2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery · 2010 · 62 citations · 1 references
EngineeringRehabilitation MedicineSports MedicineBiomedical Signal ProcessingFeature EngineeringMovement AnalysisDigital Signal ProcessingElectromyogram AnalysisFeature ExtractionMuscle Signal ProcessingSignal ProcessingTime-frequency AnalysisElectromyography Feature ExtractionElectromyography Wavelet AnalysisMuscle Signal Feature ExtractionSignal Processing For EmgTime-frequency Electromyography AnalysisWavelet AnalysisWavelet TransformWavelet-based Electromyography Analysis
Wavelet analysis is often very effective because it provides a simple approach for dealing with local aspects of a signal. The electromyogram (EMG) signals arising from muscle activities have become a useful tool for clinical diagnosis, rehabilitation medicine and sport medicine. In this paper, a time-frequency analysis based on the wavelet transform of the EMG signals is presented with a focus on 2 areas: de-noising and feature extraction.
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