JOURNAL ARTICLE

ElectroCardioGram signal denoising using Discrete Wavelet Transform

Abstract

The most common noises in ElectroCardioGram (ECG) signal processing are baseline wandering and the 50 or 60 Hz power line interferences. In order to remove these two major source of noises, we have used the recent powerful Discrete Wavelet Transform (DWT) signal processing in ECG signals which are obtained from MIT-BIH Arrhythmia Database. The results indicate that DWT is a good method for filtering noises without changing the morphology of ECG, and can be applied to all types of ECG signals, whether normal or presenting arrhythmias.

Keywords:
Discrete wavelet transform Wavelet transform Computer science Noise reduction Pattern recognition (psychology) SIGNAL (programming language) Artificial intelligence Signal processing Second-generation wavelet transform Noise (video) Wavelet Speech recognition Digital signal processing Image (mathematics) Computer hardware

Metrics

23
Cited By
1.75
FWCI (Field Weighted Citation Impact)
13
Refs
0.84
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
Phonocardiography and Auscultation Techniques
Health Sciences →  Medicine →  Pulmonary and Respiratory Medicine
EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience

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