NDLI: Muscle Fatigue Detection in EMG Using Time–Frequency Methods, ICA and Neural Networks

Content Provider	Springer Nature Link
Author	Subasi, Abdulhamit Kiymik, M. Kemal
Copyright Year	2009
Abstract	The electromyography (EMG) signals give information about different features of muscle function. Real-time measurements of EMG have been used to observe the dissociation between the electrical and mechanical measures that occurs with fatigue. The purpose of this study was to detect fatigue of biceps brachia muscle using time–frequency methods and independent component analysis (ICA). In order to realize this aim, EMG activity obtained from activated muscle during a phasic voluntary movement was recorded for 14 healthy young persons and EMG signals were observed in time–frequency domain for determination of fatigue. Time–frequency methods are used for the processing of signals that are non-stationary and time varying. The EMG contains transient signals related to muscle activity. The proposed method for the detection of muscle fatigue is automated by using artificial neural networks (ANN). The results show that ANN with ICA separates EMG signals from fresh and fatigued muscles, hence providing a visualization of the onset of fatigue over time. The system is adaptable to different subjects and conditions since the techniques used are not subject or workload regime specific.
Starting Page	777
Ending Page	785
Page Count	9
File Format	PDF
ISSN	01485598
Journal	Journal of Medical Systems
Volume Number	34
Issue Number	4
e-ISSN	1573689X
Language	English
Publisher	Springer US
Publisher Date	2009-04-28
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Electromyography (EMG) Muscle fatigue Time–frequency methods Independent Component Analysis (ICA) Artificial Neural Network (ANN) Health Informatics Statistics for Life Sciences, Medicine, Health Sciences
Content Type	Text
Resource Type	Article
Subject	Health Information Management Information Systems Health Informatics

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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