Independent component analysis of EMG for posture detection: Sensitivity to variation of posture properties

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URI: https://hdl.handle.net/11556/1691
ISBN: 9781457714986
DOI: 10.1109/TELFOR.2011.6143889
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2011
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Abstract
We applied Agglomerative Hierarchical Clustering (AHC) technique on independent components of low back surface electromyography (sEMG) signals, in order to differ sitting and standing postures. Preliminary results from small group of healthy subjects, suggested that presented method might be used to distinguish between two postures in different conditions. Clustering accuracy varied from 60% to 70% due to variation of position properties, even when the muscle activity was very low: from 11% to 23% of Maximal Voluntary Contraction (MVC).
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clustering , EMG , ICA , posture , Computer Networks and Communications
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conference output
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Miljković , N , Bijelić , G , Garcia , G A & Popović , M B 2011 , Independent component analysis of EMG for posture detection : Sensitivity to variation of posture properties . in 2011 19th Telecommunications Forum, TELFOR 2011 - Proceedings of Papers . , 6143889 , 2011 19th Telecommunications Forum, TELFOR 2011 - Proceedings of Papers , pp. 47-50 , 2011 19th Telecommunications Forum, TELFOR 2011 , Belgrade , Serbia , 22/11/11 . https://doi.org/10.1109/TELFOR.2011.6143889
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