Title :
A decomposition software package for the decomposition of long-term multi-channel electromyrographic signals
Author :
Zennaro, D. ; Wellig, P. ; Moschytz, G.S. ; Läubli, T. ; Krueger, H.
Author_Institution :
Inst. of Hygiene & Appl. Physiol., Swiss Fed. Inst. of Technol., Zurich, Switzerland
Abstract :
The analysis of intramuscular EMG signals is based on the decomposition of the signals into basic units. Existing decomposition software only supports short registration periods or single-channel recordings of signals of constant muscle effort. In this paper, we present the decomposition software EMG-LODEC (ElectroMyoGram LOng-term DEComposition) that is especially designed for multi-channel long-term recordings of signals of slight muscle movements. Based on experiments on simulated and recorded EMG signals, our software is capable of providing reliable decompositions with satisfying accuracy. EMG-LODEC is suitable for the study of motor-unit discharge patterns and recruitment order in healthy subjects and patients.
Keywords :
discrete wavelet transforms; electromyography; medical signal processing; pattern clustering; signal classification; software packages; EMG-LODEC software; artificially generated signals; bandpass-filtering; clustering; decomposition software package; discrete wavelet coefficients; intramuscular EMG signals; long-term multichannel signals; motor-unit discharge patterns; recruitment order; reliable decompositions; segmentation; single-linkage algorithm; slight muscle movements; supervised classification; template matching; weighted averaging method; Band pass filters; Electrodes; Electromyography; Muscles; Physiology; Shape; Signal analysis; Signal processing; Software packages; Wavelet coefficients;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1020374