scholarly journals Methods of Power Line Interference Elimination in EMG Signal

2019 ◽  
Vol 40 ◽  
pp. 64-70
Author(s):  
Martina Ladrova ◽  
Radek Martinek ◽  
Jan Nedoma ◽  
Marcel Fajkus
Keyword(s):  
Signal To Noise Ratio ◽  
Notch Filter ◽  
Correlation Coefficients ◽  
Power Line ◽  
Shape Distortion ◽  
Emg Signal ◽  
Wide Range ◽  
Interference Elimination ◽  
Power Line Interference ◽  
Line Interference

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.

Power Line Interference Elimination in ECG Signals

2019 ◽  
Vol 41 ◽  
pp. 105-115
Author(s):  
Martina Ladrova ◽  
Radek Martinek ◽  
René Jaros
Keyword(s):  
Moving Average ◽  
Notch Filter ◽  
Power Line ◽  
Ecg Signal ◽  
Mode Decomposition ◽  
Wide Range ◽  
Interference Elimination ◽  
Power Line Interference ◽  
Adaptive Noise Canceller ◽  
Line Interference

The recordings of electrocardiogram (ECG), as an important biological signal which provides a valuable basis for the clinical diagnosis and treatment, are often corrupted by the wide range of artifacts. One important of them is power line interference (PLI). The overlapping interference affects the quality of ECG waveform, leading to the false detection and recognition of wave groups, and thus causing faulty treatment or diagnosis. The study deals with some of the signal processing approaches frequently used for elimination of PLI in ECG signal and compares the accuracy of methods by evaluation of the power of the remaining noise and comparing a filtered ECG signal with an original. The results are compared for three levels of interference and each tested method: Butterworth filter (BF), notch filter, moving average filter (MA), adaptive noise canceller (ANC), wavelet transform (WT) and empirical mode decomposition (EMD).

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