IEEE Transactions on Biomedical Engineering · 2000 · 352 citations · 25 references
EngineeringElectrical EngineeringPhysiologyBiomedical Signal ProcessingElectrophysiologyTime Series AnalysisDigital Signal ProcessingElectromyogram AnalysisMuscle Signal ProcessingSignal ProcessingSpectral AnalysisTime-frequency AnalysisAccuracyContinuous Wavelet TransformNonstationary Signal AnalysisShort-time Fourier TransformSpectral MomentsTime-frequency Analysis Of Nonstationary SignalsWavelet TransformWigner-ville Distribution
In this paper, we introduce the 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.
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Деннис Габор · Journal of the IEE · 1946 · 4.5K citations
Time-frequency distributions-a review
Leon Cohen · Proceedings of the IEEE · 1989 · 3.6K citations
Wavelets and signal processing
Olivier Rioul, Martin Vetterli · IEEE Signal Processing Magazine · 1991 · 2.8K citations · Full text