Optimisation of thresholding techniques in de-noising of ECG signals. (29th January 2022)

• Record Type: Journal Article
• Authors: Saxena, Shivani; Vijay, Ritu; Pahadiya, Pallavi
• Is Part Of: International journal of intelligent engineering informatics. Volume 9:Number 5(2021)
• Page Start: 487
• Page End: 501
• Publication Date: 2022-01-29
• Subjects: ECG -- baseline wander noise -- power line interference noise -- thresholding -- wavelet transform -- ECG arrhythmia -- hard thresholding -- histograms -- mean square error -- soft thresholding -- thresholding rules; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

Abstract

Wavelet based thresholding procedure is most popular approach to obtained de-noised ECG signal. Traditional thresholding techniques classified into soft and hard thresholding, have their own limitations. Former one involves large data size leading to longer computational time and second one involving compression of data results in loss of information sometimes crucial. The work in this paper optimised the features of both thresholding methods in which elimination of noisy wavelet coefficients is performed and rest coefficients are modified using features of hard and soft thresholding respectively. Computed mean square error is minimum in proposed method among hard thresholding, soft thresholding and proposed thresholding technique. In addition, histogram plot is used to identify frequency distribution in de-noising ECG signals.