title: Powerline interference reduction in ECG signals using empirical wavelet transform and adaptive filtering.
abstract: Separating an information-bearing signal from the background noise is a general problem in signal processing. In a clinical environment during acquisition of an electrocardiogram (ECG) signal, The ECG signal is corrupted by various noise sources such as powerline interference (PLI), baseline wander and muscle artifacts. This paper presents novel methods for reduction of powerline interference in ECG signals using empirical wavelet transform (EWT) and adaptive filtering. The proposed methods are compared with the empirical mode decomposition (EMD) based PLI cancellation methods. A total of six methods for PLI reduction based on EMD and EWT are analysed and their results are presented in this paper. The EWT-based de-noising methods have less computational complexity and are more efficient as compared with the EMD-based de-noising methods.
authors.affiliation: Department of Electronics and Communication Engineering, National Institute of Technology Jalandhar , India.
authors.forename: Omkar
authors.initials: O
authors.lastname: Singh
authors.forename: Ramesh Kumar
authors.initials: RK
authors.lastname: Sunkaria
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016208:Databases, Factual; D004562:Electrocardiography / Q000379:methods*; D006801:Humans; D058067:Wavelet Analysis
keywords: Adaptive filtering; electrocardiogram; empirical mode decomposition; empirical wavelet transform; powerline interference