DocumentCode :
3179818
Title :
Estimation of Muscle Fatigue during Cyclic Contractions Using Source Separation Techniques
Author :
Naik, Ganesh R. ; Kumar, Dinesh K. ; Wheeler, Katherine ; Arjunan, Sridhar P.
Author_Institution :
Sch. of Electr. & Comput. Eng., RMIT Univerisity, Melbourne, VIC, Australia
fYear :
2009
fDate :
1-3 Dec. 2009
Firstpage :
217
Lastpage :
222
Abstract :
Previous research studies have reported that spectral compression of the surface Electromyogram (SEMG) towards lower frequencies is associated with onset of localized muscle fatigue. One reason for this spectral compression has been attributed to motor unit synchronization in literature. According to this, motor units are pseudo randomly excited during muscle contraction, and the recruitment pattern changes during the onset of muscle fatigue, such that the firing of motor units becomes more synchronized. While this theory is widely accepted, there is little experimental proof of the phenomenon. This paper has used source dependence properties and measures developed in research related to independent component analysis (ICA) to test for synchronization. This paper has also determined that the global matrix can be used as a measure for estimating localized muscle fatigue during cyclic movements.
Keywords :
electromyography; fatigue; independent component analysis; source separation; cyclic contractions; independent component analysis; muscle fatigue estimation; source separation techniques; spectral compression; surface electromyogram; Electromyography; Fatigue; Frequency estimation; Frequency synchronization; Independent component analysis; Life estimation; Muscles; Optical fiber polarization; Recruitment; Source separation; ICA; Muscle fatigue; Source separation; Surface EMG;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Image Computing: Techniques and Applications, 2009. DICTA '09.
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4244-5297-2
Electronic_ISBN :
978-0-7695-3866-2
Type :
conf
DOI :
10.1109/DICTA.2009.43
Filename :
5384982
Link To Document :
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