JOURNAL ARTICLE

Baseline wander removal of electrocardiogram signals using multivariate empirical mode decomposition

Praveen GuptaKamalesh Kumar SharmaShiv Dutt Joshi

Year: 2015 Journal:   Healthcare Technology Letters Vol: 2 (6)Pages: 164-166   Publisher: Institution of Engineering and Technology

Abstract

A new method for removing the baseline wander (BW) noise based on multivariate empirical mode decomposition is presented. The proposed method is compared with recently introduced technique for BW removal using Hilbert vibration decomposition in terms of correlation coefficient criterion and signal‐to‐noise ratio. To evaluate the performance of the proposed method, real BW signals are added to synthetic and clinical electrocardiogram (ECG) signals. It is shown that presented methodology has significant scope of removing BW noise in real world ECG signals.

Keywords:
Hilbert–Huang transform Multivariate statistics Noise (video) Computer science Pattern recognition (psychology) Baseline (sea) SIGNAL (programming language) Correlation coefficient Artificial intelligence Signal-to-noise ratio (imaging) Speech recognition Decomposition Mode (computer interface) Noise reduction Statistics Mathematics White noise Machine learning

Metrics

33
Cited By
0.46
FWCI (Field Weighted Citation Impact)
9
Refs
0.69
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Phonocardiography and Auscultation Techniques
Health Sciences →  Medicine →  Pulmonary and Respiratory Medicine

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