Automated ECG segmentation with dynamic time warping

To detect an abnormal conduction of the heart, cardiologists annotate certain points in the electrocardiogram (ECG) manually. As this is a very strenuous task, several algorithms have been developed to segment the ECG automatically. In this paper, we describe several such methods, and we further pre...

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Main Authors: Vullings, H.J.L.M., Verhaegen, M.H.G., Verbruggen, H.B.
Format: Conference Proceeding
Language:English
Subjects:
Band pass filters
Cardiology
Clinical diagnosis
Dynamic programming
Electrocardiography
Heart
Hidden Markov models
Speech recognition
Testing
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Verhaegen, M.H.G.
Verbruggen, H.B.
description To detect an abnormal conduction of the heart, cardiologists annotate certain points in the electrocardiogram (ECG) manually. As this is a very strenuous task, several algorithms have been developed to segment the ECG automatically. In this paper, we describe several such methods, and we further present a new single-lead method based on dynamic time warping (DTW). The results are tested on the QT database and compared to Laguna et al.'s (1997) two-lead method. DTW produces a smaller mean error, but has a higher standard deviation than Laguna's method.
doi_str_mv 10.1109/IEMBS.1998.745863
format conference_proceeding
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Band pass filters
Cardiology
Clinical diagnosis
Dynamic programming
Electrocardiography
Heart
Hidden Markov models
Speech recognition
Testing
title Automated ECG segmentation with dynamic time warping
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