DocumentCode :
1298650
Title :
Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study
Author :
Karlsson, Stefan ; Yu, Jun ; Akay, Metin
Author_Institution :
Dept. of Biomed. Eng. & Inf., Univ. Hosp., Linkoping, Sweden
Volume :
47
Issue :
2
fYear :
2000
Firstpage :
228
Lastpage :
238
Abstract :
Introduces nonstationary signal analysis methods to analyze the myoelectric (ME) signals during dynamic contractions by estimating the time-dependent spectral moments. The time-frequency analysis methods including the short-time Fourier transform, the Wigner-Ville distribution, the Choi-Williams distribution, and the continuous wavelet transform were compared for estimation accuracy and precision on synthesized and real ME signals. It is found that the estimates provided by the continuous wavelet transform have better accuracy and precision than those obtained with the other time-frequency analysis methods on simulated data sets. In addition, ME signals from four subjects during three different tests (maximum static voluntary contraction, ramp contraction, and repeated isokinetic contractions) were also examined.
Keywords :
Fourier transforms; Wigner distribution; biomechanics; electromyography; medical signal processing; time-frequency analysis; Choi-Williams distribution; Wigner-Ville distribution; continuous wavelet transform; estimation accuracy; maximum static voluntary contraction; myoelectric signals time-frequency analysis; ramp contraction; repeated isokinetic contractions; short-time Fourier transform; Continuous wavelet transforms; Fatigue; Fourier transforms; Muscles; Shape; Signal analysis; Signal processing; Time frequency analysis; Wavelet analysis; Wavelet transforms; Action Potentials; Adult; Analog-Digital Conversion; Computer Simulation; Fourier Analysis; Humans; Male; Models, Biological; Muscle Contraction; Muscle, Skeletal; Reference Values; Signal Processing, Computer-Assisted;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/10.821766
Filename :
821766
Link To Document :
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