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. 2014 Mar 8;4(1):33-8.
eCollection 2014 Mar.

Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

S Abbaspour  1 , A Fallah  1
Affiliations

Removing ECG Artifact from the Surface EMG Signal Using Adaptive Subtraction Technique

S Abbaspour et al. J Biomed Phys Eng. .

Abstract

Background: The electrocardiogram artifact is a major contamination in the electromyogram signals when electromyogram signal is recorded from upper trunk muscles and because of that the contaminated electromyogram is not useful. Objective : Removing electrocardiogram contamination from electromyogram signals.

Methods: In this paper, the clean electromyogram signal, electrocardiogram artifact and electrocardiogram signal were recorded from leg muscles, the pectoralis major muscle of the left side and V4, respectively. After the pre-processing, contaminated electromyogram signal is simulated with a combination of clean electromyogram and electrocardiogram artifact. Then, contaminated electromyogram is cleaned using adaptive subtraction method. This method contains some steps; (1) QRS detection, (2) formation of electrocardiogram template by averaging the electrocardiogram complexes, (3) using low pass filter to remove undesirable artifacts, (4) subtraction.

Results: Performance of our method is evaluated using qualitative criteria, power spectrum density and coherence and quantitative criteria signal to noise ratio, relative error and cross correlation. The result of signal to noise ratio, relative error and cross correlation is equal to 10.493, 0.04 and %97 respectively. Finally, there is a comparison between proposed method and some existing methods.

Conclusion: The result indicates that adaptive subtraction method is somewhat effective to remove electrocardiogram artifact from contaminated electromyogram signal and has an acceptable result.

Keywords: Adaptive subtraction; Contamination; Electrocardiogram artifact; Noise removal; Surface electromyogram.

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Figures

Figure 1
Figure 1
(a) ECG, (b) ECG artifact, (c) clean EMG and (d) contaminated EMG.
Figure 2
Figure 2
A sample of the created ECG template.
Figure 3
Figure 3
The filtered ECG template.
Figure 4
Figure 4
(a) contaminated EMG, (b) noise estimated and (c) cleaned EMG.
Figure 5
Figure 5
(a) PSD of clean EMG signal and (b) PSD of cleaned EMG using adaptive subtraction technique.
Figure 6
Figure 6
Coherence of clean EMG and cleaned EMG signals.
See this image and copyright information in PMC

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