DocumentCode :
2963194
Title :
Strategies to identify muscle fatigue from SEMG during cycling
Author :
Singh, V.P. ; Kumar, D.K. ; Djuwari, D. ; Polus, B. ; Fraser, S. ; Hawley, J. ; Giudice, S.L.
Author_Institution :
Dept. of Electr. & Comput. Eng, R. Melbourne Inst. of Technol., Vic., Australia
fYear :
2004
fDate :
14-17 Dec. 2004
Firstpage :
547
Lastpage :
551
Abstract :
Detection, quantification and analysis of muscle fatigue are crucial in occupational/rehabilitation and sporting settings. Sports organizations, such as the Australian Institute of Sports (AIS), currently monitor fatigue by a battery of tests including invasive techniques that require taking blood samples and/or muscle biopsies, the latter of which is highly invasive, painful, time consuming and expensive. SEMG (surface electromyography) is non-invasive monitoring of muscle activation and is an indication of localized muscle fatigue based on the observed shift of the power spectral density of the SEMG. The success of SEMG based techniques is currently limited to isometric contraction and is not acceptable to the human movement community. The paper proposes and tests a simple signal processing technique to identify the onset of muscle fatigue during cyclic activities of muscles, such as VL and VM, during cycling. Based on experiments conducted with 7 participants, using power output as a measure of fatigue, the technique is able to identify muscle fatigue with 98% significance.
Keywords :
electromyography; medical signal processing; spectral analysis; Australian Institute of Sports; blood samples; cycling; fatigue monitoring; invasive techniques; isometric contraction; muscle activation; muscle biopsies; muscle cyclic activities; muscle fatigue; power spectral density; signal processing technique; surface EMG; surface electromyography; Australia; Batteries; Biomedical monitoring; Biomedical signal processing; Biopsy; Blood; Electromyography; Fatigue; Muscles; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
Print_ISBN :
0-7803-8894-1
Type :
conf
DOI :
10.1109/ISSNIP.2004.1417520
Filename :
1417520
Link To Document :
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