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Time-frequency analysis of myoelectric signals during dynamic contractions: a comparative study
350
Citations
25
References
2000
Year
EngineeringWearable TechnologyMotor ControlTime-frequency AnalysisElectrophysiological EvaluationKinesiologyBiosignal ProcessingIsokinetic ContractionsTimefrequency AnalysisHealth SciencesDynamic ContractionsWavelet TheoryComparative StudySignal ProcessingRamp ContractionElectromyographyElectrophysiologyHuman MovementWaveform Analysis
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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