A wavelet-based algorithm for delineation and classification of wave patterns in continuous Holter ECG recordings

Quantitative analysis of the electrocardiogram (ECG) requires delineation and classification of the individual ECG wave patterns. We propose a wavelet-based waveform classifier that uses the fiducial points identified by a delineation algorithm. For validation of the algorithm, manually annotated EC...

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Published in2010 Computing in Cardiology Vol. 37; no. 5738139; pp. 979 - 982
Main Authors Johannesen, L, Grove, U S L, Sørensen, J S, Schmidt, M L, Couderc, J.-P, Graff, C
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2010
Subjects
Accuracy
Cardiology
Classification algorithms
Electrocardiography
Heart
Manuals
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Summary:Quantitative analysis of the electrocardiogram (ECG) requires delineation and classification of the individual ECG wave patterns. We propose a wavelet-based waveform classifier that uses the fiducial points identified by a delineation algorithm. For validation of the algorithm, manually annotated ECG records from the QT database (Physionet) were used. ECG waveform classification accuracies were: 85.6% (P-wave), 89.7% (QRS complex), 92.8% (T-wave) and 76.9% (U-wave). The proposed classification method shows that it is possible to classify waveforms based on the points obtained during delineation. This approach can be used to automatically classify wave patterns in long-term ECG recordings such as 24-hour Holter recordings.
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ISBN:9781424473182
1424473187
ISSN:0276-6574
2325-8861
2325-8853