuate the cognitive benefits of exercise. Importantly, exercise-induced changes in cognition were not correlated with changes in mood/anxiety, suggesting that separate neural systems mediate these effects. These data in humans mirror recent data from our group in rodents. Taken together, these current findings provide new insights into the behavioral and neural mechanisms that mediate the effects of physical exercise on memory and mental health in humans. Copyright © 2012 IBRO. Published by Elsevier Ltd. All rights reserved.

Automatic recognition of postural allocations.

PubMed

Sazonov, Edward; Krishnamurthy, Vidya; Makeyev, Oleksandr; Browning, Ray; Schutz, Yves; Hill, James

2007-01-01

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.

No Space for Girliness in Physics: Understanding and Overcoming the Masculinity of Physics

ERIC Educational Resources Information Center

Götschel, Helene

2014-01-01

Allison Gonsalves' article on "women doctoral students' positioning around discourses of gender and competence in physics" explores narratives of Canadian women physicists concerning their strategies to gain recognition as physicists. In my response to her rewarding and inspiring analysis I will reflect on her findings and arguments and…

Identifying the physical and anthropometric qualities explanatory of paddling adolescents.

PubMed

Sinclair, Wade H; Leicht, Anthony S; Eady, Troy W; Marshall, Nick J; Woods, Carl T

2017-12-01

This study aimed to identify the physical and/or anthropometric qualities explanatory of adolescent surf lifesavers participating in paddling activities. Cross-sectional observational study. A total of 53 (14-18years) male participants were recruited and classified into two groups; paddlers (n=30; actively participating in paddling), non-paddlers (n=23; not actively participating in paddling). All participants completed a testing battery that consisted of 16 physical (isometric strength and muscular endurance) and anthropometric (height, mass, segment lengths and breadths) assessments. Binary logistic regression models and receiver operating characteristic curves were built to identify the physical and/or anthropometric qualities most explanatory of paddling status (two levels: 1=paddlers, 0=non-paddlers). Significant between group differences were noted for 14 of the 16 assessments (P<0.05; d=0.59-1.29). However, it was the combination of horizontal shoulder abduction isometric strength, body mass, and sitting height that provided the greatest association with paddling status (Akaike Information Criterion=47.13). This full model successfully detected 87% and 70% of the paddlers and non-paddlers, respectively, with an area under the curve of 84.2%. These results indicate that there are distinctive physical and anthropometric qualities that may be advantageous for prospective paddling athletes to possess. Practitioners should integrate assessments of horizontal shoulder abduction isometric strength, body mass, and sitting height, as well as their subsequent cut-off thresholds, into talent detection programs focused toward the recognition of performance potential in paddling-oriented sports. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Neurocomputational bases of object and face recognition.

PubMed Central

Biederman, I; Kalocsai, P

1997-01-01

A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in a two-dimensional (2D) coordinate space, as proposed by C. von der Malsburg and his associates, may account for many of the phenomena associated with face recognition. An additional refinement, in which each column of filters (termed a 'jet') is centred on a particular facial feature (or fiducial point), allows selectivity of the input into the holistic representation to avoid incorporation of occluding or nearby surfaces. The initial hypercolumn representation also characterizes the first stage of object perception, but the image variation for objects at a given location in a 2D coordinate space may be too great to yield sufficient predictability directly from the output of spatial kernels. Consequently, objects can be represented by a structural description specifying qualitative (typically, non-accidental) characterizations of an object's parts, the attributes of the parts, and the relations among the parts, largely based on orientation and depth discontinuities (as shown by Hummel & Biederman). A series of experiments on the name priming or physical matching of complementary images (in the Fourier domain) of objects and faces documents that whereas face recognition is strongly dependent on the original spatial filter values, evidence from object recognition indicates strong invariance to these values, even when distinguishing among objects that are as similar as faces. PMID:9304687

Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

PubMed

Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

2016-06-01

Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

[Analysis of fourteen French national programmes on physical activity and sports as determinants of health from 2001 to 2006].

PubMed

Bréchat, Pierre-Henri; Vogel, Thomas; Berthel, Marc; Kaltenbach, Georges; Le Divenah, Aude; Segouin, Christophe; Rymer, Roland; Lonsdorfer, Jean

2009-01-01

Physical activity and sports are considered as one of the determinants of health. The aim of this study is to review the rationale for the formulation of this public health issue and its integration in national action plans. The study shows that fourteen national programmes were drafted and implemented between 2001 and 2006 by seven institutions. The research methodology was based on crossing data obtained from semi-directed interviews and documents regarding the design, implementation and follow-up of these programmes. For the conditions of the success, the fourteen actions scored an average of 175.0 +/- 66.9 out of 300%. Public health actors and professionals must be given more opportunities to involve themselves and engage in developing stronger relationships and linkages, in particular with the institutional and community settings. In general, the most invested parts of a programme are the structural and operational aspects of activities. Six significant points surfaced from the study: consideration of drug use as an addictive behaviour; recognition of the psychological stress of professional athletes; acknowledgment of youth as being at high risk for doping behaviour; integration of the concept that physical activity and sports must take the benefit/risk perspective into account; and the necessity to promote health. Through the exchange of numerous local and regional experiences, an optimisation of their synergistic connections was made possible on a continuum extending from "health promotion through physical activity and sports" to "prevention of drug-use and doping behaviours". Professionals have been able to develop actions in the above-mentioned domains across this continuum that have, to date, remained isolated. Proposals are made to strengthen these dynamics. Other health determinants and public health priorities could be investigated with the same methodology.

Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries †

PubMed Central

Gutiérrez-López-Franca, Carlos; Hervás, Ramón; Johnson, Esperanza

2018-01-01

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the Extended Body-Angles Algorithm, which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its relevant joints, which makes it possible to monitor the body of the user selecting only a subset of the same. But this feature of the system has both advantages and disadvantages. As a consequence, in the past we had some difficulties with the recognition of activities that only have a small subset of the joints of the body as relevant. The goal of this work, therefore, is to analyze the effect produced by the application of several strategies on the results of an activity recognition system based on skeletal tracking joint oriented devices. Strategies that we applied with the purpose of improve the recognition rates of the activities with a small subset of relevant joints. Through the results of this work, we aim to give the scientific community some first indications about which considered strategy is better. PMID:29789478

The Cost to Successfully Apply for Level 3 Medical Home Recognition.

PubMed

Halladay, Jacqueline R; Mottus, Kathleen; Reiter, Kristin; Mitchell, C Madeline; Donahue, Katrina E; Gabbard, Wilson M; Gush, Kimberly

2016-01-01

The National Committee for Quality Assurance patient-centered medical home recognition program provides practices an opportunity to implement medical home activities. Understanding the costs to apply for recognition may enable practices to plan their work. Practice coaches identified 5 exemplar practices (3 pediatric and 2 family medicine practices) that received level 3 recognition. This analysis focuses on 4 that received recognition in 2011. Clinical, informatics, and administrative staff participated in 2- to 3-hour interviews. We determined the time required to develop, implement, and maintain required activities. We categorized costs as (1) nonpersonnel, (2) developmental, (3) those used to implement activities, (4) those used to maintain activities, (5) those to document the work, and (6) consultant costs. Only incremental costs were included and are presented as costs per full-time equivalent (pFTE) provider. Practice size ranged from 2.5 to 10.5 pFTE providers, and payer mixes ranged from 7% to 43% Medicaid. There was variation in the distribution of costs by activity by practice, but the costs to apply were remarkably similar ($11,453-15,977 pFTE provider). The costs to apply for 2011 recognition were noteworthy. Work to enhance care coordination and close loops were highly valued. Financial incentives were key motivators. Future efforts to minimize the burden of low-value activities could benefit practices. © Copyright 2016 by the American Board of Family Medicine.

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment.

PubMed

Cicirelli, Franco; Fortino, Giancarlo; Giordano, Andrea; Guerrieri, Antonio; Spezzano, Giandomenico; Vinci, Andrea

2016-09-01

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

Human-inspired sound environment recognition system for assistive vehicles

NASA Astrophysics Data System (ADS)

González Vidal, Eduardo; Fredes Zarricueta, Ernesto; Auat Cheein, Fernando

2015-02-01

Objective. The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. Approach. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. Main results. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. Significance. The proposed sound-based system is very efficient at providing general descriptions of the environment. Such descriptions are focused on vulnerable situations described by the ICF. The volunteers answered a questionnaire regarding the importance of constraining the vehicle velocities in risky environments, showing that all the volunteers felt comfortable with the system and its performance.

Human-inspired sound environment recognition system for assistive vehicles.

PubMed

Vidal, Eduardo González; Zarricueta, Ernesto Fredes; Cheein, Fernando Auat

2015-02-01

The human auditory system acquires environmental information under sound stimuli faster than visual or touch systems, which in turn, allows for faster human responses to such stimuli. It also complements senses such as sight, where direct line-of-view is necessary to identify objects, in the environment recognition process. This work focuses on implementing human reaction to sound stimuli and environment recognition on assistive robotic devices, such as robotic wheelchairs or robotized cars. These vehicles need environment information to ensure safe navigation. In the field of environment recognition, range sensors (such as LiDAR and ultrasonic systems) and artificial vision devices are widely used; however, these sensors depend on environment constraints (such as lighting variability or color of objects), and sound can provide important information for the characterization of an environment. In this work, we propose a sound-based approach to enhance the environment recognition process, mainly for cases that compromise human integrity, according to the International Classification of Functioning (ICF). Our proposal is based on a neural network implementation that is able to classify up to 15 different environments, each selected according to the ICF considerations on environment factors in the community-based physical activities of people with disabilities. The accuracy rates in environment classification ranges from 84% to 93%. This classification is later used to constrain assistive vehicle navigation in order to protect the user during daily activities. This work also includes real-time outdoor experimentation (performed on an assistive vehicle) by seven volunteers with different disabilities (but without cognitive impairment and experienced in the use of wheelchairs), statistical validation, comparison with previously published work, and a discussion section where the pros and cons of our system are evaluated. The proposed sound-based system is very efficient at providing general descriptions of the environment. Such descriptions are focused on vulnerable situations described by the ICF. The volunteers answered a questionnaire regarding the importance of constraining the vehicle velocities in risky environments, showing that all the volunteers felt comfortable with the system and its performance.

Active Multimodal Sensor System for Target Recognition and Tracking

PubMed Central

Zhang, Guirong; Zou, Zhaofan; Liu, Ziyue; Mao, Jiansen

2017-01-01

High accuracy target recognition and tracking systems using a single sensor or a passive multisensor set are susceptible to external interferences and exhibit environmental dependencies. These difficulties stem mainly from limitations to the available imaging frequency bands, and a general lack of coherent diversity of the available target-related data. This paper proposes an active multimodal sensor system for target recognition and tracking, consisting of a visible, an infrared, and a hyperspectral sensor. The system makes full use of its multisensor information collection abilities; furthermore, it can actively control different sensors to collect additional data, according to the needs of the real-time target recognition and tracking processes. This level of integration between hardware collection control and data processing is experimentally shown to effectively improve the accuracy and robustness of the target recognition and tracking system. PMID:28657609

Pattern activation/recognition theory of mind

PubMed Central

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

Pattern activation/recognition theory of mind.

PubMed

du Castel, Bertrand

2015-01-01

In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

Dealing with the Effects of Sensor Displacement in Wearable Activity Recognition

PubMed Central

Banos, Oresti; Toth, Mate Attila; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

2014-01-01

Most wearable activity recognition systems assume a predefined sensor deployment that remains unchanged during runtime. However, this assumption does not reflect real-life conditions. During the normal use of such systems, users may place the sensors in a position different from the predefined sensor placement. Also, sensors may move from their original location to a different one, due to a loose attachment. Activity recognition systems trained on activity patterns characteristic of a given sensor deployment may likely fail due to sensor displacements. In this work, we innovatively explore the effects of sensor displacement induced by both the intentional misplacement of sensors and self-placement by the user. The effects of sensor displacement are analyzed for standard activity recognition techniques, as well as for an alternate robust sensor fusion method proposed in a previous work. While classical recognition models show little tolerance to sensor displacement, the proposed method is proven to have notable capabilities to assimilate the changes introduced in the sensor position due to self-placement and provides considerable improvements for large misplacements. PMID:24915181

The Pandora multi-algorithm approach to automated pattern recognition in LAr TPC detectors

NASA Astrophysics Data System (ADS)

Marshall, J. S.; Blake, A. S. T.; Thomson, M. A.; Escudero, L.; de Vries, J.; Weston, J.; MicroBooNE Collaboration

2017-09-01

The development and operation of Liquid Argon Time Projection Chambers (LAr TPCs) for neutrino physics has created a need for new approaches to pattern recognition, in order to fully exploit the superb imaging capabilities offered by this technology. The Pandora Software Development Kit provides functionality to aid the process of designing, implementing and running pattern recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition: individual algorithms each address a specific task in a particular topology; a series of many tens of algorithms then carefully builds-up a picture of the event. The input to the Pandora pattern recognition is a list of 2D Hits. The output from the chain of over 70 algorithms is a hierarchy of reconstructed 3D Particles, each with an identified particle type, vertex and direction.

[Explicit memory for type font of words in source monitoring and recognition tasks].

PubMed

Hatanaka, Yoshiko; Fujita, Tetsuya

2004-02-01

We investigated whether people can consciously remember type fonts of words by methods of examining explicit memory; source-monitoring and old/new-recognition. We set matched, non-matched, and non-studied conditions between the study and the test words using two kinds of type fonts; Gothic and MARU. After studying words in one way of encoding, semantic or physical, subjects in a source-monitoring task made a three way discrimination between new words, Gothic words, and MARU words (Exp. 1). Subjects in an old/new-recognition task indicated whether test words were previously presented or not (Exp. 2). We compared the source judgments with old/new recognition data. As a result, these data showed conscious recollection for type font of words on the source monitoring task and dissociation between source monitoring and old/new recognition performance.

Bypassing adverse injection reactions to nanoparticles through shape modification and attachment to erythrocytes

NASA Astrophysics Data System (ADS)

Wibroe, Peter Popp; Anselmo, Aaron C.; Nilsson, Per H.; Sarode, Apoorva; Gupta, Vivek; Urbanics, Rudolf; Szebeni, Janos; Hunter, Alan Christy; Mitragotri, Samir; Mollnes, Tom Eirik; Moghimi, Seyed Moein

2017-07-01

Intravenously injected nanopharmaceuticals, including PEGylated nanoparticles, induce adverse cardiopulmonary reactions in sensitive human subjects, and these reactions are highly reproducible in pigs. Although the underlying mechanisms are poorly understood, roles for both the complement system and reactive macrophages have been implicated. Here, we show the dominance and importance of robust pulmonary intravascular macrophage clearance of nanoparticles in mediating adverse cardiopulmonary distress in pigs irrespective of complement activation. Specifically, we show that delaying particle recognition by macrophages within the first few minutes of injection overcomes adverse reactions in pigs using two independent approaches. First, we changed the particle geometry from a spherical shape (which triggers cardiopulmonary distress) to either rod- or disk-shape morphology. Second, we physically adhered spheres to the surface of erythrocytes. These strategies, which are distinct from commonly leveraged stealth engineering approaches such as nanoparticle surface functionalization with poly(ethylene glycol) and/or immunological modulators, prevent robust macrophage recognition, resulting in the reduction or mitigation of adverse cardiopulmonary distress associated with nanopharmaceutical administration.

The effect of encoding strategy on the neural correlates of memory for faces.

PubMed

Bernstein, Lori J; Beig, Sania; Siegenthaler, Amy L; Grady, Cheryl L

2002-01-01

Encoding and recognition of unfamiliar faces in young adults were examined using positron emission tomography to determine whether different encoding strategies would lead to encoding/retrieval differences in brain activity. Three types of encoding were compared: a 'deep' task (judging pleasantness/unpleasantness), a 'shallow' task (judging right/left orientation), and an intentional learning task in which subjects were instructed to learn the faces for a subsequent memory test but were not provided with a specific strategy. Memory for all faces was tested with an old/new recognition test. A modest behavioral effect was obtained, with deeply-encoded faces being recognized more accurately than shallowly-encoded or intentionally-learned faces. Regardless of encoding strategy, encoding activated a primarily ventral system including bilateral temporal and fusiform regions and left prefrontal cortices, whereas recognition activated a primarily dorsal set of regions including right prefrontal and parietal areas. Within encoding, the type of strategy produced different brain activity patterns, with deep encoding being characterized by left amygdala and left anterior cingulate activation. There was no effect of encoding strategy on brain activity during the recognition conditions. Posterior fusiform gyrus activation was related to better recognition accuracy in those conditions encouraging perceptual strategies, whereas activity in left frontal and temporal areas correlated with better performance during the 'deep' condition. Results highlight three important aspects of face memory: (1) the effect of encoding strategy was seen only at encoding and not at recognition; (2) left inferior prefrontal cortex was engaged during encoding of faces regardless of strategy; and (3) differential activity in fusiform gyrus was found, suggesting that activity in this area is not only a result of automatic face processing but is modulated by controlled processes.

The Roles of Spreading Activation and Retrieval Mode in Producing False Recognition in the DRM Paradigm

ERIC Educational Resources Information Center

Meade, Michelle L.; Watson, Jason M.; Balota, David A.; Roediger, Henry L., III

2007-01-01

The nature of persisting spreading activation from list presentation in eliciting false recognition in the Deese-Roediger-McDermott (DRM) paradigm was examined in two experiments. We compared the time course of semantic priming in the lexical decision task (LDT) and false alarms in speeded recognition under identical study and test conditions. The…

Parietal cortex and episodic memory retrieval in schizophrenia.

PubMed

Lepage, Martin; Pelletier, Marc; Achim, Amélie; Montoya, Alonso; Menear, Matthew; Lal, Sam

2010-06-30

People with schizophrenia consistently show memory impairment on varying tasks including item recognition memory. Relative to the correct rejection of distracter items, the correct recognition of studied items consistently produces an effect termed the old/new effect that is characterized by increased activity in parietal and frontal cortical regions. This effect has received only scant attention in schizophrenia. We examined the old/new effect in 15 people with schizophrenia and 18 controls during an item recognition test, and neural activity was examined with event-related functional magnetic resonance imaging. Both groups performed equally well during the recognition test and showed increased activity in a left dorsolateral prefrontal region and in the precuneus bilaterally during the successful recognition of old items relative to the correct rejection of new items. The control group also exhibited increased activity in the dorsal left parietal cortex. This region has been implicated in the top-down modulation of memory which involves control processes that support memory-retrieval search, monitoring and verification. Although these processes may not be of paramount importance in item recognition memory performance, the present findings suggest that people with schizophrenia may have difficulty with such top-down modulation, a finding consistent with many other studies in information processing.

fMRI characterization of visual working memory recognition.

PubMed

Rahm, Benjamin; Kaiser, Jochen; Unterrainer, Josef M; Simon, Juliane; Bledowski, Christoph

2014-04-15

Encoding and maintenance of information in visual working memory have been extensively studied, highlighting the crucial and capacity-limiting role of fronto-parietal regions. In contrast, the neural basis of recognition in visual working memory has remained largely unspecified. Cognitive models suggest that recognition relies on a matching process that compares sensory information with the mental representations held in memory. To characterize the neural basis of recognition we varied both the need for recognition and the degree of similarity between the probe item and the memory contents, while independently manipulating memory load to produce load-related fronto-parietal activations. fMRI revealed a fractionation of working memory functions across four distributed networks. First, fronto-parietal regions were activated independent of the need for recognition. Second, anterior parts of load-related parietal regions contributed to recognition but their activations were independent of the difficulty of matching in terms of sample-probe similarity. These results argue against a key role of the fronto-parietal attention network in recognition. Rather the third group of regions including bilateral temporo-parietal junction, posterior cingulate cortex and superior frontal sulcus reflected demands on matching both in terms of sample-probe-similarity and the number of items to be compared. Also, fourth, bilateral motor regions and right superior parietal cortex showed higher activation when matching provided clear evidence for a decision. Together, the segregation between the well-known fronto-parietal activations attributed to attentional operations in working memory from those regions involved in matching supports the theoretical view of separable attentional and mnemonic contributions to working memory. Yet, the close theoretical and empirical correspondence to perceptual decision making may call for an explicit consideration of decision making mechanisms in conceptions of working memory. Copyright © 2013 Elsevier Inc. All rights reserved.

Effects of Isometric Hand-Grip Muscle Contraction on Young Adults' Free Recall and Recognition Memory

ERIC Educational Resources Information Center

Tomporowski, Phillip D.; Albrecht, Chelesa; Pendleton, Daniel M.

2017-01-01

Purpose: The purpose of this study was to determine if physical arousal produced by isometric hand-dynamometer contraction performed during word-list learning affects young adults' free recall or recognition memory. Method: Twenty-four young adults (12 female; M[subscript age] = 22 years) were presented with 4 20-item word lists. Moderate arousal…

Towards discrete wavelet transform-based human activity recognition

NASA Astrophysics Data System (ADS)

Khare, Manish; Jeon, Moongu

2017-06-01

Providing accurate recognition of human activities is a challenging problem for visual surveillance applications. In this paper, we present a simple and efficient algorithm for human activity recognition based on a wavelet transform. We adopt discrete wavelet transform (DWT) coefficients as a feature of human objects to obtain advantages of its multiresolution approach. The proposed method is tested on multiple levels of DWT. Experiments are carried out on different standard action datasets including KTH and i3D Post. The proposed method is compared with other state-of-the-art methods in terms of different quantitative performance measures. The proposed method is found to have better recognition accuracy in comparison to the state-of-the-art methods.

One recognition sequence, seven restriction enzymes, five reaction mechanisms

PubMed Central

Gowers, Darren M.; Bellamy, Stuart R.W.; Halford, Stephen E.

2004-01-01

The diversity of reaction mechanisms employed by Type II restriction enzymes was investigated by analysing the reactions of seven endonucleases at the same DNA sequence. NarI, KasI, Mly113I, SfoI, EgeI, EheI and BbeI cleave DNA at several different positions in the sequence 5′-GGCGCC-3′. Their reactions on plasmids with one or two copies of this sequence revealed five distinct mechanisms. These differ in terms of the number of sites the enzyme binds, and the number of phosphodiester bonds cleaved per turnover. NarI binds two sites, but cleaves only one bond per DNA-binding event. KasI also cuts only one bond per turnover but acts at individual sites, preferring intact to nicked sites. Mly113I cuts both strands of its recognition sites, but shows full activity only when bound to two sites, which are then cleaved concertedly. SfoI, EgeI and EheI cut both strands at individual sites, in the manner historically considered as normal for Type II enzymes. Finally, BbeI displays an absolute requirement for two sites in close physical proximity, which are cleaved concertedly. The range of reaction mechanisms for restriction enzymes is thus larger than commonly imagined, as is the number of enzymes needing two recognition sites. PMID:15226412

Rationale, design and methods for a staggered-entry, waitlist controlled clinical trial of the impact of a community-based, family-centred, multidisciplinary program focussed on activity, food and attitude habits (Curtin University’s Activity, Food and Attitudes Program—CAFAP) among overweight adolescents

PubMed Central

2012-01-01

Background Current estimates place just under one quarter of adolescents in Australia as overweight or obese. Adolescence has been identified as a critical period for the development of obesity, yet despite this recognition, there is limited systematic research into or evaluation of interventions for overweight adolescents. Reviews have concluded that there is a substantive evidence gap for effective intervention, but physical activity, lifestyle change and family involvement have been identified as promising foci for treatment. Methods This paper reports on the development of a staggered-entry, waitlist controlled clinical trial to assess the impact of a multidisciplinary intervention aiming to change the poor health trajectory of overweight adolescents and help them avoid morbid obesity in adulthood—Curtin University’s Activity, Food and Attitudes Program (CAFAP). 96 adolescents, aged 11–16 years, and parents, will attend twice weekly during an 8 week intensive multidisciplinary program with maintenance follow-up focussed on improving activity, food and attitude habits. Follow-up assessments will be conducted immediately after completing the intensive program, and at 3, 6 and 12 months post intensive program. Main outcomes will be objectively-measured physical activity, sedentary behaviour and activity behaviours; food intake (measured by 3 day diary) and food behaviours; body composition, fitness and physical function; mental and social well-being (quality of life, mood and attitudes), and family functioning. Discussion This trial will provide important information to understand whether a community based multidisciplinary intervention can have short and medium term effects on activity and food habits, attitudes, and physical and mental health status of overweight adolescents. Trial registration Australian New Zealand Clinical Trials Registry ACTRN12611001187932. PMID:22721261

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

PubMed Central

Beruvides, Gerardo

2017-01-01

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions. PMID:28906450

Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

2017-09-14

Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

Age-specific effects of voluntary exercise on memory and the older brain.

PubMed

Siette, Joyce; Westbrook, R Frederick; Cotman, Carl; Sidhu, Kuldip; Zhu, Wanlin; Sachdev, Perminder; Valenzuela, Michael J

2013-03-01

Physical exercise in early adulthood and mid-life improves cognitive function and enhances brain plasticity, but the effects of commencing exercise in late adulthood are not well-understood. We investigated the effects of voluntary exercise in the restoration of place recognition memory in aged rats and examined hippocampal changes of synaptic density and neurogenesis. We found a highly selective age-related deficit in place recognition memory that is stable across retest sessions and correlates strongly with loss of hippocampal synapses. Additionally, 12 weeks of voluntary running at 20 months of age removed the deficit in the hippocampally dependent place recognition memory. Voluntary running restored presynaptic density in the dentate gyrus and CA3 hippocampal subregions in aged rats to levels beyond those observed in younger animals, in which exercise had no functional or synaptic effects. By contrast, hippocampal neurogenesis, a possible memory-related mechanism, increased in both young and aged rats after physical exercise but was not linked with performance in the place recognition task. We used graph-based network analysis based on synaptic covariance patterns to characterize efficient intrahippocampal connectivity. This analysis revealed that voluntary running completely reverses the profound degradation of hippocampal network efficiency that accompanies sedentary aging. Furthermore, at an individual animal level, both overall hippocampal presynaptic density and subregional connectivity independently contribute to prediction of successful place recognition memory performance. Our findings emphasize the unique synaptic effects of exercise on the aged brain and their specific relevance to a hippocampally based memory system for place recognition. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Student Recognition of Visual Affordances: Supporting Use of Physics Simulations in Whole Class and Small Group Settings

ERIC Educational Resources Information Center

Stephens, A. Lynn

2012-01-01

The purpose of this study is to investigate student interactions with simulations, and teacher support of those interactions, within naturalistic high school physics classroom settings. This study focuses on data from two lesson sequences that were conducted in several physics classrooms. The lesson sequences were conducted in a whole class…

[Study on molecular recognition technology in active constituents extracted and isolated from Aconitum pendulum].

PubMed

Ma, Xue-Qin; Li, Guo-Shan; Fu, Xue-Yan; Ma, Jing-Zu

2011-03-01

To investigate CD molecular recognition technology applied in active constituents extracted and isolated from traditional Chinese medicine--Aconitum pendulum. The inclusion constant and form probability of the inclusion complex of Aconitum pendulum with p-CD was calculated by UV spectra method. The active constituents of Aconitum pendulum were extracted and isolated by molecular recognition technology. The inclusion complex was identified by UV. The chemical constituents of Aconitum pendulum and inclusion complex was determined by HPLC. The analgesic effects of inclusion complex was investigated by experiment of intraperitoneal injection of acetic acid in rats. The inclusion complex was identified and confirmed by UV spectra method, the chemical components of inclusion complex were simple, and the content of active constituents increased significantly, the analgesic effects of inclusion complex was well. The molecular recognition technology can be used for extracting and isolating active constituents of Aconitum pendulum, and the effects are obvious.

Mental health literacy: knowledge of depression among undergraduate students in Hanoi, Vietnam.

PubMed

Nguyen Thai, Quynh Chi; Nguyen, Thanh Huong

2018-01-01

Mental health literacy (MHL) refers to an individuals' knowledge and beliefs about mental disorders that aid their recognition, management, and prevention. This study aims to investigate the MHL of depression among public health and sociology undergraduate students in Hanoi, Vietnam. A cross-sectional survey was carried out from May to September 2015. Data was collected using an anonymous, self-administered questionnaire distributed to 350 undergraduate students (213 public health majors; 137 sociology majors). Questions about MHL of depression were adapted from the Australian National Survey of Mental Health Literacy and Stigma. Question topics included recognition of depression, help-seeking intentions, first-aid support, and knowledge about interventions to help people with depression. Chi squared tests were conducted to compare proportional statistics across groups for multiple measures. With regard to recognition of mental disorders, 32.0% of the respondents used the accurate label "depression" for the vignette. Among those who correctly identified depression, 82.1% would seek help. The corresponding statistic was 81.1% from those who did not recognize depression. Both groups would seek help from counselor, psychologist, family members, and close friends. First-aid support suggested by the respondents in both groups were informal sources ( to listen to her problem in an understanding way, to encourage her to be more physically active , etc.). The interventions considered most helpful by the respondents were self-help strategies such as learning how to relax , getting physically active , doing exercise early in the morning , and reading a self - help book . Joining a group of individuals with similar problems was chosen to be a helpful intervention among those who did not recognize depression (p < 0.001), but those who correctly identify depression believed that people with depression should be admitted to hospital for psychiatric treatment (p < 0.05). There is a need for education about MHL of depression among undergraduate students in Vietnam. The training can focus on symptoms of depression, appropriate help-seeking intentions, and first-aid support relevant to the Vietnamese context.

Nonlinear changes in brain activity during continuous word repetition: an event-related multiparametric functional MR imaging study.

PubMed

Hagenbeek, R E; Rombouts, S A R B; Veltman, D J; Van Strien, J W; Witter, M P; Scheltens, P; Barkhof, F

2007-10-01

Changes in brain activation as a function of continuous multiparametric word recognition have not been studied before by using functional MR imaging (fMRI), to our knowledge. Our aim was to identify linear changes in brain activation and, what is more interesting, nonlinear changes in brain activation as a function of extended word repetition. Fifteen healthy young right-handed individuals participated in this study. An event-related extended continuous word-recognition task with 30 target words was used to study the parametric effect of word recognition on brain activation. Word-recognition-related brain activation was studied as a function of 9 word repetitions. fMRI data were analyzed with a general linear model with regressors for linearly changing signal intensity and nonlinearly changing signal intensity, according to group average reaction time (RT) and individual RTs. A network generally associated with episodic memory recognition showed either constant or linearly decreasing brain activation as a function of word repetition. Furthermore, both anterior and posterior cingulate cortices and the left middle frontal gyrus followed the nonlinear curve of the group RT, whereas the anterior cingulate cortex was also associated with individual RT. Linear alteration in brain activation as a function of word repetition explained most changes in blood oxygen level-dependent signal intensity. Using a hierarchically orthogonalized model, we found evidence for nonlinear activation associated with both group and individual RTs.

PKC-epsilon activation is required for recognition memory in the rat.

PubMed

Zisopoulou, Styliani; Asimaki, Olga; Leondaritis, George; Vasilaki, Anna; Sakellaridis, Nikos; Pitsikas, Nikolaos; Mangoura, Dimitra

2013-09-15

Activation of PKCɛ, an abundant and developmentally regulated PKC isoform in the brain, has been implicated in memory throughout life and across species. Yet, direct evidence for a mechanistic role for PKCɛ in memory is still lacking. Hence, we sought to evaluate this in rats, using short-term treatments with two PKCɛ-selective peptides, the inhibitory ɛV1-2 and the activating ψɛRACK, and the novel object recognition task (NORT). Our results show that the PKCɛ-selective activator ψɛRACK, did not have a significant effect on recognition memory. In the short time frames used, however, inhibition of PKCɛ activation with the peptide inhibitor ɛV1-2 significantly impaired recognition memory. Moreover, when we addressed at the molecular level the immediate proximal signalling events of PKCɛ activation in acutely dissected rat hippocampi, we found that ψɛRACK increased in a time-dependent manner phosphorylation of MARCKS and activation of Src, Raf, and finally ERK1/2, whereas ɛV1-2 inhibited all basal activity of this pathway. Taken together, these findings present the first direct evidence that PKCɛ activation is an essential molecular component of recognition memory and point toward the use of systemically administered PKCɛ-regulating peptides as memory study tools and putative therapeutic agents. Copyright © 2013 Elsevier B.V. All rights reserved.

A depth video sensor-based life-logging human activity recognition system for elderly care in smart indoor environments.

PubMed

Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

2014-07-02

Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital.

A Depth Video Sensor-Based Life-Logging Human Activity Recognition System for Elderly Care in Smart Indoor Environments

PubMed Central

Jalal, Ahmad; Kamal, Shaharyar; Kim, Daijin

2014-01-01

Recent advancements in depth video sensors technologies have made human activity recognition (HAR) realizable for elderly monitoring applications. Although conventional HAR utilizes RGB video sensors, HAR could be greatly improved with depth video sensors which produce depth or distance information. In this paper, a depth-based life logging HAR system is designed to recognize the daily activities of elderly people and turn these environments into an intelligent living space. Initially, a depth imaging sensor is used to capture depth silhouettes. Based on these silhouettes, human skeletons with joint information are produced which are further used for activity recognition and generating their life logs. The life-logging system is divided into two processes. Firstly, the training system includes data collection using a depth camera, feature extraction and training for each activity via Hidden Markov Models. Secondly, after training, the recognition engine starts to recognize the learned activities and produces life logs. The system was evaluated using life logging features against principal component and independent component features and achieved satisfactory recognition rates against the conventional approaches. Experiments conducted on the smart indoor activity datasets and the MSRDailyActivity3D dataset show promising results. The proposed system is directly applicable to any elderly monitoring system, such as monitoring healthcare problems for elderly people, or examining the indoor activities of people at home, office or hospital. PMID:24991942

Is it me? Self-recognition bias across sensory modalities and its relationship to autistic traits.

PubMed

Chakraborty, Anya; Chakrabarti, Bhismadev

2015-01-01

Atypical self-processing is an emerging theme in autism research, suggested by lower self-reference effect in memory, and atypical neural responses to visual self-representations. Most research on physical self-processing in autism uses visual stimuli. However, the self is a multimodal construct, and therefore, it is essential to test self-recognition in other sensory modalities as well. Self-recognition in the auditory modality remains relatively unexplored and has not been tested in relation to autism and related traits. This study investigates self-recognition in auditory and visual domain in the general population and tests if it is associated with autistic traits. Thirty-nine neurotypical adults participated in a two-part study. In the first session, individual participant's voice was recorded and face was photographed and morphed respectively with voices and faces from unfamiliar identities. In the second session, participants performed a 'self-identification' task, classifying each morph as 'self' voice (or face) or an 'other' voice (or face). All participants also completed the Autism Spectrum Quotient (AQ). For each sensory modality, slope of the self-recognition curve was used as individual self-recognition metric. These two self-recognition metrics were tested for association between each other, and with autistic traits. Fifty percent 'self' response was reached for a higher percentage of self in the auditory domain compared to the visual domain (t = 3.142; P < 0.01). No significant correlation was noted between self-recognition bias across sensory modalities (τ = -0.165, P = 0.204). Higher recognition bias for self-voice was observed in individuals higher in autistic traits (τ AQ = 0.301, P = 0.008). No such correlation was observed between recognition bias for self-face and autistic traits (τ AQ = -0.020, P = 0.438). Our data shows that recognition bias for physical self-representation is not related across sensory modalities. Further, individuals with higher autistic traits were better able to discriminate self from other voices, but this relation was not observed with self-face. A narrow self-other overlap in the auditory domain seen in individuals with high autistic traits could arise due to enhanced perceptual processing of auditory stimuli often observed in individuals with autism.

The posterior parietal cortex in recognition memory: a neuropsychological study.

PubMed

Haramati, Sharon; Soroker, Nachum; Dudai, Yadin; Levy, Daniel A

2008-01-01

Several recent functional neuroimaging studies have reported robust bilateral activation (L>R) in lateral posterior parietal cortex and precuneus during recognition memory retrieval tasks. It has not yet been determined what cognitive processes are represented by those activations. In order to examine whether parietal lobe-based processes are necessary for basic episodic recognition abilities, we tested a group of 17 first-incident CVA patients whose cortical damage included (but was not limited to) extensive unilateral posterior parietal lesions. These patients performed a series of tasks that yielded parietal activations in previous fMRI studies: yes/no recognition judgments on visual words and on colored object pictures and identifiable environmental sounds. We found that patients with left hemisphere lesions were not impaired compared to controls in any of the tasks. Patients with right hemisphere lesions were not significantly impaired in memory for visual words, but were impaired in recognition of object pictures and sounds. Two lesion--behavior analyses--area-based correlations and voxel-based lesion symptom mapping (VLSM)---indicate that these impairments resulted from extra-parietal damage, specifically to frontal and lateral temporal areas. These findings suggest that extensive parietal damage does not impair recognition performance. We suggest that parietal activations recorded during recognition memory tasks might reflect peri-retrieval processes, such as the storage of retrieved memoranda in a working memory buffer for further cognitive processing.

Vision based assistive technology for people with dementia performing activities of daily living (ADLs): an overview

NASA Astrophysics Data System (ADS)

As'ari, M. A.; Sheikh, U. U.

2012-04-01

The rapid development of intelligent assistive technology for replacing a human caregiver in assisting people with dementia performing activities of daily living (ADLs) promises in the reduction of care cost especially in training and hiring human caregiver. The main problem however, is the various kinds of sensing agents used in such system and is dependent on the intent (types of ADLs) and environment where the activity is performed. In this paper on overview of the potential of computer vision based sensing agent in assistive system and how it can be generalized and be invariant to various kind of ADLs and environment. We find that there exists a gap from the existing vision based human action recognition method in designing such system due to cognitive and physical impairment of people with dementia.

Rhabdomyolysis in a Sickle Cell Trait Positive Active Duty Male Soldier.

PubMed

Saxena, Pulkit; Chavarria, Christopher; Thurlow, John

2016-01-01

Exertional rhabdomyolysis is a complication of sickle cell trait (SCT) likely first reported in the military population over 40 years ago. Although commonly a benign condition, numerous studies and case reports have identified SCT positive patients to be at increased risk for rhabdomyolysis, compartment syndrome and sudden cardiac death. We report a recent case of an SCT positive African American active duty male Soldier who suffered exertional rhabdomyolysis following an Army Physical Fitness Test. His course was complicated by acute renal failure requiring hemodialysis, and he eventually recovered renal function. The diagnosis was significantly delayed despite a typical clinical presentation and available SCT screening results. The case highlights the importance of the recognition of SCT as a risk factor for severe rhabdomyolysis, and suggests more must be done for an effective SCT screening program for the active duty military population.

PEOPLE IN PHYSICS: Interview with Peter Higgs

NASA Astrophysics Data System (ADS)

Fancey, Conducted by Norman

1998-01-01

Peter Higgs, FRSE, FRS held until recently a personal chair in theoretical physics at the University of Edinburgh and is now an emeritus professor. Peter is well known for predicting the existence of a new particle, the Higgs boson - as yet unconfirmed. He has been awarded a number of prizes in recognition of his work, most recently the Paul Dirac Medal and Prize for outstanding contributions to theoretical physics from the Institute of Physics and the 1997 High Energy and Particle Physics Prize by the European Physical Society.

Multi-resolution analysis for ear recognition using wavelet features

NASA Astrophysics Data System (ADS)

Shoaib, M.; Basit, A.; Faye, I.

2016-11-01

Security is very important and in order to avoid any physical contact, identification of human when they are moving is necessary. Ear biometric is one of the methods by which a person can be identified using surveillance cameras. Various techniques have been proposed to increase the ear based recognition systems. In this work, a feature extraction method for human ear recognition based on wavelet transforms is proposed. The proposed features are approximation coefficients and specific details of level two after applying various types of wavelet transforms. Different wavelet transforms are applied to find the suitable wavelet. Minimum Euclidean distance is used as a matching criterion. Results achieved by the proposed method are promising and can be used in real time ear recognition system.

Exosites in the substrate specificity of blood coagulation reactions.

PubMed

Bock, P E; Panizzi, P; Verhamme, I M A

2007-07-01

The specificity of blood coagulation proteinases for substrate, inhibitor, and effector recognition is mediated by exosites on the surfaces of the catalytic domains, physically separated from the catalytic site. Some thrombin ligands bind specifically to either exosite I or II, while others engage both exosites. The involvement of different, overlapping constellations of exosite residues enables binding of structurally diverse ligands. The flexibility of the thrombin structure is central to the mechanism of complex formation and the specificity of exosite interactions. Encounter complex formation is driven by electrostatic ligand-exosite interactions, followed by conformational rearrangement to a stable complex. Exosites on some zymogens are in low affinity proexosite states and are expressed concomitant with catalytic site activation. The requirement for exosite expression controls the specificity of assembly of catalytic complexes on the coagulation pathway, such as the membrane-bound factor Xa*factor Va (prothrombinase) complex, and prevents premature assembly. Substrate recognition by prothrombinase involves a two-step mechanism with initial docking of prothrombin to exosites, followed by a conformational change to engage the FXa catalytic site. Prothrombin and its activation intermediates bind prothrombinase in two alternative conformations determined by the zymogen to proteinase transition that are hypothesized to involve prothrombin (pro)exosite I interactions with FVa, which underpin the sequential activation pathway. The role of exosites as the major source of substrate specificity has stimulated development of exosite-targeted anticoagulants for treatment of thrombosis.

Physical Human Activity Recognition Using Wearable Sensors.

PubMed

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-12-11

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors' placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject.

Physical Human Activity Recognition Using Wearable Sensors

PubMed Central

Attal, Ferhat; Mohammed, Samer; Dedabrishvili, Mariam; Chamroukhi, Faicel; Oukhellou, Latifa; Amirat, Yacine

2015-01-01

This paper presents a review of different classification techniques used to recognize human activities from wearable inertial sensor data. Three inertial sensor units were used in this study and were worn by healthy subjects at key points of upper/lower body limbs (chest, right thigh and left ankle). Three main steps describe the activity recognition process: sensors’ placement, data pre-processing and data classification. Four supervised classification techniques namely, k-Nearest Neighbor (k-NN), Support Vector Machines (SVM), Gaussian Mixture Models (GMM), and Random Forest (RF) as well as three unsupervised classification techniques namely, k-Means, Gaussian mixture models (GMM) and Hidden Markov Model (HMM), are compared in terms of correct classification rate, F-measure, recall, precision, and specificity. Raw data and extracted features are used separately as inputs of each classifier. The feature selection is performed using a wrapper approach based on the RF algorithm. Based on our experiments, the results obtained show that the k-NN classifier provides the best performance compared to other supervised classification algorithms, whereas the HMM classifier is the one that gives the best results among unsupervised classification algorithms. This comparison highlights which approach gives better performance in both supervised and unsupervised contexts. It should be noted that the obtained results are limited to the context of this study, which concerns the classification of the main daily living human activities using three wearable accelerometers placed at the chest, right shank and left ankle of the subject. PMID:26690450

Clustering-Based Ensemble Learning for Activity Recognition in Smart Homes

PubMed Central

Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

2014-01-01

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks. PMID:25014095

Clustering-based ensemble learning for activity recognition in smart homes.

PubMed

Jurek, Anna; Nugent, Chris; Bi, Yaxin; Wu, Shengli

2014-07-10

Application of sensor-based technology within activity monitoring systems is becoming a popular technique within the smart environment paradigm. Nevertheless, the use of such an approach generates complex constructs of data, which subsequently requires the use of intricate activity recognition techniques to automatically infer the underlying activity. This paper explores a cluster-based ensemble method as a new solution for the purposes of activity recognition within smart environments. With this approach activities are modelled as collections of clusters built on different subsets of features. A classification process is performed by assigning a new instance to its closest cluster from each collection. Two different sensor data representations have been investigated, namely numeric and binary. Following the evaluation of the proposed methodology it has been demonstrated that the cluster-based ensemble method can be successfully applied as a viable option for activity recognition. Results following exposure to data collected from a range of activities indicated that the ensemble method had the ability to perform with accuracies of 94.2% and 97.5% for numeric and binary data, respectively. These results outperformed a range of single classifiers considered as benchmarks.

Activity Recognition on Streaming Sensor Data.

PubMed

Krishnan, Narayanan C; Cook, Diane J

2014-02-01

Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition.

Adapted Physical Education and Therapeutic Recreation in Schools

ERIC Educational Resources Information Center

Etzel-Wise, D; Mears, B

2004-01-01

Adapted physical education is a mandated service, whereas therapeutic recreation and traditional recreation are considered related services under the Individuals with Disabilities Education Act. In this article, the authors describe the distinctions between the services, recognition of need for referral, methods of assessment, sample…

Barriers to Teaching Introductory Physical Geography Online

ERIC Educational Resources Information Center

Ritter, Michael E.

2012-01-01

Learning geography online is becoming an option for more students but not without controversy. Issues of faculty resources, logistics, professional recognition, and pedagogical concerns are cited as barriers to teaching online. Offering introductory physical geography online presents special challenges. As a general education course, an…

Rad4 recognition-at-a-distance: Physical basis of conformation-specific anomalous diffusion of DNA repair proteins.

PubMed

Kong, Muwen; Van Houten, Bennett

2017-08-01

Since Robert Brown's first observations of random walks by pollen particles suspended in solution, the concept of diffusion has been subject to countless theoretical and experimental studies in diverse fields from finance and social sciences, to physics and biology. Diffusive transport of macromolecules in cells is intimately linked to essential cellular functions including nutrient uptake, signal transduction, gene expression, as well as DNA replication and repair. Advancement in experimental techniques has allowed precise measurements of these diffusion processes. Mathematical and physical descriptions and computer simulations have been applied to model complicated biological systems in which anomalous diffusion, in addition to simple Brownian motion, was observed. The purpose of this review is to provide an overview of the major physical models of anomalous diffusion and corresponding experimental evidence on the target search problem faced by DNA-binding proteins, with an emphasis on DNA repair proteins and the role of anomalous diffusion in DNA target recognition. Copyright © 2016 Elsevier Ltd. All rights reserved.

The "Finding Physics" Project: Recognizing and Exploring Physics Outside the Classroom

NASA Astrophysics Data System (ADS)

Beck, Judith; Perkins, James

2016-11-01

Students in introductory physics classes often have difficulty recognizing the relevance of physics concepts outside the confines of the physics classroom, lab, and textbook. Even though textbooks and instructors often provide examples of physics applications from a wide array of areas, students have difficulty relating physics to their own lives. Encouraging students to apply physics to their own surroundings helps them develop the critical analysis skills of a scientifically literate and competent citizen. Fink, in his book Creating Significant Learning Experiences, emphasizes the importance of constructing opportunities to help students connect what they learn in their academic courses with past and current life experiences and link them to possible future life experiences. Several excellent papers in this journal have presented labs and activities that address this concern by encouraging teachers to bring real-world examples into the classroom or to take students into the field for data collection and observation. Alternatively, Smith suggests a writing exercise in which his students identify and explain an event in terms of their understanding of physics. In this paper we present a multiphase exercise that challenges students to find their own examples of physics from outside the classroom and analyze them using the conceptual understanding and quantitative skills which they are developing in the classroom. The ultimate goal of the "Finding Physics" project is to improve students' learning through enhancing their recognition that, to quote one participant's end-of-course survey, "Physics is everywhere!"

Thermodynamic Modeling of Donor Splice Site Recognition in pre-mRNA

NASA Astrophysics Data System (ADS)

Aalberts, Daniel P.; Garland, Jeffrey A.

2004-03-01

When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 snRNA with the donor (5') splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our Finding with Binding method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.

Thermodynamic modeling of donor splice site recognition in pre-mRNA

NASA Astrophysics Data System (ADS)

Garland, Jeffrey A.; Aalberts, Daniel P.

2004-04-01

When eukaryotic genes are edited by the spliceosome, the first step in intron recognition is the binding of a U1 small nuclear RNA with the donor ( 5' ) splice site. We model this interaction thermodynamically to identify splice sites. Applied to a set of 65 annotated genes, our “finding with binding” method achieves a significant separation between real and false sites. Analyzing binding patterns allows us to discard a large number of decoy sites. Our results improve statistics-based methods for donor site recognition, demonstrating the promise of physical modeling to find functional elements in the genome.

Primitive processes, metaphor, and recognition in the treatment of traumatic loss.

PubMed

Ansorge, William

2012-12-01

This paper explores how traumatic loss and emotional abuse ruptured a patient's symbolic process and shattered her experience of the reality of her self. In treatment, metaphoric investigation of physical processes of expulsion and incorporation led to a transformation of projective identification into the containment she sought. The therapist's ability to metabolize pain, shame, and the risks of incestuous merger re-experienced in the treatment grew out of his recognition of disturbing experiences of his own that she brought to life. Mutual recognition, linked to the therapist's reverie, was a key treatment factor as both patient and therapist changed.

Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity.

PubMed

Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki

2017-01-01

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.

A Set of Handwriting Features for Use in Automated Writer Identification.

PubMed

Miller, John J; Patterson, Robert Bradley; Gantz, Donald T; Saunders, Christopher P; Walch, Mark A; Buscaglia, JoAnn

2017-05-01

A writer's biometric identity can be characterized through the distribution of physical feature measurements ("writer's profile"); a graph-based system that facilitates the quantification of these features is described. To accomplish this quantification, handwriting is segmented into basic graphical forms ("graphemes"), which are "skeletonized" to yield the graphical topology of the handwritten segment. The graph-based matching algorithm compares the graphemes first by their graphical topology and then by their geometric features. Graphs derived from known writers can be compared against graphs extracted from unknown writings. The process is computationally intensive and relies heavily upon statistical pattern recognition algorithms. This article focuses on the quantification of these physical features and the construction of the associated pattern recognition methods for using the features to discriminate among writers. The graph-based system described in this article has been implemented in a highly accurate and approximately language-independent biometric recognition system of writers of cursive documents. © 2017 American Academy of Forensic Sciences.

Adjunctive selective estrogen receptor modulator increases neural activity in the hippocampus and inferior frontal gyrus during emotional face recognition in schizophrenia.

PubMed

Ji, E; Weickert, C S; Lenroot, R; Kindler, J; Skilleter, A J; Vercammen, A; White, C; Gur, R E; Weickert, T W

2016-05-03

Estrogen has been implicated in the development and course of schizophrenia with most evidence suggesting a neuroprotective effect. Treatment with raloxifene, a selective estrogen receptor modulator, can reduce symptom severity, improve cognition and normalize brain activity during learning in schizophrenia. People with schizophrenia are especially impaired in the identification of negative facial emotions. The present study was designed to determine the extent to which adjunctive raloxifene treatment would alter abnormal neural activity during angry facial emotion recognition in schizophrenia. Twenty people with schizophrenia (12 men, 8 women) participated in a 13-week, randomized, double-blind, placebo-controlled, crossover trial of adjunctive raloxifene treatment (120 mg per day orally) and performed a facial emotion recognition task during functional magnetic resonance imaging after each treatment phase. Two-sample t-tests in regions of interest selected a priori were performed to assess activation differences between raloxifene and placebo conditions during the recognition of angry faces. Adjunctive raloxifene significantly increased activation in the right hippocampus and left inferior frontal gyrus compared with the placebo condition (family-wise error, P<0.05). There was no significant difference in performance accuracy or reaction time between active and placebo conditions. To the best of our knowledge, this study provides the first evidence suggesting that adjunctive raloxifene treatment changes neural activity in brain regions associated with facial emotion recognition in schizophrenia. These findings support the hypothesis that estrogen plays a modifying role in schizophrenia and shows that adjunctive raloxifene treatment may reverse abnormal neural activity during facial emotion recognition, which is relevant to impaired social functioning in men and women with schizophrenia.

Patterns recognition of electric brain activity using artificial neural networks

NASA Astrophysics Data System (ADS)

Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.

2017-04-01

An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.

Enemy at the gates: traffic at the plant cell pathogen interface.

PubMed

Hoefle, Caroline; Hückelhoven, Ralph

2008-12-01

The plant apoplast constitutes a space for early recognition of potentially harmful non-self. Basal pathogen recognition operates via dynamic sensing of conserved microbial patterns by pattern recognition receptors or of elicitor-active molecules released from plant cell walls during infection. Recognition elicits defence reactions depending on cellular export via SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) complex-mediated vesicle fusion or plasma membrane transporter activity. Lipid rafts appear also involved in focusing immunity-associated proteins to the site of pathogen contact. Simultaneously, pathogen effectors target recognition, apoplastic host proteins and transport for cell wall-associated defence. This microreview highlights most recent reports on the arms race for plant disease and immunity at the cell surface.

The impact of sport on health status, psychological well-being and physical performance of adults with haemophilia.

PubMed

von Mackensen, S; Harrington, C; Tuddenham, E; Littley, A; Will, A; Fareh, M; Hay, C R M; Khair, K

2016-07-01

There is increasing recognition that sport is important for individuals with haemophilia; however, there remains a paucity of data of the importance of this in adults, many of whom already have joint pathology related to childhood bleeds and treatment access. This multicentre, cross-sectional study presents the impact of sport on health-related quality of life (HRQoL), physical performance and clinical outcomes in adults with haemophilia. Fifty adults aged 35.12±14.7 with mild (n = 12), moderate (n = 10), or severe (n = 28) haemophilia A (70%) or B (30%) from four haemophilia centres across the United Kingdom participated in the study. A total of 64% were overweight/obese according to their BMI; median orthopaedic joint scores using the WFH Orthopaedic Joint Score (OJS) were 6 (range 0-48). On a VAS pain scale (range of 0-10), patients reported mean score of 5.66 ± 2.4. 36% of participants reported not doing any sport, mainly due to their physical condition. However, 64% of participants reported undertaking sporting activity including contact sports, mostly twice per week in average 4 h week(-1) . Participating in sport did not have a statistically significant impact on HRQoL; except in the domain 'sport and leisure' of the Haem-A-QoL. Patients doing more sport reported significantly better HRQoL than those doing less sport (P < 0.005). Those doing sport for more than 4 h week(-1) had a significantly better physical performance than patients doing less sport (assessed with Hep-Test-Q). Encouraging physical activity and sport in older patients with haemophilia may have a direct impact on their HRQoL; thus, education about sport activity should be incorporated into routine haemophilia care. © 2016 John Wiley & Sons Ltd.

Parallel language activation and cognitive control during spoken word recognition in bilinguals

PubMed Central

Blumenfeld, Henrike K.; Marian, Viorica

2013-01-01

Accounts of bilingual cognitive advantages suggest an associative link between cross-linguistic competition and inhibitory control. We investigate this link by examining English-Spanish bilinguals’ parallel language activation during auditory word recognition and nonlinguistic Stroop performance. Thirty-one English-Spanish bilinguals and 30 English monolinguals participated in an eye-tracking study. Participants heard words in English (e.g., comb) and identified corresponding pictures from a display that included pictures of a Spanish competitor (e.g., conejo, English rabbit). Bilinguals with higher Spanish proficiency showed more parallel language activation and smaller Stroop effects than bilinguals with lower Spanish proficiency. Across all bilinguals, stronger parallel language activation between 300–500ms after word onset was associated with smaller Stroop effects; between 633–767ms, reduced parallel language activation was associated with smaller Stroop effects. Results suggest that bilinguals who perform well on the Stroop task show increased cross-linguistic competitor activation during early stages of word recognition and decreased competitor activation during later stages of word recognition. Findings support the hypothesis that cross-linguistic competition impacts domain-general inhibition. PMID:24244842

Increased Screening for Child Physical Abuse in Emergency Departments in a Regional Trauma System: Response to a Sentinel Event.

PubMed

Wilkins, Ginger G; Ball, Jane; Mann, N Clay; Nadkarni, Milan; Meredith, J Wayne

2016-01-01

A pediatric patient was assaulted while being treated at a Level 1 pediatric trauma center, prompting a Centers for Medicare & Medicaid Services site visit. The process of screening for physical abuse and protection of patients was reevaluated and revised, and a new guideline was implemented and shared with referral hospitals. During this same time period, 13 referral hospitals participated in an unrelated federally funded study determining the impact of recognition and care of injured children in states with and without a pediatric emergency care facility recognition program. A pre-post study analysis revealed that screening for abuse doubled during this time period.

How many steps/day are enough? For adults.

PubMed

Tudor-Locke, Catrine; Craig, Cora L; Brown, Wendy J; Clemes, Stacy A; De Cocker, Katrien; Giles-Corti, Billie; Hatano, Yoshiro; Inoue, Shigeru; Matsudo, Sandra M; Mutrie, Nanette; Oppert, Jean-Michel; Rowe, David A; Schmidt, Michael D; Schofield, Grant M; Spence, John C; Teixeira, Pedro J; Tully, Mark A; Blair, Steven N

2011-07-28

Physical activity guidelines from around the world are typically expressed in terms of frequency, duration, and intensity parameters. Objective monitoring using pedometers and accelerometers offers a new opportunity to measure and communicate physical activity in terms of steps/day. Various step-based versions or translations of physical activity guidelines are emerging, reflecting public interest in such guidance. However, there appears to be a wide discrepancy in the exact values that are being communicated. It makes sense that step-based recommendations should be harmonious with existing evidence-based public health guidelines that recognize that "some physical activity is better than none" while maintaining a focus on time spent in moderate-to-vigorous physical activity (MVPA). Thus, the purpose of this review was to update our existing knowledge of "How many steps/day are enough?", and to inform step-based recommendations consistent with current physical activity guidelines. Normative data indicate that healthy adults typically take between 4,000 and 18,000 steps/day, and that 10,000 steps/day is reasonable for this population, although there are notable "low active populations." Interventions demonstrate incremental increases on the order of 2,000-2,500 steps/day. The results of seven different controlled studies demonstrate that there is a strong relationship between cadence and intensity. Further, despite some inter-individual variation, 100 steps/minute represents a reasonable floor value indicative of moderate intensity walking. Multiplying this cadence by 30 minutes (i.e., typical of a daily recommendation) produces a minimum of 3,000 steps that is best used as a heuristic (i.e., guiding) value, but these steps must be taken over and above habitual activity levels to be a true expression of free-living steps/day that also includes recommendations for minimal amounts of time in MVPA. Computed steps/day translations of time in MVPA that also include estimates of habitual activity levels equate to 7,100 to 11,000 steps/day. A direct estimate of minimal amounts of MVPA accumulated in the course of objectively monitored free-living behaviour is 7,000-8,000 steps/day. A scale that spans a wide range of incremental increases in steps/day and is congruent with public health recognition that "some physical activity is better than none," yet still incorporates step-based translations of recommended amounts of time in MVPA may be useful in research and practice. The full range of users (researchers to practitioners to the general public) of objective monitoring instruments that provide step-based outputs require good reference data and evidence-based recommendations to be able to design effective health messages congruent with public health physical activity guidelines, guide behaviour change, and ultimately measure, track, and interpret steps/day.

How many steps/day are enough? for adults

PubMed Central

2011-01-01

Physical activity guidelines from around the world are typically expressed in terms of frequency, duration, and intensity parameters. Objective monitoring using pedometers and accelerometers offers a new opportunity to measure and communicate physical activity in terms of steps/day. Various step-based versions or translations of physical activity guidelines are emerging, reflecting public interest in such guidance. However, there appears to be a wide discrepancy in the exact values that are being communicated. It makes sense that step-based recommendations should be harmonious with existing evidence-based public health guidelines that recognize that "some physical activity is better than none" while maintaining a focus on time spent in moderate-to-vigorous physical activity (MVPA). Thus, the purpose of this review was to update our existing knowledge of "How many steps/day are enough?", and to inform step-based recommendations consistent with current physical activity guidelines. Normative data indicate that healthy adults typically take between 4,000 and 18,000 steps/day, and that 10,000 steps/day is reasonable for this population, although there are notable "low active populations." Interventions demonstrate incremental increases on the order of 2,000-2,500 steps/day. The results of seven different controlled studies demonstrate that there is a strong relationship between cadence and intensity. Further, despite some inter-individual variation, 100 steps/minute represents a reasonable floor value indicative of moderate intensity walking. Multiplying this cadence by 30 minutes (i.e., typical of a daily recommendation) produces a minimum of 3,000 steps that is best used as a heuristic (i.e., guiding) value, but these steps must be taken over and above habitual activity levels to be a true expression of free-living steps/day that also includes recommendations for minimal amounts of time in MVPA. Computed steps/day translations of time in MVPA that also include estimates of habitual activity levels equate to 7,100 to 11,000 steps/day. A direct estimate of minimal amounts of MVPA accumulated in the course of objectively monitored free-living behaviour is 7,000-8,000 steps/day. A scale that spans a wide range of incremental increases in steps/day and is congruent with public health recognition that "some physical activity is better than none," yet still incorporates step-based translations of recommended amounts of time in MVPA may be useful in research and practice. The full range of users (researchers to practitioners to the general public) of objective monitoring instruments that provide step-based outputs require good reference data and evidence-based recommendations to be able to design effective health messages congruent with public health physical activity guidelines, guide behaviour change, and ultimately measure, track, and interpret steps/day. PMID:21798015

Investigating environmental determinants of diet, physical activity, and overweight among adults in Sao Paulo, Brazil.

PubMed

Jaime, Patricia Constante; Duran, Ana Clara; Sarti, Flávia Mori; Lock, Karen

2011-06-01

There is worldwide recognition that the burden of noncommunicable diseases (NCDs) and obesity-related health problems is rapidly increasing in low- and middle-income countries. Environmental determinants of obesity are likely to differ between countries, particularly in those undergoing rapid socioeconomic and nutrition transitions such as Brazil. This study aims to describe some built environment and local food environment variables and to explore their association with the overweight rate and diet and physical activity area-level aggregated indicators of adults living in the city of Sao Paulo, the largest city in Brazil. This formative study includes an ecological analysis of environmental factors associated with overweight across 31 submunicipalities of the city of Sao Paulo using statistical and spatial analyses. Average prevalence of overweight was 41.69% (95% confidence interval 38.74, 44.64), ranging from 27.14% to 60.75% across the submunicipalities. There was a wide geographical variation of both individual diet and physical activity, and indicators of food and built environments, favoring wealthier areas. After controlling for area socioeconomic status, there was a positive correlation between regular fruits and vegetables (FV) intake and density of FV specialized food markets (r = 0.497; p < 0.001), but no relationship between fast-food restaurant density and overweight prevalence was found. A negative association between overweight prevalence and density of parks and public sport facilities was seen (r = -0.527; p < 0.05). Understanding the relationship between local neighborhood environments and increasing rates of poor diet, physical activity, and obesity is essential in countries undergoing rapid economic and urban development, such as Brazil, in order to provide insights for policies to reduce increasing rates of NCDs and food access and health inequalities.

Unsupervised learning in persistent sensing for target recognition by wireless ad hoc networks of ground-based sensors

NASA Astrophysics Data System (ADS)

Hortos, William S.

2008-04-01

In previous work by the author, effective persistent and pervasive sensing for recognition and tracking of battlefield targets were seen to be achieved, using intelligent algorithms implemented by distributed mobile agents over a composite system of unmanned aerial vehicles (UAVs) for persistence and a wireless network of unattended ground sensors for pervasive coverage of the mission environment. While simulated performance results for the supervised algorithms of the composite system are shown to provide satisfactory target recognition over relatively brief periods of system operation, this performance can degrade by as much as 50% as target dynamics in the environment evolve beyond the period of system operation in which the training data are representative. To overcome this limitation, this paper applies the distributed approach using mobile agents to the network of ground-based wireless sensors alone, without the UAV subsystem, to provide persistent as well as pervasive sensing for target recognition and tracking. The supervised algorithms used in the earlier work are supplanted by unsupervised routines, including competitive-learning neural networks (CLNNs) and new versions of support vector machines (SVMs) for characterization of an unknown target environment. To capture the same physical phenomena from battlefield targets as the composite system, the suite of ground-based sensors can be expanded to include imaging and video capabilities. The spatial density of deployed sensor nodes is increased to allow more precise ground-based location and tracking of detected targets by active nodes. The "swarm" mobile agents enabling WSN intelligence are organized in a three processing stages: detection, recognition and sustained tracking of ground targets. Features formed from the compressed sensor data are down-selected according to an information-theoretic algorithm that reduces redundancy within the feature set, reducing the dimension of samples used in the target recognition and tracking routines. Target tracking is based on simplified versions of Kalman filtration. Accuracy of recognition and tracking of implemented versions of the proposed suite of unsupervised algorithms is somewhat degraded from the ideal. Target recognition and tracking by supervised routines and by unsupervised SVM and CLNN routines in the ground-based WSN is evaluated in simulations using published system values and sensor data from vehicular targets in ground-surveillance scenarios. Results are compared with previously published performance for the system of the ground-based sensor network (GSN) and UAV swarm.

76 FR 22709 - Medicare and Medicaid Programs; Approval of the American Association for Accreditation of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-22

... Surgery Facilities, Inc. for Deeming Authority for Organizations That Provide Outpatient Physical Therapy... Accreditation of Ambulatory Surgery Facilities (AAAASF) for recognition as a national accreditation program for organizations that provide outpatient physical therapy and speech-language pathology services seeking to...

Posture Detection Based on Smart Cushion for Wheelchair Users

PubMed Central

Ma, Congcong; Li, Wenfeng; Gravina, Raffaele; Fortino, Giancarlo

2017-01-01

The postures of wheelchair users can reveal their sitting habit, mood, and even predict health risks such as pressure ulcers or lower back pain. Mining the hidden information of the postures can reveal their wellness and general health conditions. In this paper, a cushion-based posture recognition system is used to process pressure sensor signals for the detection of user’s posture in the wheelchair. The proposed posture detection method is composed of three main steps: data level classification for posture detection, backward selection of sensor configuration, and recognition results compared with previous literature. Five supervised classification techniques—Decision Tree (J48), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Naive Bayes, and k-Nearest Neighbor (k-NN)—are compared in terms of classification accuracy, precision, recall, and F-measure. Results indicate that the J48 classifier provides the highest accuracy compared to other techniques. The backward selection method was used to determine the best sensor deployment configuration of the wheelchair. Several kinds of pressure sensor deployments are compared and our new method of deployment is shown to better detect postures of the wheelchair users. Performance analysis also took into account the Body Mass Index (BMI), useful for evaluating the robustness of the method across individual physical differences. Results show that our proposed sensor deployment is effective, achieving 99.47% posture recognition accuracy. Our proposed method is very competitive for posture recognition and robust in comparison with other former research. Accurate posture detection represents a fundamental basic block to develop several applications, including fatigue estimation and activity level assessment. PMID:28353684

Activity inference for Ambient Intelligence through handling artifacts in a healthcare environment.

PubMed

Martínez-Pérez, Francisco E; González-Fraga, Jose Ángel; Cuevas-Tello, Juan C; Rodríguez, Marcela D

2012-01-01

Human activity inference is not a simple process due to distinct ways of performing it. Our proposal presents the SCAN framework for activity inference. SCAN is divided into three modules: (1) artifact recognition, (2) activity inference, and (3) activity representation, integrating three important elements of Ambient Intelligence (AmI) (artifact-behavior modeling, event interpretation and context extraction). The framework extends the roaming beat (RB) concept by obtaining the representation using three kinds of technologies for activity inference. The RB is based on both analysis and recognition from artifact behavior for activity inference. A practical case is shown in a nursing home where a system affording 91.35% effectiveness was implemented in situ. Three examples are shown using RB representation for activity representation. Framework description, RB description and CALog system overcome distinct problems such as the feasibility to implement AmI systems, and to show the feasibility for accomplishing the challenges related to activity recognition based on artifact recognition. We discuss how the use of RBs might positively impact the problems faced by designers and developers for recovering information in an easier manner and thus they can develop tools focused on the user.

Activity Inference for Ambient Intelligence Through Handling Artifacts in a Healthcare Environment

PubMed Central

Martínez-Pérez, Francisco E.; González-Fraga, Jose Ángel; Cuevas-Tello, Juan C.; Rodríguez, Marcela D.

2012-01-01

Human activity inference is not a simple process due to distinct ways of performing it. Our proposal presents the SCAN framework for activity inference. SCAN is divided into three modules: (1) artifact recognition, (2) activity inference, and (3) activity representation, integrating three important elements of Ambient Intelligence (AmI) (artifact-behavior modeling, event interpretation and context extraction). The framework extends the roaming beat (RB) concept by obtaining the representation using three kinds of technologies for activity inference. The RB is based on both analysis and recognition from artifact behavior for activity inference. A practical case is shown in a nursing home where a system affording 91.35% effectiveness was implemented in situ. Three examples are shown using RB representation for activity representation. Framework description, RB description and CALog system overcome distinct problems such as the feasibility to implement AmI systems, and to show the feasibility for accomplishing the challenges related to activity recognition based on artifact recognition. We discuss how the use of RBs might positively impact the problems faced by designers and developers for recovering information in an easier manner and thus they can develop tools focused on the user. PMID:22368512

Characterizing the spatio-temporal dynamics of the neural events occurring prior to and up to overt recognition of famous faces.

PubMed

Jemel, Boutheina; Schuller, Anne-Marie; Goffaux, Valérie

2010-10-01

Although it is generally acknowledged that familiar face recognition is fast, mandatory, and proceeds outside conscious control, it is still unclear whether processes leading to familiar face recognition occur in a linear (i.e., gradual) or a nonlinear (i.e., all-or-none) manner. To test these two alternative accounts, we recorded scalp ERPs while participants indicated whether they recognize as familiar the faces of famous and unfamiliar persons gradually revealed in a descending sequence of frames, from the noisier to the least noisy. This presentation procedure allowed us to characterize the changes in scalp ERP responses occurring prior to and up to overt recognition. Our main finding is that gradual and all-or-none processes are possibly involved during overt recognition of familiar faces. Although the N170 and the N250 face-sensitive responses displayed an abrupt activity change at the moment of overt recognition of famous faces, later ERPs encompassing the N400 and late positive component exhibited an incremental increase in amplitude as the point of recognition approached. In addition, famous faces that were not overtly recognized at one trial before recognition elicited larger ERP potentials than unfamiliar faces, probably reflecting a covert recognition process. Overall, these findings present evidence that recognition of familiar faces implicates spatio-temporally complex neural processes exhibiting differential pattern activity changes as a function of recognition state.

A Joint Gaussian Process Model for Active Visual Recognition with Expertise Estimation in Crowdsourcing

PubMed Central

Long, Chengjiang; Hua, Gang; Kapoor, Ashish

2015-01-01

We present a noise resilient probabilistic model for active learning of a Gaussian process classifier from crowds, i.e., a set of noisy labelers. It explicitly models both the overall label noise and the expertise level of each individual labeler with two levels of flip models. Expectation propagation is adopted for efficient approximate Bayesian inference of our probabilistic model for classification, based on which, a generalized EM algorithm is derived to estimate both the global label noise and the expertise of each individual labeler. The probabilistic nature of our model immediately allows the adoption of the prediction entropy for active selection of data samples to be labeled, and active selection of high quality labelers based on their estimated expertise to label the data. We apply the proposed model for four visual recognition tasks, i.e., object category recognition, multi-modal activity recognition, gender recognition, and fine-grained classification, on four datasets with real crowd-sourced labels from the Amazon Mechanical Turk. The experiments clearly demonstrate the efficacy of the proposed model. In addition, we extend the proposed model with the Predictive Active Set Selection Method to speed up the active learning system, whose efficacy is verified by conducting experiments on the first three datasets. The results show our extended model can not only preserve a higher accuracy, but also achieve a higher efficiency. PMID:26924892

Recognition and reading aloud of kana and kanji word: an fMRI study.

PubMed

Ino, Tadashi; Nakai, Ryusuke; Azuma, Takashi; Kimura, Toru; Fukuyama, Hidenao

2009-03-16

It has been proposed that different brain regions are recruited for processing two Japanese writing systems, namely, kanji (morphograms) and kana (syllabograms). However, this difference may depend upon what type of word was used and also on what type of task was performed. Using fMRI, we investigated brain activation for processing kanji and kana words with similar high familiarity in two tasks: word recognition and reading aloud. During both tasks, words and non-words were presented side by side, and the subjects were required to press a button corresponding to the real word in the word recognition task and were required to read aloud the real word in the reading aloud task. Brain activations were similar between kanji and kana during reading aloud task, whereas during word recognition task in which accurate identification and selection were required, kanji relative to kana activated regions of bilateral frontal, parietal and occipitotemporal cortices, all of which were related mainly to visual word-form analysis and visuospatial attention. Concerning the difference of brain activity between two tasks, differential activation was found only in the regions associated with task-specific sensorimotor processing for kana, whereas visuospatial attention network also showed greater activation during word recognition task than during reading aloud task for kanji. We conclude that the differences in brain activation between kanji and kana depend on the interaction between the script characteristics and the task demands.

Codebook-based electrooculography data analysis towards cognitive activity recognition.

PubMed

Lagodzinski, P; Shirahama, K; Grzegorzek, M

2018-04-01

With the advancement in mobile/wearable technology, people started to use a variety of sensing devices to track their daily activities as well as health and fitness conditions in order to improve the quality of life. This work addresses an idea of eye movement analysis, which due to the strong correlation with cognitive tasks can be successfully utilized in activity recognition. Eye movements are recorded using an electrooculographic (EOG) system built into the frames of glasses, which can be worn more unobtrusively and comfortably than other devices. Since the obtained information is low-level sensor data expressed as a sequence representing values in constant intervals (100 Hz), the cognitive activity recognition problem is formulated as sequence classification. However, it is unclear what kind of features are useful for accurate cognitive activity recognition. Thus, a machine learning algorithm like a codebook approach is applied, which instead of focusing on feature engineering is using a distribution of characteristic subsequences (codewords) to describe sequences of recorded EOG data, where the codewords are obtained by clustering a large number of subsequences. Further, statistical analysis of the codeword distribution results in discovering features which are characteristic to a certain activity class. Experimental results demonstrate good accuracy of the codebook-based cognitive activity recognition reflecting the effective usage of the codewords. Copyright © 2017 Elsevier Ltd. All rights reserved.

Alterations in Resting-State Activity Relate to Performance in a Verbal Recognition Task

PubMed Central

López Zunini, Rocío A.; Thivierge, Jean-Philippe; Kousaie, Shanna; Sheppard, Christine; Taler, Vanessa

2013-01-01

In the brain, resting-state activity refers to non-random patterns of intrinsic activity occurring when participants are not actively engaged in a task. We monitored resting-state activity using electroencephalogram (EEG) both before and after a verbal recognition task. We show a strong positive correlation between accuracy in verbal recognition and pre-task resting-state alpha power at posterior sites. We further characterized this effect by examining resting-state post-task activity. We found marked alterations in resting-state alpha power when comparing pre- and post-task periods, with more pronounced alterations in participants that attained higher task accuracy. These findings support a dynamical view of cognitive processes where patterns of ongoing brain activity can facilitate –or interfere– with optimal task performance. PMID:23785436

Collegial Activity Learning between Heterogeneous Sensors.

PubMed

Feuz, Kyle D; Cook, Diane J

2017-11-01

Activity recognition algorithms have matured and become more ubiquitous in recent years. However, these algorithms are typically customized for a particular sensor platform. In this paper we introduce PECO, a Personalized activity ECOsystem, that transfers learned activity information seamlessly between sensor platforms in real time so that any available sensor can continue to track activities without requiring its own extensive labeled training data. We introduce a multi-view transfer learning algorithm that facilitates this information handoff between sensor platforms and provide theoretical performance bounds for the algorithm. In addition, we empirically evaluate PECO using datasets that utilize heterogeneous sensor platforms to perform activity recognition. These results indicate that not only can activity recognition algorithms transfer important information to new sensor platforms, but any number of platforms can work together as colleagues to boost performance.

Oxytocin, vasopressin and estrogen receptor gene expression in relation to social recognition in female mice

PubMed Central

Clipperton-Allen, Amy E.; Lee, Anna W.; Reyes, Anny; Devidze, Nino; Phan, Anna; Pfaff, Donald W.; Choleris, Elena

2012-01-01

Inter- and intra-species differences in social behavior and recognition-related hormones and receptors suggest that different distribution and/or expression patterns may relate to social recognition. We used qRT-PCR to investigate naturally occurring differences in expression of estrogen receptor-alpha (ERα), ER-beta (ERβ), progesterone receptor (PR), oxytocin (OT) and receptor, and vasopressin (AVP) and receptors in proestrous female mice. Following four 5 min exposures to the same two conspecifics, one was replaced with a novel mouse in the final trial (T5). Gene expression was examined in mice showing high (85–100%) and low (40–60%) social recognition scores (i.e., preferential novel mouse investigation in T5) in eight socially-relevant brain regions. Results supported OT and AVP involvement in social recognition, and suggest that in the medial preoptic area, increased OT and AVP mRNA, together with ERα and ERβ gene activation, relate to improved social recognition. Initial social investigation correlated with ERs, PR and OTR in the dorsolateral septum, suggesting that these receptors may modulate social interest without affecting social recognition. Finally, increased lateral amygdala gene activation in the LR mice may be associated with general learning impairments, while decreased lateral amygdala activity may indicate more efficient cognitive mechanisms in the HR mice. PMID:22079582

Towards Smart Homes Using Low Level Sensory Data

PubMed Central

Khattak, Asad Masood; Truc, Phan Tran Ho; Hung, Le Xuan; Vinh, La The; Dang, Viet-Hung; Guan, Donghai; Pervez, Zeeshan; Han, Manhyung; Lee, Sungyoung; Lee, Young-Koo

2011-01-01

Ubiquitous Life Care (u-Life care) is receiving attention because it provides high quality and low cost care services. To provide spontaneous and robust healthcare services, knowledge of a patient’s real-time daily life activities is required. Context information with real-time daily life activities can help to provide better services and to improve healthcare delivery. The performance and accuracy of existing life care systems is not reliable, even with a limited number of services. This paper presents a Human Activity Recognition Engine (HARE) that monitors human health as well as activities using heterogeneous sensor technology and processes these activities intelligently on a Cloud platform for providing improved care at low cost. We focus on activity recognition using video-based, wearable sensor-based, and location-based activity recognition engines and then use intelligent processing to analyze the context of the activities performed. The experimental results of all the components showed good accuracy against existing techniques. The system is deployed on Cloud for Alzheimer’s disease patients (as a case study) with four activity recognition engines to identify low level activity from the raw data captured by sensors. These are then manipulated using ontology to infer higher level activities and make decisions about a patient’s activity using patient profile information and customized rules. PMID:22247682

Exposure to childhood adversity and deficits in emotion recognition: results from a large, population-based sample.

PubMed

Dunn, Erin C; Crawford, Katherine M; Soare, Thomas W; Button, Katherine S; Raffeld, Miriam R; Smith, Andrew D A C; Penton-Voak, Ian S; Munafò, Marcus R

2018-03-07

Emotion recognition skills are essential for social communication. Deficits in these skills have been implicated in mental disorders. Prior studies of clinical and high-risk samples have consistently shown that children exposed to adversity are more likely than their unexposed peers to have emotion recognition skills deficits. However, only one population-based study has examined this association. We analyzed data from children participating in the Avon Longitudinal Study of Parents and Children, a prospective birth cohort (n = 6,506). We examined the association between eight adversities, assessed repeatedly from birth to age 8 (caregiver physical or emotional abuse; sexual or physical abuse; maternal psychopathology; one adult in the household; family instability; financial stress; parent legal problems; neighborhood disadvantage) and the ability to recognize facial displays of emotion measured using the faces subtest of the Diagnostic Assessment of Non-Verbal Accuracy (DANVA) at age 8.5 years. In addition to examining the role of exposure (vs. nonexposure) to each type of adversity, we also evaluated the role of the timing, duration, and recency of each adversity using a Least Angle Regression variable selection procedure. Over three-quarters of the sample experienced at least one adversity. We found no evidence to support an association between emotion recognition deficits and previous exposure to adversity, either in terms of total lifetime exposure, timing, duration, or recency, or when stratifying by sex. Results from the largest population-based sample suggest that even extreme forms of adversity are unrelated to emotion recognition deficits as measured by the DANVA, suggesting the possible immutability of emotion recognition in the general population. These findings emphasize the importance of population-based studies to generate generalizable results. © 2018 Association for Child and Adolescent Mental Health.

Physical signals for protein-DNA recognition

NASA Astrophysics Data System (ADS)

Cao, Xiao-Qin; Zeng, Jia; Yan, Hong

2009-09-01

This paper discovers consensus physical signals around eukaryotic splice sites, transcription start sites, and replication origin start and end sites on a genome-wide scale based on their DNA flexibility profiles calculated by three different flexibility models. These salient physical signals are localized highly rigid and flexible DNAs, which may play important roles in protein-DNA recognition by the sliding search mechanism. The found physical signals lead us to a detailed hypothetical view of the search process in which a DNA-binding protein first finds a genomic region close to the target site from an arbitrary starting location by three-dimensional (3D) hopping and intersegment transfer mechanisms for long distances, and subsequently uses the one-dimensional (1D) sliding mechanism facilitated by the localized highly rigid DNAs to accurately locate the target flexible binding site within 30 bp (base pair) short distances. Guided by these physical signals, DNA-binding proteins rapidly search the entire genome to recognize a specific target site from the 3D to 1D pathway. Our findings also show that current promoter prediction programs (PPPs) based on DNA physical properties may suffer from lots of false positives because other functional sites such as splice sites and replication origins have similar physical signals as promoters do.

Robust Indoor Human Activity Recognition Using Wireless Signals.

PubMed

Wang, Yi; Jiang, Xinli; Cao, Rongyu; Wang, Xiyang

2015-07-15

Wireless signals-based activity detection and recognition technology may be complementary to the existing vision-based methods, especially under the circumstance of occlusions, viewpoint change, complex background, lighting condition change, and so on. This paper explores the properties of the channel state information (CSI) of Wi-Fi signals, and presents a robust indoor daily human activity recognition framework with only one pair of transmission points (TP) and access points (AP). First of all, some indoor human actions are selected as primitive actions forming a training set. Then, an online filtering method is designed to make actions' CSI curves smooth and allow them to contain enough pattern information. Each primitive action pattern can be segmented from the outliers of its multi-input multi-output (MIMO) signals by a proposed segmentation method. Lastly, in online activities recognition, by selecting proper features and Support Vector Machine (SVM) based multi-classification, activities constituted by primitive actions can be recognized insensitive to the locations, orientations, and speeds.

Fast and Famous: Looking for the Fastest Speed at Which a Face Can be Recognized

PubMed Central

Barragan-Jason, Gladys; Besson, Gabriel; Ceccaldi, Mathieu; Barbeau, Emmanuel J.

2012-01-01

Face recognition is supposed to be fast. However, the actual speed at which faces can be recognized remains unknown. To address this issue, we report two experiments run with speed constraints. In both experiments, famous faces had to be recognized among unknown ones using a large set of stimuli to prevent pre-activation of features which would speed up recognition. In the first experiment (31 participants), recognition of famous faces was investigated using a rapid go/no-go task. In the second experiment, 101 participants performed a highly time constrained recognition task using the Speed and Accuracy Boosting procedure. Results indicate that the fastest speed at which a face can be recognized is around 360–390 ms. Such latencies are about 100 ms longer than the latencies recorded in similar tasks in which subjects have to detect faces among other stimuli. We discuss which model of activation of the visual ventral stream could account for such latencies. These latencies are not consistent with a purely feed-forward pass of activity throughout the visual ventral stream. An alternative is that face recognition relies on the core network underlying face processing identified in fMRI studies (OFA, FFA, and pSTS) and reentrant loops to refine face representation. However, the model of activation favored is that of an activation of the whole visual ventral stream up to anterior areas, such as the perirhinal cortex, combined with parallel and feed-back processes. Further studies are needed to assess which of these three models of activation can best account for face recognition. PMID:23460051

Suicidal ideation and its determinants in Korean adults: The role of physical activity and functional limitations.

PubMed

Park, S M

2015-01-01

The recognition of suicide as a major public health problem has suggested the need to identify risk factors that have implications for preventive intervention. In the suicidal process, suicidal ideation is a key stage in the pathway leading to eventual suicide. This study investigated the influence of physical activity and functional limitations on suicidal ideation among young and middle-aged adults in a high suicidal society. Data for the current study were obtained from the Fourth Korea National Health and Nutrition Examination Survey 2007-2009 (KNHANES), a cross-sectional study conducted by the Korea Centers for Disease Control and Prevention. The survey conducted face-to-face interviews with young adults (n = 2326) and middle-aged adults (n = 3396). Using multivariate logistic regression analysis, the relationship of physical activity and functional limitations with suicidal ideation in young and middle-aged adults was assessed. A notable outcome was that the absence of a regular walking was correlated with increased suicidal ideation in middle-aged women. The other major finding was that young women and middle-aged adults with functional limitations had a high rate of suicidal thoughts. Multiple intervention approaches, including informational, social and behavioural approaches, are needed to promote regular walking in middle-aged women. For instance, mass media campaigns, community walking groups and individually adapted health behaviour modification may provide opportunities for positive intervention. Additionally, another important public health implication from these findings is the need for a suicide-intervention support system that includes screening for suicide risk in healthcare settings, especially among young women with physical limitations.

Psychiatric Nursing's Role in Child Abuse: Prevention, Recognition, and Treatment.

PubMed

Ellington, Erin

2017-11-01

Child abuse affects hundreds of thousands of children in the United States each year. The effects from maltreatment extend beyond the physical injuries-the lasting effects on the child's mental health can be lifelong. Psychiatric nurses have a vital role to play in the prevention, recognition, and treatment of child abuse. [Journal of Psychosocial Nursing and Mental Health Services, 55(11), 16-20.]. Copyright 2017, SLACK Incorporated.

Recognition-Based Physical Response to Facilitate EFL Learning

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Shih, Timothy K.; Yeh, Shih-Ching; Chou, Ke-Chien; Ma, Zhao-Heng; Sommool, Worapot

2014-01-01

This study, based on total physical response and cognitive psychology, proposed a Kinesthetic English Learning System (KELS), which utilized Microsoft's Kinect technology to build kinesthetic interaction with life-related contexts in English. A subject test with 39 tenth-grade students was conducted following empirical research method in order to…

The Fair Play Game: Promoting Social Skills in Physical Education

ERIC Educational Resources Information Center

Vidoni, Carla; Ulman, Jerome D.

2012-01-01

The implementation of social skills into teaching helps students achieve such important affective outcomes as peer recognition or popularity, respect for others, acceptance of rules, pro-social values, communication skills, and positive social interactions. Within physical education, many professionals believe that students who engage in games and…

Attention and Encoding in Physics Learning and Problem Solving

ERIC Educational Resources Information Center

Feil, Adam John

2009-01-01

This dissertation presents several studies designed to probe the mental representations that physics experts and novices form when interacting with typical instructional materials, such as diagrams and problem statements. By using recognition tasks and a change detection task, the mental representations of experts and novices are studied in a more…

Aspects of the Cognitive Model of Physics Problem Solving.

ERIC Educational Resources Information Center

Brekke, Stewart E.

Various aspects of the cognitive model of physics problem solving are discussed in detail including relevant cues, encoding, memory, and input stimuli. The learning process involved in the recognition of familiar and non-familiar sensory stimuli is highlighted. Its four components include selection, acquisition, construction, and integration. The…

What older adolescents expect from physical activity: Implicit cognitions regarding health and appearance outcomes.

PubMed

McFadden, K; Berry, T R; McHugh, T F; Rodgers, W M

2018-04-01

To explore older adolescents' reflective and impulsive thoughts about health- and social/appearance-related physical activity (PA) outcomes and investigate how those thoughts relate to their PA behavior. One hundred and forty-four undergraduate students (109 women; 35 men) aged 17-19 years (M = 18.11, SD = 0.65) participated in this study in October 2015. Participants completed a Go/No-go Association Task that assessed automaticity of associations between PA words and either health outcomes or social/appearance outcomes. Questionnaires assessing PA behavior, attitudes, outcome expectations, and body image were also completed. Participants demonstrated a positive automatic association between PA and social/appearance outcomes, F(1, 136) = 4.403, p < .05, η 2 = .031, but they showed no difference in their associations between PA and desirable or undesirable health outcomes, F(1, 136) = 2.405, p = .123, η 2 = .017. Older adolescents implicitly attend to the social/appearance outcomes of PA more than potential health outcomes, indicating that social recognition and a desirable physique may be the key PA motivators for adolescents.

[From "physical idealist" to "freedom fighter". The change in the perception of Carl Friedrich von Weizsäcker in the DDR - exemplified by honorary doctorate and the Leipzig Colloquium 1987/88].

PubMed

Ackermann, Peter

2014-01-01

This article draws a representative picture of the official public perception of Carl Friedrich von Weizsäcker in the GDR. In the beginning Weizsäcker served as a classic example of a successful scientist with bourgeois philosophical ideas. So he was often a target of philosophical criticism. This changed with Weizsäcker's activities in peace studies, and the official GDR made an attempt to monopolize him. This could be seen, for example, in connection with his honorary doctorate awarded by the University of Leipzig in 1987 and with the scientific colloquium in 1988. From these examples we can also see that efforts took place to change the focus towards his physical und philosophical achievements. Weizsäcker's official recognition was also helpful for other activities in which he played a leading role. The article looks behind the scenes of a part of the academic machinery in the GDR. It shows that CFvW was an eminent stimulator also in the GDR.

Evaluation of a Home Biomonitoring Autonomous Mobile Robot.

PubMed

Dorronzoro Zubiete, Enrique; Nakahata, Keigo; Imamoglu, Nevrez; Sekine, Masashi; Sun, Guanghao; Gomez, Isabel; Yu, Wenwei

2016-01-01

Increasing population age demands more services in healthcare domain. It has been shown that mobile robots could be a potential solution to home biomonitoring for the elderly. Through our previous studies, a mobile robot system that is able to track a subject and identify his daily living activities has been developed. However, the system has not been tested in any home living scenarios. In this study we did a series of experiments to investigate the accuracy of activity recognition of the mobile robot in a home living scenario. The daily activities tested in the evaluation experiment include watching TV and sleeping. A dataset recorded by a distributed distance-measuring sensor network was used as a reference to the activity recognition results. It was shown that the accuracy is not consistent for all the activities; that is, mobile robot could achieve a high success rate in some activities but a poor success rate in others. It was found that the observation position of the mobile robot and subject surroundings have high impact on the accuracy of the activity recognition, due to the variability of the home living daily activities and their transitional process. The possibility of improvement of recognition accuracy has been shown too.

Evaluating Health Co-Benefits of Climate Change Mitigation in Urban Mobility

PubMed Central

Wolkinger, Brigitte; Weisz, Ulli; Hutter, Hans-Peter; Delcour, Jennifer; Griebler, Robert; Mittelbach, Bernhard; Maier, Philipp; Reifeltshammer, Raphael

2018-01-01

There is growing recognition that implementation of low-carbon policies in urban passenger transport has near-term health co-benefits through increased physical activity and improved air quality. Nevertheless, co-benefits and related cost reductions are often not taken into account in decision processes, likely because they are not easy to capture. In an interdisciplinary multi-model approach we address this gap, investigating the co-benefits resulting from increased physical activity and improved air quality due to climate mitigation policies for three urban areas. Additionally we take a (macro-)economic perspective, since that is the ultimate interest of policy-makers. Methodologically, we link a transport modelling tool, a transport emission model, an emission dispersion model, a health model and a macroeconomic Computable General Equilibrium (CGE) model to analyze three climate change mitigation scenarios. We show that higher levels of physical exercise and reduced exposure to pollutants due to mitigation measures substantially decrease morbidity and mortality. Expenditures are mainly born by the public sector but are mostly offset by the emerging co-benefits. Our macroeconomic results indicate a strong positive welfare effect, yet with slightly negative GDP and employment effects. We conclude that considering economic co-benefits of climate change mitigation policies in urban mobility can be put forward as a forceful argument for policy makers to take action. PMID:29710784

Evaluating Health Co-Benefits of Climate Change Mitigation in Urban Mobility.

PubMed

Wolkinger, Brigitte; Haas, Willi; Bachner, Gabriel; Weisz, Ulli; Steininger, Karl; Hutter, Hans-Peter; Delcour, Jennifer; Griebler, Robert; Mittelbach, Bernhard; Maier, Philipp; Reifeltshammer, Raphael

2018-04-28

There is growing recognition that implementation of low-carbon policies in urban passenger transport has near-term health co-benefits through increased physical activity and improved air quality. Nevertheless, co-benefits and related cost reductions are often not taken into account in decision processes, likely because they are not easy to capture. In an interdisciplinary multi-model approach we address this gap, investigating the co-benefits resulting from increased physical activity and improved air quality due to climate mitigation policies for three urban areas. Additionally we take a (macro-)economic perspective, since that is the ultimate interest of policy-makers. Methodologically, we link a transport modelling tool, a transport emission model, an emission dispersion model, a health model and a macroeconomic Computable General Equilibrium (CGE) model to analyze three climate change mitigation scenarios. We show that higher levels of physical exercise and reduced exposure to pollutants due to mitigation measures substantially decrease morbidity and mortality. Expenditures are mainly born by the public sector but are mostly offset by the emerging co-benefits. Our macroeconomic results indicate a strong positive welfare effect, yet with slightly negative GDP and employment effects. We conclude that considering economic co-benefits of climate change mitigation policies in urban mobility can be put forward as a forceful argument for policy makers to take action.

Social Disorder in Adults with Type 2 Diabetes: Building on Race, Place, and Poverty

PubMed Central

Steve, Shantell L.; Tung, Elizabeth L.; Schlichtman, John J.; Peek, Monica E.

2016-01-01

The recent resurgence of social and civic disquiet in the USA has contributed to increasing recognition that social conditions are meaningfully connected to disease and death. As a “lifestyle disease,” control of diabetes requires modifications to daily activities, including healthy dietary practices, regular physical activity, and adherence to treatment regimens. One’s ability to develop the healthy practices necessary to prevent or control type 2 diabetes may be influenced by a context of social disorder, the disruptive social and economic conditions that influence daily activity and, consequently, health status. In this paper, we report on our narrative review of the literature that explores the associations between social disorder and diabetes-related health outcomes within vulnerable communities. We also propose a multilevel ecosocial model for conceptualizing social disorder, specifically focusing on its role in racial disparities and its pathways to mediating diabetes outcomes. PMID:27319322

Parallel processing by cortical inhibition enables context-dependent behavior.

PubMed

Kuchibhotla, Kishore V; Gill, Jonathan V; Lindsay, Grace W; Papadoyannis, Eleni S; Field, Rachel E; Sten, Tom A Hindmarsh; Miller, Kenneth D; Froemke, Robert C

2017-01-01

Physical features of sensory stimuli are fixed, but sensory perception is context dependent. The precise mechanisms that govern contextual modulation remain unknown. Here, we trained mice to switch between two contexts: passively listening to pure tones and performing a recognition task for the same stimuli. Two-photon imaging showed that many excitatory neurons in auditory cortex were suppressed during behavior, while some cells became more active. Whole-cell recordings showed that excitatory inputs were affected only modestly by context, but inhibition was more sensitive, with PV + , SOM + , and VIP + interneurons balancing inhibition and disinhibition within the network. Cholinergic modulation was involved in context switching, with cholinergic axons increasing activity during behavior and directly depolarizing inhibitory cells. Network modeling captured these findings, but only when modulation coincidently drove all three interneuron subtypes, ruling out either inhibition or disinhibition alone as sole mechanism for active engagement. Parallel processing of cholinergic modulation by cortical interneurons therefore enables context-dependent behavior.

RIG-I in RNA virus recognition

PubMed Central

Kell, Alison M.; Gale, Michael

2015-01-01

Antiviral immunity is initiated upon host recognition of viral products via non-self molecular patterns known as pathogen-associated molecular patterns (PAMPs). Such recognition initiates signaling cascades that induce intracellular innate immune defenses and an inflammatory response that facilitates development of the acquired immune response. The retinoic acid-inducible gene I (RIG-I) and the RIG-I-like receptor (RLR) protein family are key cytoplasmic pathogen recognition receptors that are implicated in the recognition of viruses across genera and virus families, including functioning as major sensors of RNA viruses, and promoting recognition of some DNA viruses. RIG-I, the charter member of the RLR family, is activated upon binding to PAMP RNA. Activated RIG-I signals by interacting with the adapter protein MAVS leading to a signaling cascade that activates the transcription factors IRF3 and NF-κB. These actions induce the expression of antiviral gene products and the production of type I and III interferons that lead to an antiviral state in the infected cell and surrounding tissue. RIG-I signaling is essential for the control of infection by many RNA viruses. Recently, RIG-I crosstalk with other pathogen recognition receptors and components of the inflammasome has been described. In this review, we discuss the current knowledge regarding the role of RIG-I in recognition of a variety of virus families and its role in programming the adaptive immune response through cross-talk with parallel arms of the innate immune system, including how RIG-I can be leveraged for antiviral therapy. PMID:25749629

IDEEA activity monitor: validity of activity recognition for lying, reclining, sitting and standing.

PubMed

Jiang, Yuyu; Larson, Janet L

2013-03-01

Recent evidence demonstrates the independent negative effects of sedentary behavior on health, but there are few objective measures of sedentary behavior. Most instruments measure physical activity and are not validated as measures of sedentary behavior. The purpose of this study was to evaluate the validity of the IDEEA system's measures of sedentary and low-intensity physical activities: lying, reclining, sitting and standing. Thirty subjects, 14 men and 16 women, aged 23 to 77 years, body mass index (BMI) between 18 to 34 kg/m(2), participated in the study. IDEEA measures were compared to direct observation for 27 activities: 10 lying in bed, 3 lying on a sofa, 1 reclining in a lawn chair, 10 sitting and 3 standing. Two measures are reported, the percentage of activities accurately identified and the percentage of monitored time that was accurately labeled by the IDEEA system for all subjects. A total of 91.6% of all observed activities were accurately identified and 92.4% of the total monitored time was accurately labeled. The IDEEA system did not accurately differentiate between lying and reclining so the two activities were combined for calculating accuracy. Using this approach the IDEEA system accurately identified 96% of sitting activities for a total of 97% of the monitored sitting time, 99% and 99% for standing, 87% and 88% for lying in bed, 87% and 88% for lying on the sofa, and 83% and 83% for reclining on a lawn chair. We conclude that the IDEEA system accurately recognizes sitting and standing positions, but it is less accurate in identifying lying and reclining positions. We recommend combining the lying and reclining activities to improve accuracy. The IDEEA system enables researchers to monitor lying, reclining, sitting and standing with a reasonable level of accuracy and has the potential to advance the science of sedentary behaviors and low-intensity physical activities.

Recognition and classification of oscillatory patterns of electric brain activity using artificial neural network approach

NASA Astrophysics Data System (ADS)

Pchelintseva, Svetlana V.; Runnova, Anastasia E.; Musatov, Vyacheslav Yu.; Hramov, Alexander E.

2017-03-01

In the paper we study the problem of recognition type of the observed object, depending on the generated pattern and the registered EEG data. EEG recorded at the time of displaying cube Necker characterizes appropriate state of brain activity. As an image we use bistable image Necker cube. Subject selects the type of cube and interpret it either as aleft cube or as the right cube. To solve the problem of recognition, we use artificial neural networks. In our paper to create a classifier we have considered a multilayer perceptron. We examine the structure of the artificial neural network and define cubes recognition accuracy.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

Evaluation of impairment of the upper extremity.

PubMed

Blair, S J; McCormick, E; Bear-Lehman, J; Fess, E E; Rader, E

1987-08-01

Evaluation of impairment of the upper extremity is the product of a team effort by the physician, occupational therapist, physical therapist, and rehabilitation counselor. A careful recording of the anatomic impairment should be made because this is critical in determining the subsequent functional activities of the extremity. The measurement criteria for clinical and functional evaluation includes condition assessment instruments. Some assess the neurovascular system, others assess movements including the monitoring of articular motion and musculotendinous function. Sensibility assessment instruments measure sympathetic response and detect single joint stimulus, discrimination, quantification, and recognition abilities. A detailed description of each assessment is recorded and physical capacity evaluation is only one component of the entire vocational evaluation. This evaluation answers questions regarding the injured worker's ability to return to his previous job. The work simulator is a useful instrument that allows rehabilitation and testing of the injured upper extremity. Job site evaluation includes assessment criteria for work performance, work behavior, and work environment.

Implementation study of wearable sensors for activity recognition systems.

PubMed

Rezaie, Hamed; Ghassemian, Mona

2015-08-01

This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely 'stream-based', 'feature-based' and 'threshold-based' scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency.

Neural correlates of social odor recognition and the representation of individual distinctive social odors within entorhinal cortex and ventral subiculum.

PubMed

Petrulis, A; Alvarez, P; Eichenbaum, H

2005-01-01

Recognition of individual conspecifics is important for social behavior and requires the formation of memories for individually distinctive social signals. Individual recognition is often mediated by olfactory cues in mammals, especially nocturnal rodents such as golden hamsters. In hamsters, this form of recognition requires main olfactory system input to the lateral entorhinal cortex (LEnt). Here, we tested whether neurons in LEnt and the nearby ventral subiculum (VS) would show cellular correlates of this natural form of recognition memory. Two hundred ninety single neurons were recorded from both superficial (SE) and deep layers of LEnt (DE) and VS while male hamsters investigated volatile odorants from female vaginal secretions. Many neurons encoded differences between female's odors with many discriminating between odors from different individual females but not between different odor samples from the same female. Other neurons discriminated between odor samples from one female and generalized across collections from other females. LEnt and VS neurons showed enhanced or suppressed cellular activity during investigation of previously presented odors and in response to novel odors. A majority of SE neurons decreased firing to odor repetition and increased activity to novel odors. In contrast, DE neurons often showed suppressed activity in response to novel odors. Thus, neurons in LEnt and VS of male hamsters encode information that is critical for the identification and recognition of individual females by odor cues. This study reveals cellular mechanisms in LEnt and VS that may mediate a natural form of recognition memory in hamsters. These neuronal responses were similar to those observed in rats and monkeys during performance in standard recognition memory tasks. Consequently, the present data extend our understanding of the cellular basis for recognition memory and suggest that individual recognition requires similar neural mechanisms as those employed in laboratory tests of recognition memory.

Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments.

PubMed

Baldominos, Alejandro; Saez, Yago; Isasi, Pedro

2018-04-23

Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures.

Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments

PubMed Central

2018-01-01

Human activity recognition is a challenging problem for context-aware systems and applications. It is gaining interest due to the ubiquity of different sensor sources, wearable smart objects, ambient sensors, etc. This task is usually approached as a supervised machine learning problem, where a label is to be predicted given some input data, such as the signals retrieved from different sensors. For tackling the human activity recognition problem in sensor network environments, in this paper we propose the use of deep learning (convolutional neural networks) to perform activity recognition using the publicly available OPPORTUNITY dataset. Instead of manually choosing a suitable topology, we will let an evolutionary algorithm design the optimal topology in order to maximize the classification F1 score. After that, we will also explore the performance of committees of the models resulting from the evolutionary process. Results analysis indicates that the proposed model was able to perform activity recognition within a heterogeneous sensor network environment, achieving very high accuracies when tested with new sensor data. Based on all conducted experiments, the proposed neuroevolutionary system has proved to be able to systematically find a classification model which is capable of outperforming previous results reported in the state-of-the-art, showing that this approach is useful and improves upon previously manually-designed architectures. PMID:29690587

Evaluation of the Good Start Program: a healthy eating and physical activity intervention for Maori and Pacific Islander children living in Queensland, Australia.

PubMed

Mihrshahi, Seema; Vaughan, Lisa; Fa'avale, Nicola; De Silva Weliange, Shreenika; Manu-Sione, Inez; Schubert, Lisa

2017-01-13

Reducing the prevalence of obesity and chronic disease are important priorities. Maori and Pacific Islander communities living in Australia have higher rates of obesity and chronic disease than the wider Australian population. This study aims to assess the effectiveness of the Good Start program, which aims to improve knowledge, attitudes and practices related to healthy eating and physical activity amongst Maori and Pacific Islander communities living in Queensland. The intervention was delivered to children aged 6-19 years (N = 375) in schools by multicultural health workers. Class activities focused on one message each term related to healthy eating and physical activity using methods such as cooking sessions and cultural dance. The evaluation approach was a quantitative uncontrolled pre-post design. Data were collected each term pre- and post-intervention using a short questionnaire. There were significant increases in knowledge of correct servings of fruit and vegetables, knowledge of sugar and caffeine content of common sugar-sweetened drinks, recognition of the consequences of marketing and upsizing, and the importance of controlling portion size (all P < 0.05). There was also increases in knowledge of physical activity recommendations (P < 0.001), as well as the importance of physical activity for preventing heart disease (P < 0.001) and improving self-esteem (P < 0.001). In terms of attitudes, there were significant improvements in some attitudes to vegetables (P = 0.02), and sugar-sweetened drinks (P < 0.05). In terms of practices and behaviours, although the reported intake of vegetables increased significantly (P < 0.001), the proportion of children eating discretionary foods regularly did not change significantly, suggesting that modifying the program with an increased emphasis on reducing intake of junk food may be beneficial. The study has shown that the Good Start Program was effective in engaging children from Maori and Pacific Island backgrounds and in improving knowledge, and some attitudes and practices, related to healthy eating and physical activity. The evaluation contributes valuable information about components and impacts of this type of intervention, and considerations relevant to this population in order to successfully change behaviours and reduce the burden of chronic disease.

End-to-End Information System design at the NASA Jet Propulsion Laboratory. [data transmission between user and space-based sensor

NASA Technical Reports Server (NTRS)

Hooke, A. J.

1978-01-01

In recognition of a pressing need of the 1980s to optimize the two-way flow of information between a ground-based user and a remote-space-based sensor, an end-to-end approach to the design of information systems has been adopted at the JPL. This paper reviews End-to-End Information System (EEIS) activity at the JPL, with attention given to the scope of the EEIS transfer function, and functional and physical elements of the EEIS. The relationship between the EEIS and the NASA End-to-End Data System program is discussed.

Human Activity Recognition in AAL Environments Using Random Projections.

PubMed

Damaševičius, Robertas; Vasiljevas, Mindaugas; Šalkevičius, Justas; Woźniak, Marcin

2016-01-01

Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject's body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented.

Human Activity Recognition in AAL Environments Using Random Projections

PubMed Central

Damaševičius, Robertas; Vasiljevas, Mindaugas; Šalkevičius, Justas; Woźniak, Marcin

2016-01-01

Automatic human activity recognition systems aim to capture the state of the user and its environment by exploiting heterogeneous sensors attached to the subject's body and permit continuous monitoring of numerous physiological signals reflecting the state of human actions. Successful identification of human activities can be immensely useful in healthcare applications for Ambient Assisted Living (AAL), for automatic and intelligent activity monitoring systems developed for elderly and disabled people. In this paper, we propose the method for activity recognition and subject identification based on random projections from high-dimensional feature space to low-dimensional projection space, where the classes are separated using the Jaccard distance between probability density functions of projected data. Two HAR domain tasks are considered: activity identification and subject identification. The experimental results using the proposed method with Human Activity Dataset (HAD) data are presented. PMID:27413392

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

NASA Astrophysics Data System (ADS)

Acciarri, R.; Adams, C.; An, R.; Anthony, J.; Asaadi, J.; Auger, M.; Bagby, L.; Balasubramanian, S.; Baller, B.; Barnes, C.; Barr, G.; Bass, M.; Bay, F.; Bishai, M.; Blake, A.; Bolton, T.; Camilleri, L.; Caratelli, D.; Carls, B.; Castillo Fernandez, R.; Cavanna, F.; Chen, H.; Church, E.; Cianci, D.; Cohen, E.; Collin, G. H.; Conrad, J. M.; Convery, M.; Crespo-Anadón, J. I.; Del Tutto, M.; Devitt, D.; Dytman, S.; Eberly, B.; Ereditato, A.; Escudero Sanchez, L.; Esquivel, J.; Fadeeva, A. A.; Fleming, B. T.; Foreman, W.; Furmanski, A. P.; Garcia-Gamez, D.; Garvey, G. T.; Genty, V.; Goeldi, D.; Gollapinni, S.; Graf, N.; Gramellini, E.; Greenlee, H.; Grosso, R.; Guenette, R.; Hackenburg, A.; Hamilton, P.; Hen, O.; Hewes, J.; Hill, C.; Ho, J.; Horton-Smith, G.; Hourlier, A.; Huang, E.-C.; James, C.; Jan de Vries, J.; Jen, C.-M.; Jiang, L.; Johnson, R. A.; Joshi, J.; Jostlein, H.; Kaleko, D.; Karagiorgi, G.; Ketchum, W.; Kirby, B.; Kirby, M.; Kobilarcik, T.; Kreslo, I.; Laube, A.; Li, Y.; Lister, A.; Littlejohn, B. R.; Lockwitz, S.; Lorca, D.; Louis, W. C.; Luethi, M.; Lundberg, B.; Luo, X.; Marchionni, A.; Mariani, C.; Marshall, J.; Martinez Caicedo, D. A.; Meddage, V.; Miceli, T.; Mills, G. B.; Moon, J.; Mooney, M.; Moore, C. D.; Mousseau, J.; Murrells, R.; Naples, D.; Nienaber, P.; Nowak, J.; Palamara, O.; Paolone, V.; Papavassiliou, V.; Pate, S. F.; Pavlovic, Z.; Piasetzky, E.; Porzio, D.; Pulliam, G.; Qian, X.; Raaf, J. L.; Rafique, A.; Rochester, L.; Rudolf von Rohr, C.; Russell, B.; Schmitz, D. W.; Schukraft, A.; Seligman, W.; Shaevitz, M. H.; Sinclair, J.; Smith, A.; Snider, E. L.; Soderberg, M.; Söldner-Rembold, S.; Soleti, S. R.; Spentzouris, P.; Spitz, J.; St. John, J.; Strauss, T.; Szelc, A. M.; Tagg, N.; Terao, K.; Thomson, M.; Toups, M.; Tsai, Y.-T.; Tufanli, S.; Usher, T.; Van De Pontseele, W.; Van de Water, R. G.; Viren, B.; Weber, M.; Wickremasinghe, D. A.; Wolbers, S.; Wongjirad, T.; Woodruff, K.; Yang, T.; Yates, L.; Zeller, G. P.; Zennamo, J.; Zhang, C.

2018-01-01

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.

Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

PubMed

Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

2017-06-01

We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

Infrared/Terahertz Double Resonance for Chemical Remote Sensing: Signatures and Performance Predictions

DTIC Science & Technology

2011-01-01

remote sensing , such as Fourier-transform infrared spectroscopy, has limited recognition specificity because of atmospheric pressure broadening. Active interrogation techniques promise much greater chemical recognition that can overcome the limits imposed by atmospheric pressure broadening. Here we introduce infrared - terahertz (IR/THz) double resonance spectroscopy as an active means of chemical remote sensing that retains recognition specificity through rare, molecule-unique coincidences between IR molecular absorption and a line-tunable CO2

Physical Connectivity Mapping by Circular Permutation of Human Telomerase RNA Reveals New Regions Critical for Activity and Processivity.

PubMed

Mefford, Melissa A; Zappulla, David C

2016-01-15

Telomerase is a specialized ribonucleoprotein complex that extends the 3' ends of chromosomes to counteract telomere shortening. However, increased telomerase activity is associated with ∼90% of human cancers. The telomerase enzyme minimally requires an RNA (hTR) and a specialized reverse transcriptase protein (TERT) for activity in vitro. Understanding the structure-function relationships within hTR has important implications for human disease. For the first time, we have tested the physical-connectivity requirements in the 451-nucleotide hTR RNA using circular permutations, which reposition the 5' and 3' ends. Our extensive in vitro analysis identified three classes of hTR circular permutants with altered function. First, circularly permuting 3' of the template causes specific defects in repeat-addition processivity, revealing that the template recognition element found in ciliates is conserved in human telomerase RNA. Second, seven circular permutations residing within the catalytically important core and CR4/5 domains completely abolish telomerase activity, unveiling mechanistically critical portions of these domains. Third, several circular permutations between the core and CR4/5 significantly increase telomerase activity. Our extensive circular permutation results provide insights into the architecture and coordination of human telomerase RNA and highlight where the RNA could be targeted for the development of antiaging and anticancer therapeutics. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Voluntary Exercise Preconditioning Activates Multiple Antiapoptotic Mechanisms and Improves Neurological Recovery after Experimental Traumatic Brain Injury

PubMed Central

Zhao, Zaorui; Sabirzhanov, Boris; Wu, Junfang; Faden, Alan I.

2015-01-01

Abstract Physical activity can attenuate neuronal loss, reduce neuroinflammation, and facilitate recovery after brain injury. However, little is known about the mechanisms of exercise-induced neuroprotection after traumatic brain injury (TBI) or its modulation of post-traumatic neuronal cell death. Voluntary exercise, using a running wheel, was conducted for 4 weeks immediately preceding (preconditioning) moderate-level controlled cortical impact (CCI), a well-established experimental TBI model in mice. Compared to nonexercised controls, exercise preconditioning (pre-exercise) improved recovery of sensorimotor performance in the beam walk task, as well as cognitive/affective functions in the Morris water maze, novel object recognition, and tail-suspension tests. Further, pre-exercise reduced lesion size, attenuated neuronal loss in the hippocampus, cortex, and thalamus, and decreased microglial activation in the cortex. In addition, exercise preconditioning activated the brain-derived neurotrophic factor pathway before trauma and amplified the injury-dependent increase in heat shock protein 70 expression, thus attenuating key apoptotic pathways. The latter include reduction in CCI-induced up-regulation of proapoptotic B-cell lymphoma 2 (Bcl-2)-homology 3–only Bcl-2 family molecules (Bid, Puma), decreased mitochondria permeabilization with attenuated release of cytochrome c and apoptosis-inducing factor (AIF), reduced AIF translocation to the nucleus, and attenuated caspase activation. Given these neuroprotective actions, voluntary physical exercise may serve to limit the consequences of TBI. PMID:25419789

Physical Connectivity Mapping by Circular Permutation of Human Telomerase RNA Reveals New Regions Critical for Activity and Processivity

PubMed Central

Mefford, Melissa A.

2015-01-01

Telomerase is a specialized ribonucleoprotein complex that extends the 3′ ends of chromosomes to counteract telomere shortening. However, increased telomerase activity is associated with ∼90% of human cancers. The telomerase enzyme minimally requires an RNA (hTR) and a specialized reverse transcriptase protein (TERT) for activity in vitro. Understanding the structure-function relationships within hTR has important implications for human disease. For the first time, we have tested the physical-connectivity requirements in the 451-nucleotide hTR RNA using circular permutations, which reposition the 5′ and 3′ ends. Our extensive in vitro analysis identified three classes of hTR circular permutants with altered function. First, circularly permuting 3′ of the template causes specific defects in repeat-addition processivity, revealing that the template recognition element found in ciliates is conserved in human telomerase RNA. Second, seven circular permutations residing within the catalytically important core and CR4/5 domains completely abolish telomerase activity, unveiling mechanistically critical portions of these domains. Third, several circular permutations between the core and CR4/5 significantly increase telomerase activity. Our extensive circular permutation results provide insights into the architecture and coordination of human telomerase RNA and highlight where the RNA could be targeted for the development of antiaging and anticancer therapeutics. PMID:26503788

Receptor-like cytoplasmic kinases are pivotal components in pattern recognition receptor-mediated signaling in plant immunity.

PubMed

Yamaguchi, Koji; Yamada, Kenta; Kawasaki, Tsutomu

2013-10-01

Innate immunity is generally initiated with recognition of conserved pathogen-associated molecular patterns (PAMPs). PAMPs are perceived by pattern recognition receptors (PRRs), leading to activation of a series of immune responses, including the expression of defense genes, ROS production and activation of MAP kinase. Recent progress has indicated that receptor-like cytoplasmic kinases (RLCKs) are directly activated by ligand-activated PRRs and initiate pattern-triggered immunity (PTI) in both Arabidopsis and rice. To suppress PTI, pathogens inhibit the RLCKs by many types of effectors, including AvrAC, AvrPphB and Xoo1488. In this review, we summarize recent advances in RLCK-mediated PTI in plants.

SCFβ-TrCP ubiquitin ligase-mediated processing of NF-κB p105 requires phosphorylation of its C-terminus by IκB kinase

PubMed Central

Orian, Amir; Gonen, Hedva; Bercovich, Beatrice; Fajerman, Ifat; Eytan, Esther; Israël, Alain; Mercurio, Frank; Iwai, Kazuhiro; Schwartz, Alan L.; Ciechanover, Aaron

2000-01-01

Processing of the p105 precursor to form the active subunit p50 of the NF-κB transcription factor is a unique case in which the ubiquitin system is involved in limited processing rather than in complete destruction of the target substrate. A glycine-rich region along with a downstream acidic domain have been demonstrated to be essential for processing. Here we demonstrate that following IκB kinase (IκK)-mediated phosphorylation, the C-terminal domain of p105 (residues 918–934) serves as a recognition motif for the SCFβ-TrCP ubiquitin ligase. Expression of IκKβ dramatically increases processing of wild-type p105, but not of p105-Δ918–934. Dominant-negative β-TrCP inhibits IκK-dependent processing. Furthermore, the ligase and wild-type p105 but not p105-Δ918–934 associate physically following phosphorylation. In vitro, SCFβ-TrCP specifically conjugates and promotes processing of phosphorylated p105. Importantly, the TrCP recognition motif in p105 is different from that described for IκBs, β-catenin and human immunodeficiency virus type 1 Vpu. Since p105-Δ918–934 is also conjugated and processed, it appears that p105 can be recognized under different physiological conditions by two different ligases, targeting two distinct recognition motifs. PMID:10835356

Prestimulus default mode activity influences depth of processing and recognition in an emotional memory task.

PubMed

Soravia, Leila M; Witmer, Joëlle S; Schwab, Simon; Nakataki, Masahito; Dierks, Thomas; Wiest, Roland; Henke, Katharina; Federspiel, Andrea; Jann, Kay

2016-03-01

Low self-referential thoughts are associated with better concentration, which leads to deeper encoding and increases learning and subsequent retrieval. There is evidence that being engaged in externally rather than internally focused tasks is related to low neural activity in the default mode network (DMN) promoting open mind and the deep elaboration of new information. Thus, reduced DMN activity should lead to enhanced concentration, comprehensive stimulus evaluation including emotional categorization, deeper stimulus processing, and better long-term retention over one whole week. In this fMRI study, we investigated brain activation preceding and during incidental encoding of emotional pictures and on subsequent recognition performance. During fMRI, 24 subjects were exposed to 80 pictures of different emotional valence and subsequently asked to complete an online recognition task one week later. Results indicate that neural activity within the medial temporal lobes during encoding predicts subsequent memory performance. Moreover, a low activity of the default mode network preceding incidental encoding leads to slightly better recognition performance independent of the emotional perception of a picture. The findings indicate that the suppression of internally-oriented thoughts leads to a more comprehensive and thorough evaluation of a stimulus and its emotional valence. Reduced activation of the DMN prior to stimulus onset is associated with deeper encoding and enhanced consolidation and retrieval performance even one week later. Even small prestimulus lapses of attention influence consolidation and subsequent recognition performance. © 2015 Wiley Periodicals, Inc.

Dissociated active and passive tactile shape recognition: a case study of pure tactile apraxia.

PubMed

Valenza, N; Ptak, R; Zimine, I; Badan, M; Lazeyras, F; Schnider, A

2001-11-01

Disorders of tactile object recognition (TOR) may result from primary motor or sensory deficits or higher cognitive impairment of tactile shape representations or semantic memory. Studies with healthy participants suggest the existence of exploratory motor procedures directly linked to the extraction of specific properties of objects. A pure deficit of these procedures without concomitant gnostic disorders has never been described in a brain-damaged patient. Here, we present a patient with a right hemispheric infarction who, in spite of intact sensorimotor functions, had impaired TOR with the left hand. Recognition of 2D shapes and objects was severely deficient under the condition of spontaneous exploration. Tactile exploration of shapes was disorganized and exploratory procedures, such as the contour-following strategy, which is necessary to identify the precise shape of an object, were severely disturbed. However, recognition of 2D shapes under manually or verbally guided exploration and the recognition of shapes traced on the skin were intact, indicating a dissociation in shape recognition between active and passive touch. Functional MRI during sensory stimulation of the left hand showed preserved activation of the spared primary sensory cortex in the right hemisphere. We interpret the deficit of our patient as a pure tactile apraxia without tactile agnosia, i.e. a specific inability to use tactile feedback to generate the exploratory procedures necessary for tactile shape recognition.

Oxytocin, vasopressin and estrogen receptor gene expression in relation to social recognition in female mice.

PubMed

Clipperton-Allen, Amy E; Lee, Anna W; Reyes, Anny; Devidze, Nino; Phan, Anna; Pfaff, Donald W; Choleris, Elena

2012-02-28

Inter- and intra-species differences in social behavior and recognition-related hormones and receptors suggest that different distribution and/or expression patterns may relate to social recognition. We used qRT-PCR to investigate naturally occurring differences in expression of estrogen receptor-alpha (ERα), ER-beta (ERβ), progesterone receptor (PR), oxytocin (OT) and receptor, and vasopressin (AVP) and receptors in proestrous female mice. Following four 5 min exposures to the same two conspecifics, one was replaced with a novel mouse in the final trial (T5). Gene expression was examined in mice showing high (85-100%) and low (40-60%) social recognition scores (i.e., preferential novel mouse investigation in T5) in eight socially-relevant brain regions. Results supported OT and AVP involvement in social recognition, and suggest that in the medial preoptic area, increased OT and AVP mRNA, together with ERα and ERβ gene activation, relate to improved social recognition. Initial social investigation correlated with ERs, PR and OTR in the dorsolateral septum, suggesting that these receptors may modulate social interest without affecting social recognition. Finally, increased lateral amygdala gene activation in the LR mice may be associated with general learning impairments, while decreased lateral amygdala activity may indicate more efficient cognitive mechanisms in the HR mice. Copyright © 2011 Elsevier Inc. All rights reserved.

Object recognition for autonomous robot utilizing distributed knowledge database

NASA Astrophysics Data System (ADS)

Takatori, Jiro; Suzuki, Kenji; Hartono, Pitoyo; Hashimoto, Shuji

2003-10-01

In this paper we present a novel method of object recognition utilizing a remote knowledge database for an autonomous robot. The developed robot has three robot arms with different sensors; two CCD cameras and haptic sensors. It can see, touch and move the target object from different directions. Referring to remote knowledge database of geometry and material, the robot observes and handles the objects to understand them including their physical characteristics.

[Research on Barrier-free Home Environment System Based on Speech Recognition].

PubMed

Zhu, Husheng; Yu, Hongliu; Shi, Ping; Fang, Youfang; Jian, Zhuo

2015-10-01

The number of people with physical disabilities is increasing year by year, and the trend of population aging is more and more serious. In order to improve the quality of the life, a control system of accessible home environment for the patients with serious disabilities was developed to control the home electrical devices with the voice of the patients. The control system includes a central control platform, a speech recognition module, a terminal operation module, etc. The system combines the speech recognition control technology and wireless information transmission technology with the embedded mobile computing technology, and interconnects the lamp, electronic locks, alarms, TV and other electrical devices in the home environment as a whole system through a wireless network node. The experimental results showed that speech recognition success rate was more than 84% in the home environment.

Olfactory stimuli as context cues in human memory.

PubMed

Cann, A; Ross, D A

1989-01-01

Olfactory stimuli were used as context cues in a recognition memory paradigm. Male college students were exposed to 50 slides of the faces of college females while in the presence of a pleasant or an unpleasant odor. During the acquisition phase, ratings of physical attractiveness of the slides were collected. After a 48-hr delay, a recognition test was given using the original 50 slides and 50 new slides. The recognition test was conducted with either the original odor or the alternative odor present. A no-odor control group did not receive olfactory cues. The attractiveness ratings indicated that the odor variations had no effect on these social judgments. Analyses of d' scores, hits, and false alarms for the recognition performance indicated support for the predicted interaction in which presence of the same odor at both sessions led to better overall performance.

Reinforcing historic distinctions between mental and physical injury: the impact of the civil liability reforms.

PubMed

Forster, Christine; Engel, Jeni

2012-03-01

Mental injury has been differentiated from physical injury since its entry into Australian tort law, with mental injury consistently subject to the most onerous regime. In 2002 in its Review of the Law of Negligence, the Ipp Panel supported the historic distinction between physical and mental injury and recommended further (restrictive) changes to the common law rules in relation to mental injury. This article considers and evaluates the reforms which were introduced into six Australian jurisdictions in relation to mental injury in the tort of negligence in response to the Ipp Panel's recommendations arguing that the rationale for differentiating pure mental injury from physical injury and consequential mental injury is nebulous. It argues that the reforms operate to reinforce and magnify historic distinctions between physical and mental harm despite increasing recognition in the medical literature of the interrelationship between physical and psychiatric injury; despite the recognition of the professional ability of psychiatrists and psychologists to accurately pinpoint and diagnose mental injury; despite extensive documentation of the far-reaching and devastating impact that psychiatric injury has on victims, families and the community; and despite evidence that early and adequate treatment of mental injury can prevent a raft of damaging and costly personal and societal consequences.

Opportunities for Recognition Can Improve Learning and Performance

ERIC Educational Resources Information Center

French, Ron; Henderson, Hester L.; Lavay, Barry; Silliman-French, Lisa

2013-01-01

Physical educators need to make an effort to catch students being good and recognize them for their positive accomplishments. Unfortunately, it is usually the students who act inappropriately who receive the majority of the teachers' attention. In order to help increase learning and improve performance and behavior, the physical educator must…

Lifestyle as an important factor in control of overweight and obesity among schoolchildren from the rural environment.

PubMed

Sygit, Katarzyna; Kołłątaj, Witold; Goździewska, Małgorzta; Sygit, Marian; Kołłątaj, Barbara; Karwat, Irena Dorota

2012-01-01

Lifestyle of an individual is responsible for sixty percent of his/her state of health. Many studies of this problem indicate that in the style of life of schoolchildren, anti-health behaviours dominate over health promoting behaviours. The objective of the presented study was recognition of the lifestyle of the rural adolescents with overweight and obesity. The study covered adolescents aged 15-19, living in the rural environments of the West Pomeranian Region. Finally, the analysis covered 2,165 schoolchildren, and was performed with the use of a self-designed questionnaire form and the BMI was applied. The study showed that overweight occurred more often in the group of examined girls than boys, while obesity was twice as frequent among boys than among girls. Overweight schoolchildren (35.1%) had an adequate diet, while those obese--inadequate (78.3%). In the group of schoolchildren with overweight, passive leisure prevailed over active forms of leisure, 83.8% and 16.2%, respectively. Passive leisure was also dominant among obese respondents. Among as many as 81.8% of schoolchildren with overweight, physical activity was mediocre, while only 8.1% of them were active. The highest percentage of respondents with obesity were totally inactive physically. Obese schoolchildren relatively often experienced stressful situations. It is an alarming fact that both overweight and obese schoolchildren relatively often used psychoactive substances. A considerable number of respondents with overweight and obesity applied an adequate diet, preferred passive forms of leisure, experienced stressful situations, were characterized by low physical activity, and systematically used psychoactive substances.

Genetic and environmental influences on the allocation of adolescent leisure time activities.

PubMed

Haberstick, Brett C; Zeiger, Joanna S; Corley, Robin P

2014-01-01

There is a growing recognition of the importance of the out-of-school activities in which adolescents choose to participate. Youth activities vary widely in terms of specific activities and in time devoted to them but can generally be grouped by the type and total duration spent per type. We collected leisure time information using a 17-item leisure time questionnaire in a large sample of same- and opposite-sex adolescent twin pairs (N = 2847). Using both univariate and multivariate genetic models, we sought to determine the type and magnitude of genetic and environmental influences on the allocation of time toward different leisure times. Results indicated that both genetic and shared and nonshared environmental influences were important contributors to individual differences in physical, social, intellectual, family, and passive activities such as watching television. The magnitude of these influences differed between males and females. Environmental influences were the primary factors contributing to the covariation of different leisure time activities. Our results suggest the importance of heritable influences on the allocation of leisure time activity by adolescents and highlight the importance of environmental experiences in these choices.

Genetic and Environmental Influences on the Allocation of Adolescent Leisure Time Activities

PubMed Central

Haberstick, Brett C.; Zeiger, Joanna S.; Corley, Robin P.

2014-01-01

There is a growing recognition of the importance of the out-of-school activities in which adolescents choose to participate. Youth activities vary widely in terms of specific activities and in time devoted to them but can generally be grouped by the type and total duration spent per type. We collected leisure time information using a 17-item leisure time questionnaire in a large sample of same- and opposite-sex adolescent twin pairs (N = 2847). Using both univariate and multivariate genetic models, we sought to determine the type and magnitude of genetic and environmental influences on the allocation of time toward different leisure times. Results indicated that both genetic and shared and nonshared environmental influences were important contributors to individual differences in physical, social, intellectual, family, and passive activities such as watching television. The magnitude of these influences differed between males and females. Environmental influences were the primary factors contributing to the covariation of different leisure time activities. Our results suggest the importance of heritable influences on the allocation of leisure time activity by adolescents and highlight the importance of environmental experiences in these choices. PMID:24967407

Recognition memory for vibrotactile rhythms: an fMRI study in blind and sighted individuals.

PubMed

Sinclair, Robert J; Dixit, Sachin; Burton, Harold

2011-01-01

Calcarine sulcal cortex possibly contributes to semantic recognition memory in early blind (EB). We assessed a recognition memory role using vibrotactile rhythms and a retrieval success paradigm involving learned "old" and "new" rhythms in EB and sighted. EB showed no activation differences in occipital cortex indicating retrieval success but replicated findings of somatosensory processing. Both groups showed retrieval success in primary somatosensory, precuneus, and orbitofrontal cortex. The S1 activity might indicate generic sensory memory processes.

Recognition memory for vibrotactile rhythms: An fMRI study in blind and sighted individuals

PubMed Central

SINCLAIR, ROBERT J.; DIXIT, SACHIN; BURTON, HAROLD

2014-01-01

Calcarine sulcal cortex possibly contributes to semantic recognition memory in early blind (EB). We assessed a recognition memory role using vibrotactile rhythms and a retrieval success paradigm involving learned “old” and “new” rhythms in EB and sighted. EB showed no activation differences in occipital cortex indicating retrieval success but replicated findings of somatosensory processing. Both groups showed retrieval success in primary somatosensory, precuneus, and orbitofrontal cortex. The S1 activity might indicate generic sensory memory processes. PMID:21846300

Women in Physics in the United States

NASA Astrophysics Data System (ADS)

Zastavker, Yevgeniya V.; Gueye, Paul; Mack, Kelly M.; Ivie, Rachel; Simmons, Elizabeth H.; Santos, Lea F.; Martínez-Miranda, Luz J.; Bienenstock, Arthur; Blickenstaff, Jacob Clark; Horton, K. Renee; MacLachlan, Anne J.; Berrah, Nora; Hartline, Beverly K.

2009-04-01

The underrepresentation of women in physics and related fields in the US remains significant despite an increase in doctoral degrees earned over the past 10 years. An even greater disparity is seen among minority women. Increasing recognition of the contributions of women to discovery and education in physics and related fields has led to government initiatives and other programs to promote broader inclusion, balance, and gender equity. These actions for advocating women in physics in the US since the first IUPAP Women in Physics Conference in 2002 are presented.

A dynamical pattern recognition model of gamma activity in auditory cortex

PubMed Central

Zavaglia, M.; Canolty, R.T.; Schofield, T.M.; Leff, A.P.; Ursino, M.; Knight, R.T.; Penny, W.D.

2012-01-01

This paper describes a dynamical process which serves both as a model of temporal pattern recognition in the brain and as a forward model of neuroimaging data. This process is considered at two separate levels of analysis: the algorithmic and implementation levels. At an algorithmic level, recognition is based on the use of Occurrence Time features. Using a speech digit database we show that for noisy recognition environments, these features rival standard cepstral coefficient features. At an implementation level, the model is defined using a Weakly Coupled Oscillator (WCO) framework and uses a transient synchronization mechanism to signal a recognition event. In a second set of experiments, we use the strength of the synchronization event to predict the high gamma (75–150 Hz) activity produced by the brain in response to word versus non-word stimuli. Quantitative model fits allow us to make inferences about parameters governing pattern recognition dynamics in the brain. PMID:22327049

Event-related theta synchronization predicts deficit in facial affect recognition in schizophrenia.

PubMed

Csukly, Gábor; Stefanics, Gábor; Komlósi, Sarolta; Czigler, István; Czobor, Pál

2014-02-01

Growing evidence suggests that abnormalities in the synchronized oscillatory activity of neurons in schizophrenia may lead to impaired neural activation and temporal coding and thus lead to neurocognitive dysfunctions, such as deficits in facial affect recognition. To gain an insight into the neurobiological processes linked to facial affect recognition, we investigated both induced and evoked oscillatory activity by calculating the Event Related Spectral Perturbation (ERSP) and the Inter Trial Coherence (ITC) during facial affect recognition. Fearful and neutral faces as well as nonface patches were presented to 24 patients with schizophrenia and 24 matched healthy controls while EEG was recorded. The participants' task was to recognize facial expressions. Because previous findings with healthy controls showed that facial feature decoding was associated primarily with oscillatory activity in the theta band, we analyzed ERSP and ITC in this frequency band in the time interval of 140-200 ms, which corresponds to the N170 component. Event-related theta activity and phase-locking to facial expressions, but not to nonface patches, predicted emotion recognition performance in both controls and patients. Event-related changes in theta amplitude and phase-locking were found to be significantly weaker in patients compared with healthy controls, which is in line with previous investigations showing decreased neural synchronization in the low frequency bands in patients with schizophrenia. Neural synchrony is thought to underlie distributed information processing. Our results indicate a less effective functioning in the recognition process of facial features, which may contribute to a less effective social cognition in schizophrenia. PsycINFO Database Record (c) 2014 APA, all rights reserved.

REM sleep and emotional face memory in typically-developing children and children with autism.

PubMed

Tessier, Sophie; Lambert, Andréane; Scherzer, Peter; Jemel, Boutheina; Godbout, Roger

2015-09-01

Relationship between REM sleep and memory was assessed in 13 neurotypical and 13 children with Autistic Spectrum Disorder (ASD). A neutral/positive/negative face recognition task was administered the evening before (learning and immediate recognition) and the morning after (delayed recognition) sleep. The number of rapid eye movements (REMs), beta and theta EEG activity over the visual areas were measured during REM sleep. Compared to neurotypical children, children with ASD showed more theta activity and longer reaction time (RT) for correct responses in delayed recognition of neutral faces. Both groups showed a positive correlation between sleep and performance but different patterns emerged: in neurotypical children, accuracy for recalling neutral faces and overall RT improvement overnight was correlated with EEG activity and REMs; in children with ASD, overnight RT improvement for positive and negative faces correlated with theta and beta activity, respectively. These results suggest that neurotypical and children with ASD use different sleep-related brain networks to process faces. Copyright © 2015 Elsevier B.V. All rights reserved.

Recognizing stationary and locomotion activities using combinational of spectral analysis with statistical descriptors features

NASA Astrophysics Data System (ADS)

Zainudin, M. N. Shah; Sulaiman, Md Nasir; Mustapha, Norwati; Perumal, Thinagaran

2017-10-01

Prior knowledge in pervasive computing recently garnered a lot of attention due to its high demand in various application domains. Human activity recognition (HAR) considered as the applications that are widely explored by the expertise that provides valuable information to the human. Accelerometer sensor-based approach is utilized as devices to undergo the research in HAR since their small in size and this sensor already build-in in the various type of smartphones. However, the existence of high inter-class similarities among the class tends to degrade the recognition performance. Hence, this work presents the method for activity recognition using our proposed features from combinational of spectral analysis with statistical descriptors that able to tackle the issue of differentiating stationary and locomotion activities. The noise signal is filtered using Fourier Transform before it will be extracted using two different groups of features, spectral frequency analysis, and statistical descriptors. Extracted signal later will be classified using random forest ensemble classifier models. The recognition results show the good accuracy performance for stationary and locomotion activities based on USC HAD datasets.

Luminance sticker based facial expression recognition using discrete wavelet transform for physically disabled persons.

PubMed

Nagarajan, R; Hariharan, M; Satiyan, M

2012-08-01

Developing tools to assist physically disabled and immobilized people through facial expression is a challenging area of research and has attracted many researchers recently. In this paper, luminance stickers based facial expression recognition is proposed. Recognition of facial expression is carried out by employing Discrete Wavelet Transform (DWT) as a feature extraction method. Different wavelet families with their different orders (db1 to db20, Coif1 to Coif 5 and Sym2 to Sym8) are utilized to investigate their performance in recognizing facial expression and to evaluate their computational time. Standard deviation is computed for the coefficients of first level of wavelet decomposition for every order of wavelet family. This standard deviation is used to form a set of feature vectors for classification. In this study, conventional validation and cross validation are performed to evaluate the efficiency of the suggested feature vectors. Three different classifiers namely Artificial Neural Network (ANN), k-Nearest Neighborhood (kNN) and Linear Discriminant Analysis (LDA) are used to classify a set of eight facial expressions. The experimental results demonstrate that the proposed method gives very promising classification accuracies.

Improvement of dizocilpine-induced social recognition deficits in mice by brexpiprazole, a novel serotonin-dopamine activity modulator.

PubMed

Yoshimi, Noriko; Futamura, Takashi; Hashimoto, Kenji

2015-03-01

Cognitive impairment, including impaired social cognition, is largely responsible for the deterioration in social life suffered by patients with psychiatric disorders, such as schizophrenia and major depressive disorder (MDD). Brexpiprazole (7-{4-[4-(1-benzothiophen-4-yl)piperazin-1-yl]butoxy}quinolin-2(1H)-one), a novel serotonin-dopamine activity modulator, was developed to offer efficacious and tolerable therapy for different psychiatric disorders, including schizophrenia and adjunctive treatment of MDD. In this study, we investigated whether brexpiprazole could improve social recognition deficits (one of social cognition deficits) in mice, after administration of the N-methyl-d-aspartate (NMDA) receptor antagonist MK-801 (dizocilpine). Dosing with dizocilpine (0.1mg/kg) induced significant impairment of social recognition in mice. Brexpiprazole (0.01, 0.03, 0.1mg/kg, p.o.) significantly ameliorated dizocilpine-induced social recognition deficits, without sedation or a reduction of exploratory behavior. In addition, brexpiprazole alone had no effect on social recognition in untreated control mice. By contrast, neither risperidone (0.03mg/kg, p.o.) nor olanzapine (0.03mg/kg, p.o.) altered dizocilpine-induced social recognition deficits. Finally, the effect of brexpiprazole on dizocilpine-induced social recognition deficits was antagonized by WAY-100,635, a selective serotonin 5-HT1A antagonist. These results suggest that brexpiprazole could improve dizocilpine-induced social recognition deficits via 5-HT1A receptor activation in mice. Therefore, brexpiprazole may confer a beneficial effect on social cognition deficits in patients with psychiatric disorders. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

No space for girliness in physics: understanding and overcoming the masculinity of physics

NASA Astrophysics Data System (ADS)

Götschel, Helene

2014-06-01

Allison Gonsalves' article on "women doctoral students' positioning around discourses of gender and competence in physics" explores narratives of Canadian women physicists concerning their strategies to gain recognition as physicists. In my response to her rewarding and inspiring analysis I will reflect on her findings and arguments and put them into a broader context of research in gender and physics. In addition to her promising strategies to make physics attractive and welcoming to all genders I want to stress two more aspects of the tricky problem: diversity and contextuality of physics.

Functional MRI study of diencephalic amnesia in Wernicke-Korsakoff syndrome.

PubMed

Caulo, M; Van Hecke, J; Toma, L; Ferretti, A; Tartaro, A; Colosimo, C; Romani, G L; Uncini, A

2005-07-01

Anterograde amnesia in Wernicke-Korsakoff syndrome is associated with diencephalic lesions, mainly in the anterior thalamic nuclei. Whether diencephalic and temporal lobe amnesias are distinct entities is still not clear. We investigated episodic memory for faces using functional MRI (fMRI) in eight controls and in a 34-year-old man with Wernicke-Korsakoff syndrome and diencephalic lesions but without medial temporal lobe (MTL) involvement at MRI. fMRI was performed with a 1.5 tesla unit. Three dual-choice tasks were employed: (i) face encoding (18 faces were randomly presented three times and subjects were asked to memorize the faces); (ii) face perception (subjects indicated which of two faces matched a third face); and (iii) face recognition (subjects indicated which of two faces belonged to the group they had been asked to memorize during encoding). All activation was greater in the right hemisphere. In controls both the encoding and recognition tasks activated two hippocampal regions (anterior and posterior). The anterior hippocampal region was more activated during recognition. Activation in the prefrontal cortex was greater during recognition. In the subject with Wernicke-Korsakoff syndrome, fMRI did not show hippocampal activation during either encoding or recognition. During recognition, although behavioural data showed defective retrieval, the prefrontal regions were activated as in controls, except for the ventrolateral prefrontal cortex. fMRI activation of the visual cortices and the behavioural score on the perception task indicated that the subject with Wernicke-Korsakoff syndrome perceived the faces, paid attention to the task and demonstrated accurate judgement. In the subject with Wernicke-Korsakoff syndrome, although the anatomical damage does not involve the MTL, the hippocampal memory encoding has been lost, possibly as a consequence of the hippocampal-anterior thalamic axis involvement. Anterograde amnesia could therefore be the expression of damage to an extended hippocampal system, and the distinction between temporal lobe and diencephalic amnesia has limited value. In the subject with Wernicke-Korsakoff syndrome, the preserved dorsolateral prefrontal cortex activation during incorrect recognition suggests that this region is more involved in either the orientation or attention at retrieval than in retrieval. The lack of activation of the prefrontal ventrolateral cortex confirms the role of this area in episodic memory formation.

Production of human lactoferrin in animal milk.

PubMed

Goldman, I L; Georgieva, S G; Gurskiy, Ya G; Krasnov, A N; Deykin, A V; Popov, A N; Ermolkevich, T G; Budzevich, A I; Chernousov, A D; Sadchikova, E R

2012-06-01

Genetic constructs containing the human lactoferrin (hLf) gene were created within a joint program of Russian and Belorussian scientists. Using these constructs, transgenic mice were bred (the maximum hLf concentration in their milk was 160 g/L), and transgenic goats were also generated (up to 10 g/L hLf in their milk). Experimental goatherds that produced hLf in their milk were also bred, and the recombinant hLf was found to be identical to the natural protein in its physical and chemical properties. These properties included electrophoretic mobility, isoelectric point, recognition by polyclonal and monoclonal antibodies, circular dichroic spectra, interaction with natural ligands (DNA, lipopolysaccharides, and heparin), the binding of iron ions, the sequence of the 7 terminal amino acids, and its biological activity. The latter was assessed by the agglutination of Micrococcus luteus protoplasts, bactericidal activity against Escherichia coli and Listeria monocytogenes , and fungicidal activity against Candida albicans . We also demonstrated a significant increase in the activity of antibiotics when used in combination with Lf.

Implementation study of wearable sensors for activity recognition systems

PubMed Central

Ghassemian, Mona

2015-01-01

This Letter investigates and reports on a number of activity recognition methods for a wearable sensor system. The authors apply three methods for data transmission, namely ‘stream-based’, ‘feature-based’ and ‘threshold-based’ scenarios to study the accuracy against energy efficiency of transmission and processing power that affects the mote's battery lifetime. They also report on the impact of variation of sampling frequency and data transmission rate on energy consumption of motes for each method. This study leads us to propose a cross-layer optimisation of an activity recognition system for provisioning acceptable levels of accuracy and energy efficiency. PMID:26609413

Implementation of a Peltier-based cooling device for localized deep cortical deactivation during in vivo object recognition testing

NASA Astrophysics Data System (ADS)

Marra, Kyle; Graham, Brett; Carouso, Samantha; Cox, David

2012-02-01

While the application of local cortical cooling has recently become a focus of neurological research, extended localized deactivation deep within brain structures is still unexplored. Using a wirelessly controlled thermoelectric (Peltier) device and water-based heat sink, we have achieved inactivating temperatures (<20 C) at greater depths (>8 mm) than previously reported. After implanting the device into Long Evans rats' basolateral amygdala (BLA), an inhibitory brain center that controls anxiety and fear, we ran an open field test during which anxiety-driven behavioral tendencies were observed to decrease during cooling, thus confirming the device's effect on behavior. Our device will next be implanted in the rats' temporal association cortex (TeA) and recordings from our signal-tracing multichannel microelectrodes will measure and compare activated and deactivated neuronal activity so as to isolate and study the TeA signals responsible for object recognition. Having already achieved a top performing computational face-recognition system, the lab will utilize this TeA activity data to generalize its computational efforts of face recognition to achieve general object recognition.

Video-based convolutional neural networks for activity recognition from robot-centric videos

NASA Astrophysics Data System (ADS)

Ryoo, M. S.; Matthies, Larry

2016-05-01

In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

Activity Augmentation of Amphioxus Peptidoglycan Recognition Protein BbtPGRP3 via Fusion with a Chitin Binding Domain

PubMed Central

Wang, Wen-Jie; Cheng, Wang; Luo, Ming; Yan, Qingyu; Yu, Hong-Mei; Li, Qiong; Cao, Dong-Dong; Huang, Shengfeng; Xu, Anlong; Mariuzza, Roy A.; Chen, Yuxing; Zhou, Cong-Zhao

2015-01-01

Peptidoglycan recognition proteins (PGRPs), which have been identified in most animals, are pattern recognition molecules that involve antimicrobial defense. Resulting from extraordinary expansion of innate immune genes, the amphioxus encodes many PGRPs of diverse functions. For instance, three isoforms of PGRP encoded by Branchiostoma belcheri tsingtauense, termed BbtPGRP1~3, are fused with a chitin binding domain (CBD) at the N-terminus. Here we report the 2.7 Å crystal structure of BbtPGRP3, revealing an overall structure of an N-terminal hevein-like CBD followed by a catalytic PGRP domain. Activity assays combined with site-directed mutagenesis indicated that the individual PGRP domain exhibits amidase activity towards both DAP-type and Lys-type peptidoglycans (PGNs), the former of which is favored. The N-terminal CBD not only has the chitin-binding activity, but also enables BbtPGRP3 to gain a five-fold increase of amidase activity towards the Lys-type PGNs, leading to a significantly broadened substrate spectrum. Together, we propose that modular evolution via domain shuffling combined with gene horizontal transfer makes BbtPGRP1~3 novel PGRPs of augmented catalytic activity and broad recognition spectrum. PMID:26479246

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition.

PubMed

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-18

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters' influence on performance to provide insights about their optimisation.

Longing for existential recognition: a qualitative study of everyday concerns for people with somatoform disorders.

PubMed

Lind, Annemette Bondo; Risoer, Mette Bech; Nielsen, Klaus; Delmar, Charlotte; Christensen, Morten Bondo; Lomborg, Kirsten

2014-02-01

Patients with somatoform disorders could be vulnerable to stressors and have difficulties coping with stress. The aim was to explore what the patients experience as stressful and how they resolve stress in everyday life. A cross-sectional retrospective design using 24 semi-structured individual life history interviews. Data-analysis was based on grounded theory. A major concern in patients was a longing for existential recognition. This influenced the patients' self-confidence, stress appraisals, symptom perceptions, and coping attitudes. Generally, patients had difficulties with self-confidence and self-recognition of bodily sensations, feelings, vulnerability, and needs, which negatively framed their attempts to obtain recognition in social interactions. Experiences of recognition appeared in three different modalities: 1) "existential misrecognition" covered the experience of being met with distrust and disrespect, 2) "uncertain existential recognition" covered experiences of unclear communication and a perception of not being totally recognized, and 3) "successful existential recognition" covered experiences of total respect and understanding. "Misrecognition" and "uncertain recognition" related to decreased self-confidence, avoidant coping behaviours, increased stress, and symptom appraisal; whereas "successful recognition" related to higher self-confidence, active coping behaviours, decreased stress, and symptom appraisal. Different modalities of existential recognition influenced self-identity and social identity affecting patients' daily stress and symptom appraisals, self-confidence, self-recognition, and coping attitudes. Clinically it seems crucial to improve the patients' ability to communicate concerns, feelings, and needs in social interactions. Better communicative skills and more active coping could reduce the harm the patients experienced by not being recognized and increase the healing potential of successful recognition. Copyright © 2013 Elsevier Inc. All rights reserved.

Activation of mitogen-activated protein kinase/extracellular signal-regulated kinase in hippocampal circuitry is required for consolidation and reconsolidation of recognition memory.

PubMed

Kelly, Aine; Laroche, Serge; Davis, Sabrina

2003-06-15

Consolidation and reconsolidation of long-term memory have been shown to be dependent on the synthesis of new proteins, but the specific molecular mechanisms underlying these events remain to be elucidated. The mitogen-activated protein kinase (MAPK) pathway can trigger genomic responses in neurons, leading to changes in protein synthesis, and several studies have identified its pivotal role in synaptic plasticity and long-term memory formation. In this study, we analyze the involvement of this pathway in the consolidation and reconsolidation of long-term recognition memory, using an object recognition task. We show that inhibition of the MAPK pathway by intracerebroventricular injection of the MEK [MAPK/extracellular signal-regulated kinase (ERK)] inhibitor UO126 blocks consolidation of object recognition memory but does not affect short-term memory. Brain regions of the entorhinal cortex-hippocampal circuitry were analyzed for ERK activation, and it was shown that consolidation of recognition memory was associated with increased phosphorylation of ERK in the dentate gyrus and entorhinal cortex, although total expression of ERK was unchanged. We also report that inhibition of the MAPK pathway blocks reconsolidation of recognition memory, and this was shown to be dependent on reactivation of the memory trace by brief reexposure to the objects. In addition, reconsolidation of memory was associated with an increase in the phosphorylation of ERK in entorhinal cortex and CA1. In summary, our data show that the MAPK kinase pathway is required for both consolidation and reconsolidation of long-term recognition memory, and that this is associated with hyperphosphorylation of ERK in different subregions of the entorhinal cortex-hippocampal circuitry.

Functional Connectivity of Multiple Brain Regions Required for the Consolidation of Social Recognition Memory.

PubMed

Tanimizu, Toshiyuki; Kenney, Justin W; Okano, Emiko; Kadoma, Kazune; Frankland, Paul W; Kida, Satoshi

2017-04-12

Social recognition memory is an essential and basic component of social behavior that is used to discriminate familiar and novel animals/humans. Previous studies have shown the importance of several brain regions for social recognition memories; however, the mechanisms underlying the consolidation of social recognition memory at the molecular and anatomic levels remain unknown. Here, we show a brain network necessary for the generation of social recognition memory in mice. A mouse genetic study showed that cAMP-responsive element-binding protein (CREB)-mediated transcription is required for the formation of social recognition memory. Importantly, significant inductions of the CREB target immediate-early genes c-fos and Arc were observed in the hippocampus (CA1 and CA3 regions), medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), and amygdala (basolateral region) when social recognition memory was generated. Pharmacological experiments using a microinfusion of the protein synthesis inhibitor anisomycin showed that protein synthesis in these brain regions is required for the consolidation of social recognition memory. These findings suggested that social recognition memory is consolidated through the activation of CREB-mediated gene expression in the hippocampus/mPFC/ACC/amygdala. Network analyses suggested that these four brain regions show functional connectivity with other brain regions and, more importantly, that the hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas the ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. We have found that a brain network composed of the hippocampus/mPFC/ACC/amygdala is required for the consolidation of social recognition memory. SIGNIFICANCE STATEMENT Here, we identify brain networks composed of multiple brain regions for the consolidation of social recognition memory. We found that social recognition memory is consolidated through CREB-meditated gene expression in the hippocampus, medial prefrontal cortex, anterior cingulate cortex (ACC), and amygdala. Importantly, network analyses based on c-fos expression suggest that functional connectivity of these four brain regions with other brain regions is increased with time spent in social investigation toward the generation of brain networks to consolidate social recognition memory. Furthermore, our findings suggest that hippocampus functions as a hub to integrate brain networks and generate social recognition memory, whereas ACC and amygdala are important for coordinating brain activity when social interaction is initiated by connecting with other brain regions. Copyright © 2017 the authors 0270-6474/17/374103-14$15.00/0.

Limited Bandwidth Recognition of Collective Behaviors in Bio-Inspired Swarms

DTIC Science & Technology

2014-05-01

Nevai, K. M. Passino, and P. Srinivasan. Stability of choice in the honey bee nest-site selection processs. Journal of Theoretical Biology , 263(1):93...and N. Franks. Collective memory and spatial sorting in animal groups. Journal of Theoretical Biology , 218(1):1–11, 2002. [4] D. Cvetkovic, P...motion from local attraction. Journal of Theoretical Biology , 283(1):145–151, 2011. [18] G. Sukthankar and K. Sycara. Robust recognition of physical team

Understanding the impact of symptoms on the burden of COPD.

PubMed

Miravitlles, Marc; Ribera, Anna

2017-04-21

Chronic obstructive pulmonary disease (COPD) imposes a substantial burden on individuals with the disease, which can include a range of symptoms (breathlessness, cough, sputum production, wheeze, chest tightness) of varying severities. We present an overview of the biomedical literature describing reported relationships between COPD symptoms and disease burden in terms of quality of life, health status, daily activities, physical activity, sleep, comorbid anxiety, and depression, as well as risk of exacerbations and disease prognosis. In addition, the substantial variability of COPD symptoms encountered (morning, daytime, and nighttime) is addressed and their implications for disease burden considered. The findings from this narrative review, which mainly focuses on real-world and observational studies, demonstrate the impact of COPD symptoms on the burden of disease and that improved recognition and understanding of their impact is central to alleviating this burden.

Learning a Taxonomy of Predefined and Discovered Activity Patterns

PubMed Central

Krishnan, Narayanan; Cook, Diane J.; Wemlinger, Zachary

2013-01-01

Many intelligent systems that focus on the needs of a human require information about the activities that are being performed by the human. At the core of this capability is activity recognition. Activity recognition techniques have become robust but rarely scale to handle more than a few activities. They also rarely learn from more than one smart home data set because of inherent differences between labeling techniques. In this paper we investigate a data-driven approach to creating an activity taxonomy from sensor data found in disparate smart home datasets. We investigate how the resulting taxonomy can help analyze the relationship between classes of activities. We also analyze how the taxonomy can be used to scale activity recognition to a large number of activity classes and training datasets. We describe our approach and evaluate it on 34 smart home datasets. The results of the evaluation indicate that the hierarchical modeling can reduce training time while maintaining accuracy of the learned model. PMID:25302084

Utilizing a State Level Volunteer Recognition Program at the County Level

ERIC Educational Resources Information Center

McCall, Fran Korthaus; Culp, Ken, III

2013-01-01

Volunteer recognition is an important component of Extension programs. Most land-grant universities have implemented a state volunteer recognition program. Extension professionals, however, are too overburdened with meetings, programs, and activities to effectively recognize volunteers locally. Utilizing a state model is an efficient means of…

Adaptive Learning and Pruning Using Periodic Packet for Fast Invariance Extraction and Recognition

NASA Astrophysics Data System (ADS)

Chang, Sheng-Jiang; Zhang, Bian-Li; Lin, Lie; Xiong, Tao; Shen, Jin-Yuan

2005-02-01

A new learning scheme using a periodic packet as the neuronal activation function is proposed for invariance extraction and recognition of handwritten digits. Simulation results show that the proposed network can extract the invariant feature effectively and improve both the convergence and the recognition rate.

A Survey on Banknote Recognition Methods by Various Sensors

PubMed Central

Lee, Ji Woo; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung

2017-01-01

Despite a decrease in the use of currency due to the recent growth in the use of electronic financial transactions, real money transactions remain very important in the global market. While performing transactions with real money, touching and counting notes by hand, is still a common practice in daily life, various types of automated machines, such as ATMs and banknote counters, are essential for large-scale and safe transactions. This paper presents studies that have been conducted in four major areas of research (banknote recognition, counterfeit banknote detection, serial number recognition, and fitness classification) in the accurate banknote recognition field by various sensors in such automated machines, and describes the advantages and drawbacks of the methods presented in those studies. While to a limited extent some surveys have been presented in previous studies in the areas of banknote recognition or counterfeit banknote recognition, this paper is the first of its kind to review all four areas. Techniques used in each of the four areas recognize banknote information (denomination, serial number, authenticity, and physical condition) based on image or sensor data, and are actually applied to banknote processing machines across the world. This study also describes the technological challenges faced by such banknote recognition techniques and presents future directions of research to overcome them. PMID:28208733

Molecular recognition by gold, silver and copper nanoparticles

PubMed Central

Tauran, Yannick; Brioude, Arnaud; Coleman, Anthony W; Rhimi, Moez; Kim, Beonjoom

2013-01-01

The intrinsic physical properties of the noble metal nanoparticles, which are highly sensitive to the nature of their local molecular environment, make such systems ideal for the detection of molecular recognition events. The current review describes the state of the art concerning molecular recognition of Noble metal nanoparticles. In the first part the preparation of such nanoparticles is discussed along with methods of capping and stabilization. A brief discussion of the three common methods of functionalization: Electrostatic adsorption; Chemisorption; Affinity-based coordination is given. In the second section a discussion of the optical and electrical properties of nanoparticles is given to aid the reader in understanding the use of such properties in molecular recognition. In the main section the various types of capping agents for molecular recognition; nucleic acid coatings, protein coatings and molecules from the family of supramolecular chemistry are described along with their numerous applications. Emphasis for the nucleic acids is on complementary oligonucleotide and aptamer recognition. For the proteins the recognition properties of antibodies form the core of the section. With respect to the supramolecular systems the cyclodextrins, calix[n]arenes, dendrimers, crown ethers and the cucurbitales are treated in depth. Finally a short section deals with the possible toxicity of the nanoparticles, a concern in public health. PMID:23977421

Influence of music with different volumes and styles on recognition activity in humans.

PubMed

Pavlygina, R A; Sakharov, D S; Davydov, V I; Avdonkin, A V

2010-10-01

The efficiency of the recognition of masked visual images (Arabic numerals) increased when accompanied by classical (62 dB) and rock music (25 dB). These changes were accompanied by increases in the coherence of potentials in the frontal areas seen on recognition without music. Changes in intercenter EEG relationships correlated with the formation a dominant at the behavioral level. When loud music (85 dB) and music of other styles was used, these changes in behavior and the EEG were not seen; however, the coherence of potentials in the temporal and motor cortex of the right hemisphere increased and the latent periods of motor reactions of the hands decreased. These results provide evidence that the "recognition" dominant is formed when there are particular ratios of the levels of excitation in the corresponding centers, which should be considered when there is a need to increase the efficiency of recognition activity in humans.

Neuropeptide S interacts with the basolateral amygdala noradrenergic system in facilitating object recognition memory consolidation.

PubMed

Han, Ren-Wen; Xu, Hong-Jiao; Zhang, Rui-San; Wang, Pei; Chang, Min; Peng, Ya-Li; Deng, Ke-Yu; Wang, Rui

2014-01-01

The noradrenergic activity in the basolateral amygdala (BLA) was reported to be involved in the regulation of object recognition memory. As the BLA expresses high density of receptors for Neuropeptide S (NPS), we investigated whether the BLA is involved in mediating NPS's effects on object recognition memory consolidation and whether such effects require noradrenergic activity. Intracerebroventricular infusion of NPS (1nmol) post training facilitated 24-h memory in a mouse novel object recognition task. The memory-enhancing effect of NPS could be blocked by the β-adrenoceptor antagonist propranolol. Furthermore, post-training intra-BLA infusions of NPS (0.5nmol/side) improved 24-h memory for objects, which was impaired by co-administration of propranolol (0.5μg/side). Taken together, these results indicate that NPS interacts with the BLA noradrenergic system in improving object recognition memory during consolidation. Copyright © 2013 Elsevier Inc. All rights reserved.

Divergent short- and long-term effects of acute stress in object recognition memory are mediated by endogenous opioid system activation.

PubMed

Nava-Mesa, Mauricio O; Lamprea, Marisol R; Múnera, Alejandro

2013-11-01

Acute stress induces short-term object recognition memory impairment and elicits endogenous opioid system activation. The aim of this study was thus to evaluate whether opiate system activation mediates the acute stress-induced object recognition memory changes. Adult male Wistar rats were trained in an object recognition task designed to test both short- and long-term memory. Subjects were randomly assigned to receive an intraperitoneal injection of saline, 1 mg/kg naltrexone or 3 mg/kg naltrexone, four and a half hours before the sample trial. Five minutes after the injection, half the subjects were submitted to movement restraint during four hours while the other half remained in their home cages. Non-stressed subjects receiving saline (control) performed adequately during the short-term memory test, while stressed subjects receiving saline displayed impaired performance. Naltrexone prevented such deleterious effect, in spite of the fact that it had no intrinsic effect on short-term object recognition memory. Stressed subjects receiving saline and non-stressed subjects receiving naltrexone performed adequately during the long-term memory test; however, control subjects as well as stressed subjects receiving a high dose of naltrexone performed poorly. Control subjects' dissociated performance during both memory tests suggests that the short-term memory test induced a retroactive interference effect mediated through light opioid system activation; such effect was prevented either by low dose naltrexone administration or by strongly activating the opioid system through acute stress. Both short-term memory retrieval impairment and long-term memory improvement observed in stressed subjects may have been mediated through strong opioid system activation, since they were prevented by high dose naltrexone administration. Therefore, the activation of the opioid system plays a dual modulating role in object recognition memory. Copyright © 2013 Elsevier Inc. All rights reserved.

The Neural Regions Sustaining Episodic Encoding and Recognition of Objects

ERIC Educational Resources Information Center

Hofer, Alex; Siedentopf, Christian M.; Ischebeck, Anja; Rettenbacher, Maria A.; Widschwendter, Christian G.; Verius, Michael; Golaszewski, Stefan M.; Koppelstaetter, Florian; Felber, Stephan; Wolfgang Fleischhacker, W.

2007-01-01

In this functional MRI experiment, encoding of objects was associated with activation in left ventrolateral prefrontal/insular and right dorsolateral prefrontal and fusiform regions as well as in the left putamen. By contrast, correct recognition of previously learned objects (R judgments) produced activation in left superior frontal, bilateral…

Spoken Idiom Recognition: Meaning Retrieval and Word Expectancy

ERIC Educational Resources Information Center

Tabossi, Patrizia; Fanari, Rachele; Wolf, Kinou

2005-01-01

This study investigates recognition of spoken idioms occurring in neutral contexts. Experiment 1 showed that both predictable and non-predictable idiom meanings are available at string offset. Yet, only predictable idiom meanings are active halfway through a string and remain active after the string's literal conclusion. Experiment 2 showed that…

Impact of the Make Healthy Normal mass media campaign (Phase 1) on knowledge, attitudes and behaviours: a cohort study.

PubMed

Kite, James; Gale, Joanne; Grunseit, Anne; Bellew, William; Li, Vincy; Lloyd, Beverley; Maxwell, Michelle; Vineburg, John; Bauman, Adrian

2018-06-01

To determine the impact of the first phase of the Make Healthy Normal mass media campaign on NSW adults' active living and healthy eating knowledge, attitudes, intentions and behaviour. Cohort design with NSW adults, followed up three times over 12 months, with n=939 participants completing all three waves. We used generalised linear mixed models to examine campaign awareness, knowledge, attitudes, intentions and behaviours over time. Campaign recognition built to a reasonable level (45% at Wave 3), although unprompted recall was low (9% at Wave 3). There were significant increases in knowledge of physical activity recommendations (46% to 50%), the health effects of obesity (52% to 64%), and weight loss benefits (53% to 65%), with stronger effects in campaign recognisers. Conversely, we found declines in self-efficacy and intention to increase physical activity (39% to 31%) and decrease soft drink consumption (31% to 24%). Overall, there are some positives for the campaign but intentions need to be a focus of future campaign phases. Continued investment over the medium- to long-term is needed. Mass media campaigns can play a role in obesity prevention but robust evaluations are needed to identify the characteristics of effective campaigns. © 2018 The Authors.

Toward seamless wearable sensing: Automatic on-body sensor localization for physical activity monitoring.

PubMed

Saeedi, Ramyar; Purath, Janet; Venkatasubramanian, Krishna; Ghasemzadeh, Hassan

2014-01-01

Mobile wearable sensors have demonstrated great potential in a broad range of applications in healthcare and wellness. These technologies are known for their potential to revolutionize the way next generation medical services are supplied and consumed by providing more effective interventions, improving health outcomes, and substantially reducing healthcare costs. Despite these potentials, utilization of these sensor devices is currently limited to lab settings and in highly controlled clinical trials. A major obstacle in widespread utilization of these systems is that the sensors need to be used in predefined locations on the body in order to provide accurate outcomes such as type of physical activity performed by the user. This has reduced users' willingness to utilize such technologies. In this paper, we propose a novel signal processing approach that leverages feature selection algorithms for accurate and automatic localization of wearable sensors. Our results based on real data collected using wearable motion sensors demonstrate that the proposed approach can perform sensor localization with 98.4% accuracy which is 30.7% more accurate than an approach without a feature selection mechanism. Furthermore, utilizing our node localization algorithm aids the activity recognition algorithm to achieve 98.8% accuracy (an increase from 33.6% for the system without node localization).

B-cell acquisition of antigen: Sensing the surface.

PubMed

Knight, Andrew M

2015-06-01

B-cell antigen receptor (BCR) recognition and acquisition of antigen by B cells is the essential first step in the generation of effective antibody responses. As B-cell-mediated antigen presentation is also believed to play a significant role in the activation of CD4(+) Th-cell responses, considerable effort has focused on clarifying the nature of antigen/BCR interactions. Following earlier descriptions of interactions of soluble antigens with the BCR, it is now clear that B cells also recognize, physically extract and present antigens that are tethered to, or integral components of, the surfaces or extracellular matrix of other cells. In this issue of the European Journal of Immunology, Zeng et al. [Eur. J. Immunol. 2015. 45: XXXX-XXXX] examine how the physical property or "stiffness" of the surface displaying antigens to B cells influences the B-cell response. This commentary reports that antigen tethered on "less stiff" surfaces induces increased B-cell activation and antibody responses. I then infer how "sensing the surface" by B cells may represent a new component of the immune system's ability to detect "damage," and how this understanding may influence approaches to clinical therapies where immune activity is either unwanted or desired. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The impact of inverted text on visual word processing: An fMRI study.

PubMed

Sussman, Bethany L; Reddigari, Samir; Newman, Sharlene D

2018-06-01

Visual word recognition has been studied for decades. One question that has received limited attention is how different text presentation orientations disrupt word recognition. By examining how word recognition processes may be disrupted by different text orientations it is hoped that new insights can be gained concerning the process. Here, we examined the impact of rotating and inverting text on the neural network responsible for visual word recognition focusing primarily on a region of the occipto-temporal cortex referred to as the visual word form area (VWFA). A lexical decision task was employed in which words and pseudowords were presented in one of three orientations (upright, rotated or inverted). The results demonstrate that inversion caused the greatest disruption of visual word recognition processes. Both rotated and inverted text elicited increased activation in spatial attention regions within the right parietal cortex. However, inverted text recruited phonological and articulatory processing regions within the left inferior frontal and left inferior parietal cortices. Finally, the VWFA was found to not behave similarly to the fusiform face area in that unusual text orientations resulted in increased activation and not decreased activation. It is hypothesized here that the VWFA activation is modulated by feedback from linguistic processes. Copyright © 2018 Elsevier Inc. All rights reserved.

MDMA (Ecstasy) use is associated with reduced BOLD signal change during semantic recognition in abstinent human polydrug users: a preliminary fMRI study

PubMed Central

Raj, Vidya; Liang, Han-Chun; Woodward, Neil D.; Bauernfeind, Amy L.; Lee, Junghee; Dietrich, Mary; Park, Sohee; Cowan, Ronald L.

2011-01-01

Objectives MDMA users have impaired verbal memory, and voxel-based morphometry has demonstrated decreased gray matter in Brodmann area (BA) 18, 21 and 45. Because these regions play a role in verbal memory, we hypothesized that MDMA users would show altered brain activation in these areas during performance of an fMRI task that probed semantic verbal memory. Methods Polysubstance users enriched for MDMA exposure participated in a semantic memory encoding and recognition fMRI task that activated left BA 9, 18, 21/22 and 45. Primary outcomes were percent BOLD signal change in left BA 9, 18, 21/22 and 45, accuracy and response time. Results During semantic recognition, lifetime MDMA use was associated with decreased activation in left BA 9, 18 and 21/22 but not 45. This was partly influenced by contributions from cannabis and cocaine use. MDMA exposure was not associated with accuracy or response time during the semantic recognition task. Conclusions During semantic recognition, MDMA exposure is associated with reduced regional brain activation in regions mediating verbal memory. These findings partially overlap with prior structural evidence for reduced gray matter in MDMA users and may, in part, explain the consistent verbal memory impairments observed in other studies of MDMA users. PMID:19304866

Engineering Translational Activators with CRISPR-Cas System.

PubMed

Du, Pei; Miao, Chensi; Lou, Qiuli; Wang, Zefeng; Lou, Chunbo

2016-01-15

RNA parts often serve as critical components in genetic engineering. Here we report a design of translational activators which is composed of an RNA endoribonuclease (Csy4) and two exchangeable RNA modules. Csy4, a member of Cas endoribonuclease, cleaves at a specific recognition site; this cleavage releases a cis-repressive RNA module (crRNA) from the masked ribosome binding site (RBS), which subsequently allows the downstream translation initiation. Unlike small RNA as a translational activator, the endoribonuclease-based activator is able to efficiently unfold the perfect RBS-crRNA pairing. As an exchangeable module, the crRNA-RBS duplex was forwardly and reversely engineered to modulate the dynamic range of translational activity. We further showed that Csy4 and its recognition site, together as a module, can also be replaced by orthogonal endoribonuclease-recognition site homologues. These modularly structured, high-performance translational activators would endow the programming of gene expression in the translation level with higher feasibility.

The Role of Heart-Rate Variability Parameters in Activity Recognition and Energy-Expenditure Estimation Using Wearable Sensors.

PubMed

Park, Heesu; Dong, Suh-Yeon; Lee, Miran; Youn, Inchan

2017-07-24

Human-activity recognition (HAR) and energy-expenditure (EE) estimation are major functions in the mobile healthcare system. Both functions have been investigated for a long time; however, several challenges remain unsolved, such as the confusion between activities and the recognition of energy-consuming activities involving little or no movement. To solve these problems, we propose a novel approach using an accelerometer and electrocardiogram (ECG). First, we collected a database of six activities (sitting, standing, walking, ascending, resting and running) of 13 voluntary participants. We compared the HAR performances of three models with respect to the input data type (with none, all, or some of the heart-rate variability (HRV) parameters). The best recognition performance was 96.35%, which was obtained with some selected HRV parameters. EE was also estimated for different choices of the input data type (with or without HRV parameters) and the model type (single and activity-specific). The best estimation performance was found in the case of the activity-specific model with HRV parameters. Our findings indicate that the use of human physiological data, obtained by wearable sensors, has a significant impact on both HAR and EE estimation, which are crucial functions in the mobile healthcare system.

Determinants of Job Satisfaction and Turnover Intent in Home Health Workers: The Role of Job Demands and Resources.

PubMed

Jang, Yuri; Lee, Ahyoung A; Zadrozny, Michelle; Bae, Sung-Heui; Kim, Miyong T; Marti, Nathan C

2017-01-01

Based on the job demands-resources (JD-R) model, this study explored the impact of job demands (physical injury and racial/ethnic discrimination) and resources (self-confidence in job performance and recognition by supervisor/organization/society) on home health workers' employee outcomes (job satisfaction and turnover intent). Using data from the National Home Health Aide Survey (N = 3,354), multivariate models of job satisfaction and turnover intent were explored. In both models, the negative impact of demands (physical injury and racial/ethnic discrimination) and the positive impact of resources (self-confidence in job performance and recognition by supervisor and organization) were observed. The overall findings suggest that physical injury and discrimination should be prioritized in prevention and intervention efforts to improve home health workers' safety and well-being. Attention also needs to be paid to ways to bolster work-related efficacy and to promote an organizational culture of appreciation and respect. © The Author(s) 2015.

Personal Identification of Deceased Persons: An Overview of the Current Methods Based on Physical Appearance.

PubMed

Caplova, Zuzana; Obertova, Zuzana; Gibelli, Daniele M; De Angelis, Danilo; Mazzarelli, Debora; Sforza, Chiarella; Cattaneo, Cristina

2018-05-01

The use of the physical appearance of the deceased has become more important because the available antemortem information for comparisons may consist only of a physical description and photographs. Twenty-one articles dealing with the identification based on the physiognomic features of the human body were selected for review and were divided into four sections: (i) visual recognition, (ii) specific facial/body areas, (iii) biometrics, and (iv) dental superimposition. While opinions about the reliability of the visual recognition differ, the search showed that it has been used in mass disasters, even without testing its objectivity and reliability. Specific facial areas being explored for the identification of dead; however, their practical use is questioned, similarly to soft biometrics. The emerging dental superimposition seems to be the only standardized and successfully applied method for identification so far. More research is needed into a potential use of the individualizing features, considering that postmortem changes and technical difficulties may affect the identification. © 2017 American Academy of Forensic Sciences.

Getting into Teams in Physical Education and Exclusion Processes among Students

ERIC Educational Resources Information Center

Grimminger, Elke

2014-01-01

Although splitting up a class into teams is a consistent didactical element in physical education (PE), it is under-investigated in terms of how students handle the social dynamics in these situations. Therefore, the present study examines the strategies of exclusion as markers for non-recognition when students are split up into teams/pairs. The…

Teachers' Continuing Professional Development in Primary Physical Education: Lessons from Present and Past to Inform the Future

ERIC Educational Resources Information Center

Armour, Kathleen M.; Duncombe, Rebecca

2004-01-01

There is a growing recognition that teachers' learning, and effective policies and structures to support it, should be at the heart of government polices to improve standards in education (Day, 1999). In England, the continuing professional development (CPD) landscape for teachers is changing; and professional development in physical education…

Maternal Socialization of Children's Anger, Sadness, and Physical Pain in Two Communities in Gujarat, India

ERIC Educational Resources Information Center

Raval, Vaishali Vidhatri; Martini, Tanya Susan

2009-01-01

Despite the recognition of cultural influences in child socialization, little is known about socialization of emotion in children from different cultures. This study examined (a) Gujarati Indian mothers' reports concerning their beliefs, affective and behavioral responses to their children's displays of anger, sadness, and physical pain, and (b)…

Young People's Perceptions of Mental and Physical Health in the Context of General Wellbeing

ERIC Educational Resources Information Center

Singletary, Joanne H.; Bartle, Craig L.; Svirydzenka, Nadzeya; Suter-Giorgini, Nicola M.; Cashmore, Annette M.; Dogra, Nisha

2015-01-01

Objectives: Increased recognition of the need for health education in schools has seen advances in health literacy in recent years. Most of these have focussed on physical health, whereas education about mental health is generally lacking and focussed on tackling stigma rather than promoting good mental health. This study evaluated a pilot…

Towards NIRS-based hand movement recognition.

PubMed

Paleari, Marco; Luciani, Riccardo; Ariano, Paolo

2017-07-01

This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.

From Caregivers to Peers: Puberty Shapes Human Face Perception.

PubMed

Picci, Giorgia; Scherf, K Suzanne

2016-11-01

Puberty prepares mammals to sexually reproduce during adolescence. It is also hypothesized to invoke a social metamorphosis that prepares adolescents to take on adult social roles. We provide the first evidence to support this hypothesis in humans and show that pubertal development retunes the face-processing system from a caregiver bias to a peer bias. Prior to puberty, children exhibit enhanced recognition for adult female faces. With puberty, superior recognition emerges for peer faces that match one's pubertal status. As puberty progresses, so does the peer recognition bias. Adolescents become better at recognizing faces with a pubertal status similar to their own. These findings reconceptualize the adolescent "dip" in face recognition by showing that it is a recalibration of the face-processing system away from caregivers toward peers. Thus, in addition to preparing the physical body for sexual reproduction, puberty shapes the perceptual system for processing the social world in new ways. © The Author(s) 2016.

An intelligent tool for activity data collection.

PubMed

Sarkar, A M Jehad

2011-01-01

Activity recognition systems using simple and ubiquitous sensors require a large variety of real-world sensor data for not only evaluating their performance but also training the systems for better functioning. However, a tremendous amount of effort is required to setup an environment for collecting such data. For example, expertise and resources are needed to design and install the sensors, controllers, network components, and middleware just to perform basic data collections. It is therefore desirable to have a data collection method that is inexpensive, flexible, user-friendly, and capable of providing large and diverse activity datasets. In this paper, we propose an intelligent activity data collection tool which has the ability to provide such datasets inexpensively without physically deploying the testbeds. It can be used as an inexpensive and alternative technique to collect human activity data. The tool provides a set of web interfaces to create a web-based activity data collection environment. It also provides a web-based experience sampling tool to take the user's activity input. The tool generates an activity log using its activity knowledge and the user-given inputs. The activity knowledge is mined from the web. We have performed two experiments to validate the tool's performance in producing reliable datasets.

Self-face recognition shares brain regions active during proprioceptive illusion in the right inferior fronto-parietal superior longitudinal fasciculus III network.

PubMed

Morita, Tomoyo; Saito, Daisuke N; Ban, Midori; Shimada, Koji; Okamoto, Yuko; Kosaka, Hirotaka; Okazawa, Hidehiko; Asada, Minoru; Naito, Eiichi

2017-04-21

Proprioception is somatic sensation that allows us to sense and recognize position, posture, and their changes in our body parts. It pertains directly to oneself and may contribute to bodily awareness. Likewise, one's face is a symbol of oneself, so that visual self-face recognition directly contributes to the awareness of self as distinct from others. Recently, we showed that right-hemispheric dominant activity in the inferior fronto-parietal cortices, which are connected by the inferior branch of the superior longitudinal fasciculus (SLF III), is associated with proprioceptive illusion (awareness), in concert with sensorimotor activity. Herein, we tested the hypothesis that visual self-face recognition shares brain regions active during proprioceptive illusion in the right inferior fronto-parietal SLF III network. We scanned brain activity using functional magnetic resonance imaging while twenty-two right-handed healthy adults performed two tasks. One was a proprioceptive illusion task, where blindfolded participants experienced a proprioceptive illusion of right hand movement. The other was a visual self-face recognition task, where the participants judged whether an observed face was their own. We examined whether the self-face recognition and the proprioceptive illusion commonly activated the inferior fronto-parietal cortices connected by the SLF III in a right-hemispheric dominant manner. Despite the difference in sensory modality and in the body parts involved in the two tasks, both tasks activated the right inferior fronto-parietal cortices, which are likely connected by the SLF III, in a right-side dominant manner. Here we discuss possible roles for right inferior fronto-parietal activity in bodily awareness and self-awareness. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

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

Acciarri, R.; Adams, C.; An, R.

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

DOE PAGES

Acciarri, R.; Adams, C.; An, R.; ...

2018-01-29

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens ofmore » algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.« less

Magical ideation associated social cognition in adolescents: signs of a negative facial affect recognition deficit.

PubMed

Canli, Derya; Ozdemir, Hatice; Kocak, Orhan Murat

2015-08-01

Studies provide evidence for impaired social cognition in schizotypy and its association with negative symptoms. Cognitive features related to magical ideation - a component of the positive dimension of schizotypy - have been less investigated. We aimed to assess social cognitive functioning among adolescents with high magical ideation scores, mainly focusing on face and emotion recognition. 22 subjects with magical ideation scale scores above the cut off level and 22 controls with lowest scores from among 250 students screened with this scale were included in the study. A face and emotion recognition n-back test, the empathy quotient, theory of mind tests and the Physical Anhedonia Scale were applied to both magical ideation and control groups. The magical ideation group performed significantly worse than controls on both face and emotion recognition tests. Emotion recognition performance was found to be affected by memory load, with sadness, among emotions, revealing a difference between the two groups. Empathy and theory of mind tests did not distinguish the magical ideation group from controls. Our findings provide evidence for a deficit in negative emotion recognition affected by memory load associated with magical ideation in adolescents. Copyright © 2015 Elsevier Inc. All rights reserved.

Functional-anatomic study of episodic retrieval using fMRI. I. Retrieval effort versus retrieval success.

PubMed

Buckner, R L; Koutstaal, W; Schacter, D L; Wagner, A D; Rosen, B R

1998-04-01

A number of recent functional imaging studies have identified brain areas activated during tasks involving episodic memory retrieval. The identification of such areas provides a foundation for targeted hypotheses regarding the more specific contributions that these areas make to episodic retrieval. As a beginning effort toward such an endeavor, whole-brain functional magnetic resonance imaging (fMRI) was used to examine 14 subjects during episodic word recognition in a block-designed fMRI experiment. Study conditions were manipulated by presenting either shallow or deep encoding tasks. This manipulation yielded two recognition conditions that differed with regard to retrieval effort and retrieval success: shallow encoding yielded low levels of recognition success with high levels of retrieval effort, and deep encoding yielded high levels of recognition success with low levels of effort. Many brain areas were activated in common by these two recognition conditions compared to a low-level fixation condition, including left and right prefrontal regions often detected during PET episodic retrieval paradigms (e.g., R. L. Buckner et al., 1996, J. Neurosci. 16, 6219-6235) thereby generalizing these findings to fMRI. Characterization of the activated regions in relation to the separate recognition conditions showed (1) bilateral anterior insular regions and a left dorsal prefrontal region were more active after shallow encoding, when retrieval demanded greatest effort, and (2) right anterior prefrontal cortex, which has been implicated in episodic retrieval, was most active during successful retrieval after deep encoding. We discuss these findings in relation to component processes involved in episodic retrieval and in the context of a companion study using event-related fMRI.

Electrophysiological distinctions between recognition memory with and without awareness

PubMed Central

Ko, Philip C.; Duda, Bryant; Hussey, Erin P.; Ally, Brandon A.

2013-01-01

The influence of implicit memory representations on explicit recognition may help to explain cases of accurate recognition decisions made with high uncertainty. During a recognition task, implicit memory may enhance the fluency of a test item, biasing decision processes to endorse it as “old”. This model may help explain recognition-without-identification, a remarkable phenomenon in which participants make highly accurate recognition decisions despite the inability to identify the test item. The current study investigated whether recognition-without-identification for pictures elicits a similar pattern of neural activity as other types of accurate recognition decisions made with uncertainty. Further, this study also examined whether recognition-without-identification for pictures could be attained by the use of perceptual and conceptual information from memory. To accomplish this, participants studied pictures and then performed a recognition task under difficult viewing conditions while event-related potentials (ERPs) were recorded. Behavioral results showed that recognition was highly accurate even when test items could not be identified, demonstrating recognition-without identification. The behavioral performance also indicated that recognition-without-identification was mediated by both perceptual and conceptual information, independently of one another. The ERP results showed dramatically different memory related activity during the early 300 to 500 ms epoch for identified items that were studied compared to unidentified items that were studied. Similar to previous work highlighting accurate recognition without retrieval awareness, test items that were not identified, but correctly endorsed as “old,” elicited a negative posterior old/new effect (i.e., N300). In contrast, test items that were identified and correctly endorsed as “old,” elicited the classic positive frontal old/new effect (i.e., FN400). Importantly, both of these effects were elicited under conditions when participants used perceptual information to make recognition decisions. Conceptual information elicited very different ERPs than perceptual information, showing that the informational wealth of pictures can evoke multiple routes to recognition even without awareness of memory retrieval. These results are discussed within the context of current theories regarding the N300 and the FN400. PMID:23287567

Process dissociation between contextual retrieval and item recognition.

PubMed

Weis, Susanne; Specht, Karsten; Klaver, Peter; Tendolkar, Indira; Willmes, Klaus; Ruhlmann, Jürgen; Elger, Christian E; Fernández, Guillén

2004-12-22

We employed a source memory task in an event related fMRI study to dissociate MTL processes associated with either contextual retrieval or item recognition. To introduce context during study, stimuli (photographs of buildings and natural landscapes) were transformed into one of four single-color-scales: red, blue, yellow, or green. In the subsequent old/new recognition memory test, all stimuli were presented as gray scale photographs, and old-responses were followed by a four-alternative source judgment referring to the color in which the stimulus was presented during study. Our results suggest a clear-cut process dissociation within the human MTL. While an activity increase accompanies successful retrieval of contextual information, an activity decrease provides a familiarity signal that is sufficient for successful item recognition.

Structural coupling of SH2-kinase domains links Fes and Abl substrate recognition and kinase activation.

PubMed

Filippakopoulos, Panagis; Kofler, Michael; Hantschel, Oliver; Gish, Gerald D; Grebien, Florian; Salah, Eidarus; Neudecker, Philipp; Kay, Lewis E; Turk, Benjamin E; Superti-Furga, Giulio; Pawson, Tony; Knapp, Stefan

2008-09-05

The SH2 domain of cytoplasmic tyrosine kinases can enhance catalytic activity and substrate recognition, but the molecular mechanisms by which this is achieved are poorly understood. We have solved the structure of the prototypic SH2-kinase unit of the human Fes tyrosine kinase, which appears specialized for positive signaling. In its active conformation, the SH2 domain tightly interacts with the kinase N-terminal lobe and positions the kinase alphaC helix in an active configuration through essential packing and electrostatic interactions. This interaction is stabilized by ligand binding to the SH2 domain. Our data indicate that Fes kinase activation is closely coupled to substrate recognition through cooperative SH2-kinase-substrate interactions. Similarly, we find that the SH2 domain of the active Abl kinase stimulates catalytic activity and substrate phosphorylation through a distinct SH2-kinase interface. Thus, the SH2 and catalytic domains of active Fes and Abl pro-oncogenic kinases form integrated structures essential for effective tyrosine kinase signaling.

The effect of background noise on the word activation process in nonnative spoken-word recognition.

PubMed

Scharenborg, Odette; Coumans, Juul M J; van Hout, Roeland

2018-02-01

This article investigates 2 questions: (1) does the presence of background noise lead to a differential increase in the number of simultaneously activated candidate words in native and nonnative listening? And (2) do individual differences in listeners' cognitive and linguistic abilities explain the differential effect of background noise on (non-)native speech recognition? English and Dutch students participated in an English word recognition experiment, in which either a word's onset or offset was masked by noise. The native listeners outperformed the nonnative listeners in all listening conditions. Importantly, however, the effect of noise on the multiple activation process was found to be remarkably similar in native and nonnative listening. The presence of noise increased the set of candidate words considered for recognition in both native and nonnative listening. The results indicate that the observed performance differences between the English and Dutch listeners should not be primarily attributed to a differential effect of noise, but rather to the difference between native and nonnative listening. Additional analyses showed that word-initial information was found to be more important than word-final information during spoken-word recognition. When word-initial information was no longer reliably available word recognition accuracy dropped and word frequency information could no longer be used suggesting that word frequency information is strongly tied to the onset of words and the earliest moments of lexical access. Proficiency and inhibition ability were found to influence nonnative spoken-word recognition in noise, with a higher proficiency in the nonnative language and worse inhibition ability leading to improved recognition performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A test for measuring gustatory function.

PubMed

Smutzer, Gregory; Lam, Si; Hastings, Lloyd; Desai, Hetvi; Abarintos, Ray A; Sobel, Marc; Sayed, Nabil

2008-08-01

The purpose of this study was to determine the usefulness of edible taste strips for measuring human gustatory function. The physical properties of edible taste strips were examined to determine their potential for delivering threshold and suprathreshold amounts of taste stimuli to the oral cavity. Taste strips were then assayed by fluorescence to analyze the uniformity and distribution of bitter tastant in the strips. Finally, taste recognition thresholds for sweet taste were examined to determine whether or not taste strips could detect recognition thresholds that were equal to or better than those obtained from aqueous tests. Edible strips were prepared from pullulan-hydroxypropyl methylcellulose solutions that were dried to a thin film. The maximal amount of a tastant that could be incorporated in a 2.54 cm2 taste strip was identified by including representative taste stimuli for each class of tastant (sweet, sour, salty, bitter, and umami) during strip formation. Distribution of the bitter tastant quinine hydrochloride in taste strips was assayed by fluorescence emission spectroscopy. The efficacy of taste strips for evaluating human gustatory function was examined by using a single series ascending method of limits protocol. Sucrose taste recognition threshold data from edible strips was then compared with results that were obtained from a standard "sip and spit" recognition threshold test. Edible films that formed from a pullulan-hydroxypropyl methylcellulose polymer mixture can be used to prepare clear, thin strips that have essentially no background taste and leave no physical presence after release of tastant. Edible taste strips could uniformly incorporate up to 5% of their composition as tastant. Taste recognition thresholds for sweet taste were over one order of magnitude lower with edible taste strips when compared with an aqueous taste test. Edible taste strips are a highly sensitive method for examining taste recognition thresholds in humans. This new means of presenting taste stimuli should have widespread applications for examining human taste function in the laboratory, in the clinic, or at remote locations.

ERP Correlates of Recognition Memory in Autism Spectrum Disorder

ERIC Educational Resources Information Center

Massand, Esha; Bowler, Dermot M.; Mottron, Laurent; Hosein, Anthony; Jemel, Boutheina

2013-01-01

Recognition memory in autism spectrum disorder (ASD) tends to be undiminished compared to that of typically developing (TD) individuals (Bowler et al. 2007), but it is still unknown whether memory in ASD relies on qualitatively similar or different neurophysiology. We sought to explore the neural activity underlying recognition by employing the…

21 CFR 310.533 - Drug products containing active ingredients offered over-the-counter (OTC) for human use as an...

Code of Federal Regulations, 2010 CFR

2010-04-01

...); however, there are inadequate data to establish general recognition of the effectiveness of this... milligram) but there are inadequate data to establish general recognition of the effectiveness of these... are inadequate safety and effectiveness data to establish general recognition of the safety and/or...

Social Recognition Memory Requires Two Stages of Protein Synthesis in Mice

ERIC Educational Resources Information Center

Wolf, Gerald; Engelmann, Mario; Richter, Karin

2005-01-01

Olfactory recognition memory was tested in adult male mice using a social discrimination task. The testing was conducted to begin to characterize the role of protein synthesis and the specific brain regions associated with activity in this task. Long-term olfactory recognition memory was blocked when the protein synthesis inhibitor anisomycin was…

Anticipation of Negative Pictures Enhances the P2 and P3 in Their Later Recognition

PubMed Central

Lin, Huiyan; Xiang, Jing; Li, Saili; Liang, Jiafeng; Jin, Hua

2015-01-01

Anticipation of emotional pictures has been found to be relevant to the encoding of the pictures as well as their later recognition performance. However, it is as yet unknown whether anticipation modulates neural activity in the later recognition of emotional pictures. To address this issue, participants in the present study were asked to view emotional (negative or neutral) pictures. The picture was preceded by a cue which indicated the emotional content of the picture in half of the trials (the anticipated condition) and without any cues in the other half (the unanticipated condition). Subsequently, participants had to perform an unexpected old/new recognition task in which old and novel pictures were presented without any preceding cues. Electroencephalography data was recorded during the recognition phase. Event-related potential results showed that for negative pictures, P2 and P3 amplitudes were larger in the anticipated as compared to the unanticipated condition; whereas this anticipation effect was not shown for neutral pictures. The present findings suggest that anticipation of negative pictures may enhance neural activity in their later recognition. PMID:26648860

Anticipation of Negative Pictures Enhances the P2 and P3 in Their Later Recognition.

PubMed

Lin, Huiyan; Xiang, Jing; Li, Saili; Liang, Jiafeng; Jin, Hua

2015-01-01

Anticipation of emotional pictures has been found to be relevant to the encoding of the pictures as well as their later recognition performance. However, it is as yet unknown whether anticipation modulates neural activity in the later recognition of emotional pictures. To address this issue, participants in the present study were asked to view emotional (negative or neutral) pictures. The picture was preceded by a cue which indicated the emotional content of the picture in half of the trials (the anticipated condition) and without any cues in the other half (the unanticipated condition). Subsequently, participants had to perform an unexpected old/new recognition task in which old and novel pictures were presented without any preceding cues. Electroencephalography data was recorded during the recognition phase. Event-related potential results showed that for negative pictures, P2 and P3 amplitudes were larger in the anticipated as compared to the unanticipated condition; whereas this anticipation effect was not shown for neutral pictures. The present findings suggest that anticipation of negative pictures may enhance neural activity in their later recognition.

Oxytocin Promotes Facial Emotion Recognition and Amygdala Reactivity in Adults with Asperger Syndrome

PubMed Central

Domes, Gregor; Kumbier, Ekkehardt; Heinrichs, Markus; Herpertz, Sabine C

2014-01-01

The neuropeptide oxytocin has recently been shown to enhance eye gaze and emotion recognition in healthy men. Here, we report a randomized double-blind, placebo-controlled trial that examined the neural and behavioral effects of a single dose of intranasal oxytocin on emotion recognition in individuals with Asperger syndrome (AS), a clinical condition characterized by impaired eye gaze and facial emotion recognition. Using functional magnetic resonance imaging, we examined whether oxytocin would enhance emotion recognition from facial sections of the eye vs the mouth region and modulate regional activity in brain areas associated with face perception in both adults with AS, and a neurotypical control group. Intranasal administration of the neuropeptide oxytocin improved performance in a facial emotion recognition task in individuals with AS. This was linked to increased left amygdala reactivity in response to facial stimuli and increased activity in the neural network involved in social cognition. Our data suggest that the amygdala, together with functionally associated cortical areas mediate the positive effect of oxytocin on social cognitive functioning in AS. PMID:24067301

Oxytocin promotes facial emotion recognition and amygdala reactivity in adults with asperger syndrome.

PubMed

Domes, Gregor; Kumbier, Ekkehardt; Heinrichs, Markus; Herpertz, Sabine C

2014-02-01

The neuropeptide oxytocin has recently been shown to enhance eye gaze and emotion recognition in healthy men. Here, we report a randomized double-blind, placebo-controlled trial that examined the neural and behavioral effects of a single dose of intranasal oxytocin on emotion recognition in individuals with Asperger syndrome (AS), a clinical condition characterized by impaired eye gaze and facial emotion recognition. Using functional magnetic resonance imaging, we examined whether oxytocin would enhance emotion recognition from facial sections of the eye vs the mouth region and modulate regional activity in brain areas associated with face perception in both adults with AS, and a neurotypical control group. Intranasal administration of the neuropeptide oxytocin improved performance in a facial emotion recognition task in individuals with AS. This was linked to increased left amygdala reactivity in response to facial stimuli and increased activity in the neural network involved in social cognition. Our data suggest that the amygdala, together with functionally associated cortical areas mediate the positive effect of oxytocin on social cognitive functioning in AS.

Learning during processing Word learning doesn’t wait for word recognition to finish

PubMed Central

Apfelbaum, Keith S.; McMurray, Bob

2017-01-01

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082

Health Impacts of Yoga and Pranayama: A State-of-the-Art Review

PubMed Central

Sengupta, Pallav

2012-01-01

Thousands of years ago yoga originated in India, and in present day and age, an alarming awareness was observed in health and natural remedies among people by yoga and pranayama which has been proven an effective method for improving health in addition to prevention and management of diseases. With increasing scientific research in yoga, its therapeutic aspects are also being explored. Yoga is reported to reduce stress and anxiety, improves autonomic functions by triggering neurohormonal mechanisms by the suppression of sympathetic activity, and even, now-a-days, several reports suggested yoga is beneficial for physical health of cancer patients. Such global recognition of yoga also testifies to India's growing cultural influence. PMID:22891145

Proceedings of the Symposium on the Role of Behavioral Science in Physical Security (5th Annual) Held at Gaithersburg, Maryland, June 11-12, 1980

DTIC Science & Technology

1981-06-01

targets that have been cali- brated for different types of search tasks. Recognition tests might include visual recognition of site personnel, auditory ...Strength o Physiological processes o Auditory processes o Visual processes o Tactile sense o Psychomotor processes o Tolerance to environment o Learning...sensitive" to an easily measurable degree, and another third at a more subliminal level. This sensitivity is even further height- ened in individuals by the

Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring

DTIC Science & Technology

2015-10-02

ratio or physical layout than the training sample, or new vs old bananas . For our system, this is similar the multimodal case mentioned above; however...different modes. Foods with multiple “types” such as green, yellow, and brown bananas are seamlessly handled as well. Secondly, with hundreds or thousands...Recognition and Classification of Food Grains, Fruits and Flowers Using Machine Vision. INTERNATIONAL JOURNAL OF FOOD ENGINEERING, 5(4), 2009. [155] T. E

Statistical assessment of speech system performance

NASA Technical Reports Server (NTRS)

Moshier, Stephen L.

1977-01-01

Methods for the normalization of performance tests results of speech recognition systems are presented. Technological accomplishments in speech recognition systems, as well as planned research activities are described.

Physical approaches to biomaterial design

PubMed Central

Mitragotri, Samir; Lahann, Joerg

2009-01-01

The development of biomaterials for drug delivery, tissue engineering and medical diagnostics has traditionally been based on new chemistries. However, there is growing recognition that the physical as well as the chemical properties of materials can regulate biological responses. Here, we review this transition with regard to selected physical properties including size, shape, mechanical properties, surface texture and compartmentalization. In each case, we present examples demonstrating the significance of these properties in biology. We also discuss synthesis methods and biological applications for designer biomaterials, which offer unique physical properties. PMID:19096389

Eugene P. Wigner's Visionary Contributions to Generations-I through IV Fission Reactors

NASA Astrophysics Data System (ADS)

Carré, Frank

2014-09-01

Among Europe's greatest scientists who fled to Britain and America in the 1930s, Eugene P. Wigner made instrumental advances in reactor physics, reactor design and technology, and spent nuclear fuel processing for both purposes of developing atomic weapons during world-war II and nuclear power afterwards. Wigner who had training in chemical engineering and self-education in physics first gained recognition for his remarkable articles and books on applications of Group theory to Quantum mechanics, Solid state physics and other topics that opened new branches of Physics.

Interventional nephrology: Physical examination as a tool for surveillance for the hemodialysis arteriovenous access.

PubMed

Salman, Loay; Beathard, Gerald

2013-07-01

The prospective recognition of stenosis affecting dialysis vascular access and its prospective treatment is important in the management of the hemodialysis patient. Surveillance by physical examination is easily learned, easily performed, quickly done, and economical. In addition, it has a level of accuracy and reliability equivalent to other approaches that require special instrumentation. Physical examination should be part of any education to all hemodialysis care givers. This review presents the basic principles of physical examination of the hemodialysis vascular access and discusses the evidence behind its value.

Prediction of activity type in preschool children using machine learning techniques.

PubMed

Hagenbuchner, Markus; Cliff, Dylan P; Trost, Stewart G; Van Tuc, Nguyen; Peoples, Gregory E

2015-07-01

Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Eleven children aged 3-6 years (mean age=4.8±0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

The contribution of conceptual frameworks to knowledge translation interventions in physical therapy.

PubMed

Hudon, Anne; Gervais, Mathieu-Joël; Hunt, Matthew

2015-04-01

There is growing recognition of the importance of knowledge translation activities in physical therapy to ensure that research findings are integrated into clinical practice, and increasing numbers of knowledge translation interventions are being conducted. Although various frameworks have been developed to guide and facilitate the process of translating knowledge into practice, these tools have been infrequently used in physical therapy knowledge translation studies to date. Knowledge translation in physical therapy implicates multiple stakeholders and environments and involves numerous steps. In light of this complexity, the use of explicit conceptual frameworks by clinicians and researchers conducting knowledge translation interventions is associated with a range of potential benefits. This perspective article argues that such frameworks are important resources to promote the uptake of new evidence in physical therapist practice settings. Four key benefits associated with the use of conceptual frameworks in designing and implementing knowledge translation interventions are identified, and limits related to their use are considered. A sample of 5 conceptual frameworks is evaluated, and how they address common barriers to knowledge translation in physical therapy is assessed. The goal of this analysis is to provide guidance to physical therapists seeking to identify a framework to support the design and implementation of a knowledge translation intervention. Finally, the use of a conceptual framework is illustrated through a case example. Increased use of conceptual frameworks can have a positive impact on the field of knowledge translation in physical therapy and support the development and implementation of robust and effective knowledge translation interventions that help span the research-practice gap. © 2015 American Physical Therapy Association.

Rapid effects of dorsal hippocampal G-protein coupled estrogen receptor on learning in female mice.

PubMed

Lymer, Jennifer; Robinson, Alana; Winters, Boyer D; Choleris, Elena

2017-03-01

Through rapid mechanisms of action, estrogens affect learning and memory processes. It has been shown that 17β-estradiol and an Estrogen Receptor (ER) α agonist enhances performance in social recognition, object recognition, and object placement tasks when administered systemically or infused in the dorsal hippocampus. In contrast, systemic and dorsal hippocampal ERβ activation only promote spatial learning. In addition, 17β-estradiol, the ERα and the G-protein coupled estrogen receptor (GPER) agonists increase dendritic spine density in the CA1 hippocampus. Recently, we have shown that selective systemic activation of the GPER also rapidly facilitated social recognition, object recognition, and object placement learning in female mice. Whether activation the GPER specifically in the dorsal hippocampus can also rapidly improve learning and memory prior to acquisition is unknown. Here, we investigated the rapid effects of infusion of the GPER agonist, G-1 (dose: 50nM, 100nM, 200nM), in the dorsal hippocampus on social recognition, object recognition, and object placement learning tasks in home cage. These paradigms were completed within 40min, which is within the range of rapid estrogenic effects. Dorsal hippocampal administration of G-1 improved social (doses: 50nM, 200nM G-1) and object (dose: 200nM G-1) recognition with no effect on object placement. Additionally, when spatial cues were minimized by testing in a Y-apparatus, G-1 administration promoted social (doses: 100nM, 200nM G-1) and object (doses: 50nM, 100nM, 200nM G-1) recognition. Therefore, like ERα, the GPER in the hippocampus appears to be sufficient for the rapid facilitation of social and object recognition in female mice, but not for the rapid facilitation of object placement learning. Thus, the GPER in the dorsal hippocampus is involved in estrogenic mediation of learning and memory and these effects likely occur through rapid signalling mechanisms. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design and test of a hybrid foot force sensing and GPS system for richer user mobility activity recognition.

PubMed

Zhang, Zelun; Poslad, Stefan

2013-11-01

Wearable and accompanied sensors and devices are increasingly being used for user activity recognition. However, typical GPS-based and accelerometer-based (ACC) methods face three main challenges: a low recognition accuracy; a coarse recognition capability, i.e., they cannot recognise both human posture (during travelling) and transportation mode simultaneously, and a relatively high computational complexity. Here, a new GPS and Foot-Force (GPS + FF) sensor method is proposed to overcome these challenges that leverages a set of wearable FF sensors in combination with GPS, e.g., in a mobile phone. User mobility activities that can be recognised include both daily user postures and common transportation modes: sitting, standing, walking, cycling, bus passenger, car passenger (including private cars and taxis) and car driver. The novelty of this work is that our approach provides a more comprehensive recognition capability in terms of reliably recognising both human posture and transportation mode simultaneously during travel. In addition, by comparing the new GPS + FF method with both an ACC method (62% accuracy) and a GPS + ACC based method (70% accuracy) as baseline methods, it obtains a higher accuracy (95%) with less computational complexity, when tested on a dataset obtained from ten individuals.

Benefits of adaptive FM systems on speech recognition in noise for listeners who use hearing aids.

PubMed

Thibodeau, Linda

2010-06-01

To compare the benefits of adaptive FM and fixed FM systems through measurement of speech recognition in noise with adults and students in clinical and real-world settings. Five adults and 5 students with moderate-to-severe hearing loss completed objective and subjective speech recognition in noise measures with the 2 types of FM processing. Sentence recognition was evaluated in a classroom for 5 competing noise levels ranging from 54 to 80 dBA while the FM microphone was positioned 6 in. from the signal loudspeaker to receive input at 84 dB SPL. The subjective measures included 2 classroom activities and 6 auditory lessons in a noisy, public aquarium. On the objective measures, adaptive FM processing resulted in significantly better speech recognition in noise than fixed FM processing for 68- and 73-dBA noise levels. On the subjective measures, all individuals preferred adaptive over fixed processing for half of the activities. Adaptive processing was also preferred by most (8-9) individuals for the remaining 4 activities. The adaptive FM processing resulted in significant improvements at the higher noise levels and was preferred by the majority of participants in most of the conditions.

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar

PubMed Central

Shin, Young Hoon; Seo, Jiwon

2016-01-01

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker’s vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing. PMID:27801867

Towards Contactless Silent Speech Recognition Based on Detection of Active and Visible Articulators Using IR-UWB Radar.

PubMed

Shin, Young Hoon; Seo, Jiwon

2016-10-29

People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker's vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing.

Retaining undergrads, and preparing grads for academic jobs: the PFPF program

NASA Astrophysics Data System (ADS)

Stewart, Gay

2001-04-01

When we embarked upon an NSF supported curriculum development project, it became clear that the greatest need for educational reform to be sustained was for future faculty to be prepared to be as professional about roles as educators as roles as researchers. A new faculty member may find themselves preparing to teach a class for the first time, with little guidance. Complaints employers have about those hired for research positions involve interpersonal skills. More researchers are being called upon to do outreach. Teaching and outreach activities develop these skills. We are adding these kinds of activities to the graduate program, with the same sort of mentoring that accompanies the development of research skills, without extending the time to degree. Also, a new MA for those that find themselves unmotivated by research, but still loving physics, provides a route straight into teaching at very low resource cost. These interests helped us become one of four pilot sites for the Preparing Future Physics Faculty program. The early results of our efforts will be presented: increased undergraduate enrollment and satisfaction with the departmental climate, recognition from the university administration for doing a superior job in student preparation, and graduate students more comfortable in the classroom.

Retaining undergrads, and preparing grads for academic jobs: the PFPF program

NASA Astrophysics Data System (ADS)

Stewart, Gay

2001-03-01

When we embarked upon an NSF supported curriculum development project, it became clear that the greatest need for educational reform to be sustained was for future faculty to be prepared to be as professional about roles as educators as roles as researchers. A new faculty member may find themselves preparing to teach a class for the first time, with little guidance. Complaints employers have about those hired for research positions involve interpersonal skills. More researchers are being called upon to do outreach. Teaching and outreach activities develop these skills. We are adding these kinds of activities to the graduate program, with the same sort of mentoring that accompanies the development of research skills, without extending the time to degree. Also, a new MA for those that find themselves unmotivated by research, but still loving physics, provides a route straight into teaching at very low resource cost. These interests helped us become one of four pilot sites for the Preparing Future Physics Faculty program. The early results of our efforts will be presented: increased undergraduate enrollment and satisfaction with the departmental climate, recognition from the university administration for doing a superior job in student preparation, and graduate students more comfortable in the classroom.

Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

PubMed Central

Ordóñez, Francisco Javier; Roggen, Daniel

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we propose a generic deep framework for activity recognition based on convolutional and LSTM recurrent units, which: (i) is suitable for multimodal wearable sensors; (ii) can perform sensor fusion naturally; (iii) does not require expert knowledge in designing features; and (iv) explicitly models the temporal dynamics of feature activations. We evaluate our framework on two datasets, one of which has been used in a public activity recognition challenge. Our results show that our framework outperforms competing deep non-recurrent networks on the challenge dataset by 4% on average; outperforming some of the previous reported results by up to 9%. Our results show that the framework can be applied to homogeneous sensor modalities, but can also fuse multimodal sensors to improve performance. We characterise key architectural hyperparameters’ influence on performance to provide insights about their optimisation. PMID:26797612

Simple thermal to thermal face verification method based on local texture descriptors

NASA Astrophysics Data System (ADS)

Grudzien, A.; Palka, Norbert; Kowalski, M.

2017-08-01

Biometrics is a science that studies and analyzes physical structure of a human body and behaviour of people. Biometrics found many applications ranging from border control systems, forensics systems for criminal investigations to systems for access control. Unique identifiers, also referred to as modalities are used to distinguish individuals. One of the most common and natural human identifiers is a face. As a result of decades of investigations, face recognition achieved high level of maturity, however recognition in visible spectrum is still challenging due to illumination aspects or new ways of spoofing. One of the alternatives is recognition of face in different parts of light spectrum, e.g. in infrared spectrum. Thermal infrared offer new possibilities for human recognition due to its specific properties as well as mature equipment. In this paper we present the scheme of subject's verification methodology by using facial images in thermal range. The study is focused on the local feature extraction methods and on the similarity metrics. We present comparison of two local texture-based descriptors for thermal 1-to-1 face recognition.

Response to displaced neighbours in a territorial songbird with a large repertoire

NASA Astrophysics Data System (ADS)

Briefer, Elodie; Aubin, Thierry; Rybak, Fanny

2009-09-01

Neighbour recognition allows territory owners to modulate their territorial response according to the threat posed by each neighbour and thus to reduce the costs associated with territorial defence. Individual acoustic recognition of neighbours has been shown in numerous bird species, but few of them had a large repertoire. Here, we tested individual vocal recognition in a songbird with a large repertoire, the skylark Alauda arvensis. We first examined the physical basis for recognition in the song, and we then experimentally tested recognition by playing back songs of adjacent neighbours and strangers. Males showed a lower territorial response to adjacent neighbours than to strangers when we broadcast songs from the shared boundary. However, when we broadcast songs from the opposite boundary, males showed a similar response to neighbours and strangers, indicating a spatial categorisation of adjacent neighbours’ songs. Acoustic analyses revealed that males could potentially use the syntactical arrangement of syllables in sequences to identify the songs of their neighbours. Neighbour interactions in skylarks are thus subtle relationships that can be modulated according to the spatial position of each neighbour.

Automated information-analytical system for thunderstorm monitoring and early warning alarms using modern physical sensors and information technologies with elements of artificial intelligence

NASA Astrophysics Data System (ADS)

Boldyreff, Anton S.; Bespalov, Dmitry A.; Adzhiev, Anatoly Kh.

2017-05-01

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

Arousal Rather than Basic Emotions Influence Long-Term Recognition Memory in Humans

PubMed Central

Marchewka, Artur; Wypych, Marek; Moslehi, Abnoos; Riegel, Monika; Michałowski, Jarosław M.; Jednoróg, Katarzyna

2016-01-01

Emotion can influence various cognitive processes, however its impact on memory has been traditionally studied over relatively short retention periods and in line with dimensional models of affect. The present study aimed to investigate emotional effects on long-term recognition memory according to a combined framework of affective dimensions and basic emotions. Images selected from the Nencki Affective Picture System were rated on the scale of affective dimensions and basic emotions. After 6 months, subjects took part in a surprise recognition test during an fMRI session. The more negative the pictures the better they were remembered, but also the more false recognitions they provoked. Similar effects were found for the arousal dimension. Recognition success was greater for pictures with lower intensity of happiness and with higher intensity of surprise, sadness, fear, and disgust. Consecutive fMRI analyses showed a significant activation for remembered (recognized) vs. forgotten (not recognized) images in anterior cingulate and bilateral anterior insula as well as in bilateral caudate nuclei and right thalamus. Further, arousal was found to be the only subjective rating significantly modulating brain activation. Higher subjective arousal evoked higher activation associated with memory recognition in the right caudate and the left cingulate gyrus. Notably, no significant modulation was observed for other subjective ratings, including basic emotion intensities. These results emphasize the crucial role of arousal for long-term recognition memory and support the hypothesis that the memorized material, over time, becomes stored in a distributed cortical network including the core salience network and basal ganglia. PMID:27818626

Arousal Rather than Basic Emotions Influence Long-Term Recognition Memory in Humans.

PubMed

Marchewka, Artur; Wypych, Marek; Moslehi, Abnoos; Riegel, Monika; Michałowski, Jarosław M; Jednoróg, Katarzyna

2016-01-01

Emotion can influence various cognitive processes, however its impact on memory has been traditionally studied over relatively short retention periods and in line with dimensional models of affect. The present study aimed to investigate emotional effects on long-term recognition memory according to a combined framework of affective dimensions and basic emotions. Images selected from the Nencki Affective Picture System were rated on the scale of affective dimensions and basic emotions. After 6 months, subjects took part in a surprise recognition test during an fMRI session. The more negative the pictures the better they were remembered, but also the more false recognitions they provoked. Similar effects were found for the arousal dimension. Recognition success was greater for pictures with lower intensity of happiness and with higher intensity of surprise, sadness, fear, and disgust. Consecutive fMRI analyses showed a significant activation for remembered (recognized) vs. forgotten (not recognized) images in anterior cingulate and bilateral anterior insula as well as in bilateral caudate nuclei and right thalamus. Further, arousal was found to be the only subjective rating significantly modulating brain activation. Higher subjective arousal evoked higher activation associated with memory recognition in the right caudate and the left cingulate gyrus. Notably, no significant modulation was observed for other subjective ratings, including basic emotion intensities. These results emphasize the crucial role of arousal for long-term recognition memory and support the hypothesis that the memorized material, over time, becomes stored in a distributed cortical network including the core salience network and basal ganglia.

Normative Approaches to Justice in Physical Education for Pupils with Physical Disabilities--Dilemmas of Recognition and Redistribution

ERIC Educational Resources Information Center

Jerlinder, Kajsa; Danermark, Berth; Gill, Peter

2009-01-01

Seeking social justice in education for pupils with disabilities creates certain dilemmas. A "school for all" means that educators are faced with the dilemma whereby the notion of "disability" is perceived as ought not to matter but where in actual fact it seems to matter very much! This article explores ways out of this…

Preface of 16th International conference on Defects, Recognition, Imaging and Physics in Semiconductors

NASA Astrophysics Data System (ADS)

Yang, Deren; Xu, Ke

2016-11-01

The 16th International conference on Defects-Recognition, Imaging and Physics in Semiconductors (DRIP-XVI) was held at the Worldhotel Grand Dushulake in Suzhou, China from 6th to 10th September 2015, around the 30th anniversary of the first DRIP conference. It was hosted by the Suzhou Institute of Nano-tech and Nano-bionics (SINANO), Chinese Academy of Sciences. On this occasion, about one hundred participants from nineteen countries attended the event. And a wide range of subjects were addressed during the conference: physics of point and extended defects in semiconductors: origin, electrical, optical and magnetic properties of defects; diagnostics techniques of crystal growth and processing of semiconductor materials (in-situ and process control); device imaging and mapping to evaluate performance and reliability; defect analysis in degraded optoelectronic and electronic devices; imaging techniques and instruments (proximity probe, x-ray, electron beam, non-contact electrical, optical and thermal imaging techniques, etc.); new frontiers of atomic-scale-defect assessment (STM, AFM, SNOM, ballistic electron energy microscopy, TEM, etc.); new approaches for multi-physic-parameter characterization with Nano-scale space resolution. Within these subjects, there were 58 talks, of which 18 invited, and 50 posters.

Beyond Babies and Orgasm.

ERIC Educational Resources Information Center

Weg, Ruth B.

1982-01-01

Debunks the mythology that the older woman is sexually neuter. Describes the older woman's physical and emotional characteristics and needs and encourages the recognition of qualities of affection, sensuality, and sexuality in later life. (SK)

Gender recognition from unconstrained and articulated human body.

PubMed

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Gender Recognition from Unconstrained and Articulated Human Body

PubMed Central

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition. PMID:24977203

Structural insight into RNA recognition motifs: versatile molecular Lego building blocks for biological systems.

PubMed

Muto, Yutaka; Yokoyama, Shigeyuki

2012-01-01

'RNA recognition motifs (RRMs)' are common domain-folds composed of 80-90 amino-acid residues in eukaryotes, and have been identified in many cellular proteins. At first they were known as RNA binding domains. Through discoveries over the past 20 years, however, the RRMs have been shown to exhibit versatile molecular recognition activities and to behave as molecular Lego building blocks to construct biological systems. Novel RNA/protein recognition modes by RRMs are being identified, and more information about the molecular recognition by RRMs is becoming available. These RNA/protein recognition modes are strongly correlated with their biological significance. In this review, we would like to survey the recent progress on these versatile molecular recognition modules. Copyright © 2012 John Wiley & Sons, Ltd.