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Updated: Aug 15, 2026
Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
Published on: May 23, 2021
Characteristic wave detection in ECG signal using morphological transform
Yan Sun1, Kap Luk Chan, Shankar Muthu Krishnan
1Bioinformatics Institute, 138671, Singapore. sunyan@bii.a-star.edu.sg
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.
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