ECG Signal Denoising Based on Morphological Filtering

Electrocardiographic (ECG) signal are often contaminated with different types of noise and base-line drift. A morphological filtering approach was put forward to remove the noise of the ECG signals and to calibrate the base-line drift in this paper. Different sizes of structuring elements were used...

Full description

Saved in:
Bibliographic Details
Published in2011 5th International Conference on Bioinformatics and Biomedical Engineering pp. 1 - 4
Main Authors Zhongguo Liu, Jinliang Wang, Boqiang Liu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2011
Subjects
Adaptive filters
Electrocardiography
Filtering
Morphology
Noise
Shape
Online AccessGet full text
ISBN9781424450886
1424450888
ISSN2151-7614
DOI10.1109/icbbe.2011.5780239

Cover

More Information
Summary:Electrocardiographic (ECG) signal are often contaminated with different types of noise and base-line drift. A morphological filtering approach was put forward to remove the noise of the ECG signals and to calibrate the base-line drift in this paper. Different sizes of structuring elements were used to process the signal for different nature of ECG signal and noise. The morphological filtering approach is simple, fast and real-time in processing, and it keeps the ECG signal shape unchanged while removing the noise. An experiment was carried out to simulate the morphological filtering approach with LABVIEW, and it was shown that this approach was effective in removing noise and in calibrating the base-line drift.
ISBN:9781424450886
1424450888
ISSN:2151-7614
DOI:10.1109/icbbe.2011.5780239