Journal of biomimetics, biomaterials and biomedical engineering · 2019 · 14 citations · 10 references
EngineeringElectrical EngineeringBioinstrumentationBiomedical Signal ProcessingElectrophysiologyArtifact RejectionDigital Signal ProcessingElectromyogram AnalysisMuscle Signal ProcessingNoise ReductionSignal ProcessingAdaptive Noise CancellationAdaptive Noise ReductionElectromyography Artifact RemovalElectromyography Signal FilteringElectromyography Signal PreprocessingNotch FilteringShape DistortionSignal-to-noise Ratio
Electromyogram (EMG) recordings are often corrupted by the wide range of artifacts, which one of them is power line interference (PLI). The study focuses on some of the well-known signal processing approaches used to eliminate or attenuate PLI from EMG signal. The results are compared using signal-to-noise ratio (SNR), correlation coefficients and Bland-Altman analysis for each tested method: notch filter, adaptive noise canceller (ANC) and wavelet transform (WT). Thus, the power of the remaining noise and shape of the output signal are analysed. The results show that the ANC method gives the best output SNR and lowest shape distortion compared to the other methods.
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Radek Martínek, Radana Kahánková, Janusz Jeżewski et al. · Frontiers in Physiology · 2018 · 118 citations · Full text