DocumentCode :
3846422
Title :
Experimental Analysis of Accuracy in the Identification of Motor Unit Spike Trains From High-Density Surface EMG
Author :
Aleş ;Marco Alessandro Minetto;Alberto Botter;Francesco Negro;Dario Farina
Author_Institution :
Faculty of Electrical Engineering and Computer Science, Laboratorio di Ingegneria del Sistema Neuromuscolare, University of Maribor, Politecnico di Torino, Maribor, Torino, SloveniaItaly
Volume :
18
Issue :
3
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
221
Lastpage :
229
Abstract :
The aim of this study was to compare the decomposition results obtained from high-density surface electromyography (EMG) and concurrently recorded intramuscular EMG. Surface EMG signals were recorded with electrode grids from the tibialis anterior, biceps brachii, and abductor digiti minimi muscles of twelve healthy men during isometric contractions ranging between 5% and 20% of the maximal force. Bipolar intramuscular EMG signals were recorded with pairs of wire electrodes. Surface and intramuscular EMG were independently decomposed into motor unit spike trains. When averaged over all the contractions of the same contraction force, the percentage of discharge times of motor units identified by both decompositions varied in the ranges 84%-87% (tibialis anterior), 84%-86% (biceps brachii), and 87%-92% (abductor digiti minimi) across the force levels analyzed. This index of agreement between the two decompositions was linearly correlated with a self-consistency measure of motor unit discharge pattern that was based on coefficient of variation for the interspike interval (R2 = 0.68 for tibialis anterior, R2 = 0.56 for biceps brachii, and R2 = 0.38 for abductor digiti minimi). These results constitute an important contribution to the validation of the noninvasive approach for the investigation of motor unit behavior in isometric low-force tasks.
Keywords :
"Electromyography","Electrodes","Laboratories","Wire","Signal analysis","Needles","Muscles","Surface discharges","Measurement units","Signal resolution"
Journal_Title :
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2010.2041593
Filename :
5409593
Link To Document :
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