Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition. (August 2018)

• Record Type: Journal Article
• Authors: Sharma, Rishi Raj; Pachori, Ram Bilas
• Is Part Of: Biomedical signal processing and control. Volume 45(2018)
• Page Start: 33
• Page End: 49
• Publication Date: 2018-08
• Subjects: Baseline wander -- ECG denoising -- Eigenvalue decomposition -- Hankel matrix -- Power line interference; 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.2018.05.002
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: A methodology is proposed to remove baseline wander and power line interference from ECG signal. An eigenvalue decomposition based method is proposed in this work. The relation between eigenvalues of ECG signal and its baseline wander, and power line interference presented is explored. Abstract: In this paper, a novel method is proposed for baseline wander (BW) and power line interference (PLI) removal from electrocardiogram (ECG) signals. The proposed methodology is based on the eigenvalue decomposition of the Hankel matrix. It has been observed that the end-point eigenvalues of the Hankel matrix formed using noisy ECG signals are correlated with BW and PLI components. We have proposed a methodology to remove BW and PLI noise by eliminating eigenvalues corresponding to noisy components. The proposed concept uses one-step process for removing both BW and PLI noise simultaneously. The proposed method has been compared with other existing methods using performance measure parameters namely output signal to noise ratio (SNRout ), and percent root mean square difference (PRD). Simulation results validate the better performance of the proposed method than compared methods at different noise levels. The proposed method is suitable for preprocessing of ECG signals.