Algorithm for EMG noise level approximation in ECG signals. (April 2017)

• Record Type: Journal Article
• Authors: Marouf, Mohamed; Saranovac, Lazar; Vukomanovic, Goran
• Is Part Of: Biomedical signal processing and control. Volume 34(2017)
• Page Start: 158
• Page End: 165
• Publication Date: 2017-04
• Subjects: ECG -- Filtering -- Adaptive noise reduction -- Wavelet transform -- Noise -- Estimation -- Signal quality; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2017.02.002
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: An EMG noise level approximation in the ECG signal is proposed. The approximation relies on the wavelet details of the ECG signal. A reference signal is built to indicate the EMG noise level over time. Normal and abnormal rhythms are considered when building the reference signal. Several applications of tahe proposed reference signal are proposed. Abstract: In this paper, we introduce an approach for Electromyogram (EMG) noise level approximation in Electrocardiogram (ECG) signals. The stationary wavelet transform (SWT) is used to find efficient translation-invariant approximation of EMG noise. This is accomplished in the form of reference signal extracted as an estimation of the signal quality vs. EMG noise. The reference signal is built and then normalized after considering different heart rates and rhythms which increases its robustness and reliability to give accurate results regardless of input signal rhythm. Additionally, four applications of the extracted reference signal are suggested in this paper. For evaluation purposes both real EMG and artificial noises were used. The tested ECG signals are from MIT-BIH Arrhythmia Database Directory. The correlation coefficient between the added noise and the reference signal were computed for moving windows over the signal. Finally, the correlation between beats detection and reference signal was computed and presented. Reference signal gave high correlation with false positive values. Most false positives caused by EMG noise occur in intervals of greater amplitude reference signal and vice versa.