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2018 Index IEEE Journal of Biomedical and Health Informatics Vol. 22

2018 IEEE journal of biomedical and health informatics  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  ., +, JBHI Sept. 2018 1362-1372 Inertial systems Smartphone Orientation Estimation Algorithm Combining Kalman Filter With Gradient Descent.  ... 
doi:10.1109/jbhi.2018.2880294 fatcat:3cy3e7no55emlgbxfe3mwef3vu

Deep Learning for Monitoring of Human Gait: A Review

Abdullah S Alharthi, Syed U Yunas, Krikor B Ozanyan
2019 IEEE Sensors Journal  
The modalities for capturing the gait data are grouped according to the sensing technology: video sequences, wearable sensors, and floor sensors, as well as the publicly available datasets.  ...  data and the motivation for multi-sensor, multi-modality fusion.  ...  An LSTM-based gait-phase recognition algorithm is used to train the labeled data.  ... 
doi:10.1109/jsen.2019.2928777 fatcat:seb7vcs77bae7ixbpkajo3ysee

Human Action Recognition with RGB-D Sensors [chapter]

Enea Cippitelli, Ennio Gambi, Susanna Spinsante
2017 Motion Tracking and Gesture Recognition  
Furthermore, the availability of depth data allows to implement solutions that are unobtrusive and privacy preserving with respect to classic video-based analysis.  ...  The release of inexpensive RGB-D sensors fostered researchers working in this field because depth data simplify the processing of visual data that could be otherwise difficult using classic RGB devices  ...  Wearable inertial sensors are quite cheap and generate a limited amount of data that can be processed easily with respect to video data, even if they do not provide information about the context.  ... 
doi:10.5772/68121 fatcat:y263o6ywb5byln3zpemkfgym24

Multi-sensor fusion based on multiple classifier systems for human activity identification

Henry Friday Nweke, Ying Wah Teh, Ghulam Mujtaba, Uzoma Rita Alo, Mohammed Ali Al-garadi
2019 Human-Centric Computing and Information Sciences  
To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature  ...  To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection  ...  Acknowledgements The authors would like to thank University of Malaya for sponsoring the paper through the BKP Special grants and researchers that collected the datasets that were used to support this  ... 
doi:10.1186/s13673-019-0194-5 fatcat:oif3o7dfhzdwhcqeept7t5jypq

2020 Index IEEE Journal of Biomedical and Health Informatics Vol. 24

2020 IEEE journal of biomedical and health informatics  
Algorithm; JBHI Dec. 2020 3630-3641 Jiang, S., see Zhou, Z., JBHI Jan. 2020 194-204 Jiang, X., see Zhou, Z., JBHI April 2020 943-956 Jiang, Y., see Yu, R., JBHI Feb. 2020 486-492 Jiao, C., Gao,  ...  ., and Inan, O.T., A Globalized Model for Mapping Wearable Seismocardiogram Signals to Whole-Body Ballistocardiogram Signals Based on Deep Learning; JBHI May 2020 1296-1309 Herskovic, V., see Saint-Pierre  ...  ., +, JBHI July 2020 1994-2005 Detection of Gait From Continuous Inertial Sensor Data Using Harmonic Frequencies.  ... 
doi:10.1109/jbhi.2020.3048808 fatcat:iifrkwtzazdmboabdqii7x5ukm

From Emotions to Mood Disorders: A Survey on Gait Analysis Methodology

Fani Deligianni, Yao Guo, Guang-Zhong Yang
2019 IEEE journal of biomedical and health informatics  
Here we review evidence that demonstrates the relationship between gait, emotions and mood disorders, highlighting the potential of a multimodal approach that couples gait data with physiological signals  ...  Gait and body movements can be affected by mood disorders, and thus they can be used as a surrogate sign, as well as an objective index for pervasive monitoring of emotion and mood disorders in daily life  ...  Lately, Inertial Measurement Units (IMUs) sensors have also been successfully used to study human gait [93] - [95] .  ... 
doi:10.1109/jbhi.2019.2938111 pmid:31502995 fatcat:c2h43ezryrbuva44okrxhky2iq

WearableDL: Wearable Internet-of-Things and Deep Learning for Big Data Analytics—Concept, Literature, and Future

Aras R. Dargazany, Paolo Stegagno, Kunal Mankodiya
2018 Mobile Information Systems  
This article eventually develops an outlook and provides insightful suggestions for WearableDL and its application in the field of big data analytics.  ...  to the brain) represents Internet-of-things for fog computing and big data flow/transfer. (3) Peripheral sensory and motor nerves (components of the peripheral nervous system (PNS)) represent wearable  ...  Deep CNN is used for stride length estimation to map stride-specific inertial sensor data to the resulting stride length. I. DL for mobile gait analytics J.  ... 
doi:10.1155/2018/8125126 fatcat:ty3a7n4in5aahbqyl7wum5vonq

Automated Human Activity Recognition by Colliding Bodies Optimization-based Optimal Feature Selection with Recurrent Neural Network [article]

Pankaj Khatiwada, Ayan Chatterjee, Matrika Subedi
2021 arXiv   pre-print
Hence, this paper tempts to implement the HAR system using deep learning with the data collected from smart sensors that are publicly available in the UC Irvine Machine Learning Repository (UCI).  ...  In smart healthcare, Human Activity Recognition (HAR) is considered to be an efficient model in pervasive computation from sensor readings.  ...  CBO [18] is a populationbased evolutionary algorithm that uses the concept of the laws of the collision of two objects.  ... 
arXiv:2010.03324v3 fatcat:4mbshp5ay5a6jbis3ob7pbfldi

MEMS Sensor Technologies for Human Centred Applications in Healthcare, Physical Activities, Safety and Environmental Sensing: A Review on Research Activities in Italy

Gastone Ciuti, Leonardo Ricotti, Arianna Menciassi, Paolo Dario
2015 Sensors  
Monitoring and precisely quantifying users' physical activity with inertial measurement unit-based devices, for instance, has also proven to be important in health management of patients affected by chronic  ...  Finally, the paper will depict the future perspective of sensor technologies and corresponding exploitation opportunities, again with a specific focus on Italy.  ...  Acknowledgments The authors wish to thank the Micromachine Center of Japan (MMC-http://www.mmc.or.jp/e/) and the organizers and delegations of the Micromachine Summits (http://mmc.la.coocan.jp/summit/)  ... 
doi:10.3390/s150306441 pmid:25808763 pmcid:PMC4435109 fatcat:k66xoar3kjhgbj6fe5fmvsaleq

Machine Learning in Manufacturing Ergonomics: Recent Advances, Challenges, and Opportunities

Sujee Lee, Li Liu, Robert Radwin, Jingshan Li
2021 IEEE Robotics and Automation Letters  
ergonomics, and manufacturing systems perspectives.  ...  To incentivize future research in this area, this letter reviews the recent advances of ML applications in manufacturing ergonomics, and discusses future research opportunities and challenges from ML,  ...  Moreover, using the data collected from sensors on screwdrivers, paper [8] studies manual activity recognition by comparing datasets covering different tool movements, sensor placements with different  ... 
doi:10.1109/lra.2021.3084881 fatcat:hqdsvn3v7vcepfv5orvqlp57lu

Bi-Modality Anxiety Emotion Recognition with PSO-CSVM [chapter]

Ruihu Wang, Bin Fang
2011 State of the art in Biometrics  
Multimodal human emotion recognition involving facial expression and motion recognition could be applied to intelligent video surveillance system to provide an early warning mechanism in case of potential  ...  CMU's Video Surveillance and Monitoring (VSAM) project [26] and MIT AI Lab's Forest of Sensors project [27] are examples of recent research efforts in this field.  ... 
doi:10.5772/18245 fatcat:7wihv4lrhzaj5atv6tmywh7rxq

Fusion of Neuro-Signals and Dynamic Signatures for Person Authentication

Pradeep Kumar, Rajkumar Saini, Barjinder Kaur, Partha Pratim Roy, Erik Scheme
2019 Sensors  
With growing levels of private data readily available across the internet, a more robust authentication system is needed for use in emerging technologies and mobile applications.  ...  in 3.75% FAR and 1.87% HTER with 100% TPR for forgery attempts.  ...  A multimodal gait recognition system was proposed in [18] , where a decision fusion approach was used to combine the results of inertial sensors (accelerometer, gyroscope, and magnetometer) and video  ... 
doi:10.3390/s19214641 pmid:31661761 pmcid:PMC6864782 fatcat:tviluxng5ffxvihaail3cotfti

2021 Index IEEE Robotics and Automation Letters Vol. 6

2021 IEEE Robotics and Automation Letters  
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination.  ...  The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages.  ...  Shape Recognition of a Tensegrity With Soft Sensor Threads and Artificial Muscles Using a Recurrent Neural Network.  ... 
doi:10.1109/lra.2021.3119726 fatcat:lsnerdofvveqhlv7xx7gati2xu

Force Controlled Hexapod Walking [chapter]

Shalutha De Silva, Joaquin Sitte
2012 Advances in Autonomous Mini Robots  
A new joint controller is proposed and demonstrated for a hexapod that uses joint angles and force feedback information in order to generate a torque.  ...  The approach in this study is to use joint angles and leg reaction forces as inputs to the new controller and produce a torque as the output, which drives the joint.  ...  Prediction, data mining and classification, and pattern recognition are some of these problems. One method of addressing this problem is by using ANNs.  ... 
doi:10.1007/978-3-642-27482-4_25 fatcat:sykt2gahy5ervoo5xx4bdc3hja

2019 Index IEEE Transactions on Intelligent Transportation Systems Vol. 20

2019 IEEE transactions on intelligent transportation systems (Print)  
., and Ma, J  ...  ., +, TITS April 2019 1341-1352 Image sensors Benchmark Data and Method for Real-Time People Counting in Cluttered Scenes Using Depth Sensors.  ...  ., +, TITS Aug. 2019 3038-3048 Benchmark Data and Method for Real-Time People Counting in Cluttered Scenes Using Depth Sensors.  ... 
doi:10.1109/tits.2020.2966388 fatcat:xkvww7uabzhlzgfz3yiecyb75y
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