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Journal of Medical Systems
Published in: Journal of Medical Systems 1/2017

01-01-2017 | Mobile & Wireless Health

Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection

Authors: Juyoung Park, Mingon Kang, Jean Gao, Younghoon Kim, Kyungtae Kang

Published in: Journal of Medical Systems | Issue 1/2017

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Abstract

Detecting arrhythmia from ECG data is now feasible on mobile devices, but in this environment it is necessary to trade computational efficiency against accuracy. We propose an adaptive strategy for feature extraction that only considers normalized beat morphology features when running in a resource-constrained environment; but in a high-performance environment it takes account of a wider range of ECG features. This process is augmented by a cascaded random forest classifier. Experiments on data from the MIT-BIH Arrhythmia Database showed classification accuracies from 96.59% to 98.51%, which are comparable to state-of-the art methods.
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Metadata
Title
Cascade Classification with Adaptive Feature Extraction for Arrhythmia Detection
Authors
Juyoung Park
Mingon Kang
Jean Gao
Younghoon Kim
Kyungtae Kang
Publication date
01-01-2017
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 1/2017
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-016-0660-9

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