DocumentCode :
1508943
Title :
Enhancement of spectral analysis of myoelectric signals during static contractions using wavelet methods
Author :
Karlsson, Stefan ; Yu, Jun ; Akay, Metin
Author_Institution :
Dept. of Biomed. Eng. & Inf., Univ. Hospital, Umea, Sweden
Volume :
46
Issue :
6
fYear :
1999
fDate :
6/1/1999 12:00:00 AM
Firstpage :
670
Lastpage :
684
Abstract :
Introduces wavelet packets as an alternative method for spectral analysis of surface myoelectric (ME) signals. Both computer synthesized and real ME signals are used to investigate the performance. The authors´ simulation results show that wavelet packet estimate has slightly less mean square error (MSE) than Fourier method, and both methods perform similarly on the real data. Moreover, wavelet packets give one some advantages over the traditional methods such as multiresolution of frequency, as well as its potential use for effecting time-frequency decomposition of the nonstationary signals such as the ME signals during dynamic contractions. The authors also introduce wavelet shrinkage method for improving spectral estimates by significantly reducing the MSE´s for both Fourier and wavelet packet methods.
Keywords :
electromyography; medical signal processing; spectral analysis; wavelet transforms; EMG analysis; Fourier methods; computer synthesized signals; mean square error; myoelectric signals spectral analysis; static contractions; wavelet methods; wavelet packets; Computational modeling; Frequency; Mean square error methods; Potential well; Signal resolution; Signal synthesis; Spectral analysis; Surface waves; Wavelet analysis; Wavelet packets; Action Potentials; Adult; Algorithms; Analysis of Variance; Bias (Epidemiology); Data Interpretation, Statistical; Fourier Analysis; Humans; Isometric Contraction; Male; Reproducibility of Results; Signal Processing, Computer-Assisted; Time Factors;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.764944
Filename :
764944
Link To Document :
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