ECG signal denoising and baseline wander correction based on the empirical mode decomposition

• Published in: Computers in biology and medicine Vol. 38; no. 1; pp. 1 - 13
• Main Authors: Blanco-Velasco, Manuel, Weng, Binwei, Barner, Kenneth E
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.01.2008; Elsevier Limited
• Subjects: Algorithms; Arrhythmias, Cardiac - diagnosis; Arrhythmias, Cardiac - physiopathology; Baseline drift; Baseline wander; Databases, Factual; Denoising; Diagnosis, Computer-Assisted - methods; ECG enhancement; Electrocardiogram (ECG); Electrocardiography - methods; Empirical mode decomposition (EMD); Humans; Internal Medicine; Other; Reproducibility of Results; Signal Processing, Computer-Assisted; Stress ECG; Baseline wander; Stress ECG; Empirical mode decomposition (EMD); ECG enhancement; Electrocardiogram (ECG); Baseline drift; Denoising
• ISSN: 0010-4825; 1879-0534
• DOI: 10.1016/j.compbiomed.2007.06.003

Abstract The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Good quality ECG are utilized by physicians for interpretation and identification of physiological and pathological phenomena. However, in real situations, ECG recordings are often corrupted by artifacts. Two dominant artifacts present in ECG recordings are: (1) high-frequency noise caused by electromyogram induced noise, power line interferences, or mechanical forces acting on the electrodes; (2) baseline wander (BW) that may be due to respiration or the motion of the patients or the instruments. These artifacts severely limit the utility of recorded ECGs and thus need to be removed for better clinical evaluation. Several methods have been developed for ECG enhancement. In this paper, we propose a new ECG enhancement method based on the recently developed empirical mode decomposition (EMD). The proposed EMD-based method is able to remove both high-frequency noise and BW with minimum signal distortion. The method is validated through experiments on the MIT–BIH databases. Both quantitative and qualitative results are given. The simulations show that the proposed EMD-based method provides very good results for denoising and BW removal.