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Open Access Highly Accessed Research article

Characteristic wave detection in ECG signal using morphological transform

Yan Sun1*, Kap Luk Chan2 and Shankar Muthu Krishnan

Author Affiliations

1 Bioinformatics Institute, Singapore 138671

2 Biomedical Engineering Research Center, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798

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BMC Cardiovascular Disorders 2005, 5:28  doi:10.1186/1471-2261-5-28

Published: 20 September 2005

Abstract

Background

Detection of characteristic waves, such as QRS complex, P wave and T wave, is one of the essential tasks in the cardiovascular arrhythmia recognition from Electrocardiogram (ECG).

Methods

A multiscale morphological derivative (MMD) transform-based singularity detector, is developed for the detection of fiducial points in ECG signal, where these points are related to the characteristic waves such as the QRS complex, P wave and T wave. The MMD detector is constructed by substituting the conventional derivative with a multiscale morphological derivative.

Results

We demonstrated through experiments that the Q wave, R peak, S wave, the onsets and offsets of the P wave and T wave could be reliably detected in the multiscale space by the MMD detector. Compared with the results obtained via with wavelet transform-based and adaptive thresholding-based techniques, an overall better performance by the MMD method was observed.

Conclusion

The developed MMD method exhibits good potentials for automated ECG signal analysis and cardiovascular arrhythmia recognition.