Open AccessRemoval of Baseline Wander from Electrocardiogram using Ensemble Empirical Mode Decomposition and Low Pass Filter
Author(s) -
Roshan M. Bodile,
T. Venkatappa Rao
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d6883.118419
Subject(s) - hilbert–huang transform , artificial intelligence , computer science , signal (programming language) , pattern recognition (psychology) , filter (signal processing) , noise (video) , visualization , distortion (music) , noise reduction , interference (communication) , sinus rhythm , electrocardiography , speech recognition , computer vision , cardiology , image (mathematics) , medicine , telecommunications , bandwidth (computing) , amplifier , channel (broadcasting) , programming language , atrial fibrillation
Electrocardiogram (ECG) is a graphical visualization of the electrical activity of human heart. The biomedical signal, such as ECG, has a major issue of separating the pure signal from artifacts due to baseline wander (BW), electrode artifacts, muscle artifacts, and power-line interference. Reduction of these artifacts is vital for clinical purposes for diagnosis and interpretation of the human heart condition. This paper presents removal of BW from ECG using ensemble empirical mode decomposition (EMD) with multiband filtering approach. A comparative performance analysis of EMD and ensemble EMD for synthetic as well as real BW on normal sinus rhythm and arrhythmia ECG signal are presented. This method can remove the BW in different inherent signal to noise ratio (SNR) including negative and positive as well. This method shows that quantitative and qualitative results with miniscule signal distortion via experiments on several ECG records.