Removal of Baseline Wander from Electrocardiogram using Ensemble Empirical Mode Decomposition and Low Pass Filter
Roshan M. Bodile1, T.V.K. Hanumantha Rao2
1Roshan M. Bodile*, Department of ECE, National Institute of Technology, Warangal, India.
2T.V.K. Hanumantha Rao, Department of ECE, National Institute of Technology, Warangal, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on November 30, 2019. | PP: 2771-2774 | Volume-8 Issue-4, November 2019. | Retrieval Number: D6883118419/2019©BEIESP | DOI: 10.35940/ijrte.D6883.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: ECG; EMD; Ensemble EMD; Low Pass Filter.
Scope of the Article: Empirical Software Engineering.