NDLI: Fourier and wavelet spectral analysis of EMG signals in supramaximal constant load dynamic exercise

Content Provider	IEEE Xplore Digital Library
Author	Camata, T.V. Dantas, J.L. Abrão, T. Brunetto, M.A.O.C. Moraes, A.C. Altimari, L.R.
Copyright Year	2010
Description	Author affiliation: Group of Study and Research in Neuromuscular System and Exercise, CEFE - State University of Londrina (UEL), PR, Brazil (Camata, T.V.; Dantas, J.L.; Altimari, L.R.) \|\| GPNeurom - Laboratory of Electromyography Studies, FEF - State University of Campinas (UNICAMP), SP, Brazil (Moraes, A.C.) \|\| Department of Electrical Engineering, CTU - State University of Londrina (UEL), PR, Brazil (Abrão, T.) \|\| Department of Computing, CCE - State University of Londrina (UEL), PR, Brazil (Brunetto, M.A.O.C.)
Abstract	Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in supramaximal constant load dynamic exercise (110% VO2peak). The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in supramaximal constant load dynamic exercise (P>0.05). However, the results of the variance was significantly lower for at least one of the muscles studied in CWT compared to STFT (P<0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.
Starting Page	1364
Ending Page	1367
File Size	468532
Page Count	4
File Format	PDF
ISBN	9781424441235
ISSN	1557170X
DOI	10.1109/IEMBS.2010.5626743
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-08-31
Publisher Place	Argentina
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Muscles Electromyography Continuous wavelet transforms Fatigue Time frequency analysis
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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