NDLI: Shape analysis and clustering of Surface EMG Data

Content Provider	IEEE Xplore Digital Library
Author	Boudaoud, S. Ayachi, F. Marque, C.
Copyright Year	2010
Description	Author affiliation: BMBI-CNRS UMR 6600 laboratory of the University of Technology of Compiègne (UTC), France (Boudaoud, S.; Ayachi, F.; Marque, C.)
Abstract	Functional Data Analysis (FDA) is a recent field in data analysis and processing. It provides efficient methods and tools by considering the analyzed data as realizations of functions. In this discipline, raised shape analysis approaches. Among them, the Core Shape Modelling (CSM) furnished statistical tools for the evaluation of the shape dispersion among a set of curves. In this work, it is proposed to use this approach to study Surface EMG (SEMG) Data. These data represent electrical activity elicited during muscle contractions and measured on the surface of the skin. The generation of the SEMG signal is dependent on many morphological, physiological and neural parameters. In fact, the neural parameters tune the spatial and time recruitment of the Motor Units (MUs). In this study, the CSM algorithm is applied to detect MUs firing synchrony on SEMG data simulated using a realistic generation model. The generation parameters induce several variabilities and compensatory effects on SEMG data that could complicate and bias the data processing task. After phase realignment, a shape clustering is done on SEMG amplitude histograms using CSM formalism for different MU synchrony classes. The obtained results are promising and demonstrate the ability of shape analysis using the CSM approach to detect and classify MUs firing synchrony levels in SEMG data despite the present variabilities.
Starting Page	4703
Ending Page	4706
File Size	282313
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626378
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Shape Muscles Synchronization Force Histograms Fatigue Electromyography
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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
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