Yao, X. and Wei, H. orcid.org/0000-0002-4704-7346 (2022) A Modified Dynamic Time Warping (MDTW) approach and innovative Average Non-Self Match Distance (ANSD) method for anomaly detection in ECG recordings. In: Jiang, R., Zhang, L., Wei, H.L., Crookes, D. and Chazot, P., (eds.) Recent Advances in AI‑enabled Automated Medical Diagnosis. AI4MED 2021 : International Symposium on Artificial Intelligence for Medical Applications, 19-23 Aug 2021, Virtual Conference. CRC Press , pp. 281-303. ISBN ISBN 9781032008431
Abstract
ECGs objectively reflects the working conditions of the hearts as these signals contain vast physiological and pathological information. In this work, in order to improve the efficiency and accuracy of "best so far" time series analysis-based ECG anomaly detection methods, a novel method, comprising a modified dynamic time warping (MDTW) and an innovative average non-self match distance (ANSD) measure, is proposed for ECG anomaly detection. To evaluate the performance of the proposed method, the proposed method is applied to real ECG data selected from the MIT-BIH heartbeat database. To provide a reference for comparison, two existing anomaly detection methods, namely, brute force discord discovery (BFDD) and adaptive window discord discovery (AWDD), are also applied to the same data. The experimental results show that our proposed method outperforms BFDD and AWD.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2022 Richard Jiang, Li Zhang, Hua-Liang Wei, Danny Crookes, Paul Chazot. This is an author-produced version of a paper subsequently published in Recent Advances in AI-enabled Automated Medical Diagnosis. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Anomaly detection; Dynamic time warping; Non-self match distance; ECG |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/I011056/1; EP/H00453X/1 Natural Environment Research Council NE/V002511/1;NE/V001787/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Nov 2021 14:16 |
Last Modified: | 20 Oct 2023 00:13 |
Status: | Published |
Publisher: | CRC Press |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:179843 |