@inproceedings{f7e81eb34610444f8e5a598e434f36c4,
title = "Independent component analysis of EMG for posture detection: Sensitivity to variation of posture properties",
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).",
keywords = "clustering, EMG, ICA, posture",
author = "Nadica Miljkovi{\'c} and Goran Bijeli{\'c} and Garcia, {Gonzalo A.} and Popovi{\'c}, {Mirjana B.}",
year = "2011",
doi = "10.1109/TELFOR.2011.6143889",
language = "English",
isbn = "9781457714986",
series = "2011 19th Telecommunications Forum, TELFOR 2011 - Proceedings of Papers",
pages = "47--50",
booktitle = "2011 19th Telecommunications Forum, TELFOR 2011 - Proceedings of Papers",
note = "2011 19th Telecommunications Forum, TELFOR 2011 ; Conference date: 22-11-2011 Through 24-11-2011",
}