JOURNAL ARTICLE

Power line interference attenuation in multi-channel sEMG signals: Algorithms and analysis

Abstract

Electromyogram (EMG) recordings are often corrupted by power line interference (PLI) even though the skin is prepared and well-designed instruments are used. This study focuses on the analysis of some of the recent and classical existing digital signal processing approaches have been used to attenuate, if not eliminate, the power line interference from EMG signals. A comparison of the signal to interference ratio (SIR) of the output signals is presented, for four methods: classical notch filter, spectral interpolation, adaptive noise canceller with phase locked loop (ANC-PLL) and adaptive filter, applied to simulated multichannel monopolar EMG signals with different SIR. The effect of each method on the shape of the EMG signals is also analyzed. The results show that ANC-PLL method gives the best output SIR and lowest shape distortion compared to the other methods. Classical notch filtering is the simplest method but some information might be lost as it removes both the interference and the EMG signals. Thus, it is obvious that notch filter has the lowest performance and it introduces distortion into the resulting signals.

Keywords:
Interference (communication) Band-stop filter Distortion (music) Computer science Phase-locked loop SIGNAL (programming language) Adaptive filter Filter (signal processing) Noise (video) Power (physics) Interpolation (computer graphics) Attenuation Line (geometry) Adjacent-channel interference Control theory (sociology) Comb filter Signal processing Algorithm Electronic engineering Channel (broadcasting) Low-pass filter Mathematics Artificial intelligence Digital signal processing Telecommunications Engineering Computer vision Bandwidth (computing) Jitter Physics

Metrics

13
Cited By
0.35
FWCI (Field Weighted Citation Impact)
10
Refs
0.65
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Muscle activation and electromyography studies
Physical Sciences →  Engineering →  Biomedical Engineering
EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience
ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
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