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Heartbeat classification for detecting arrhythmia using normalized beat morphology features
- Issue Date
- Nov-2015
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- beat morphology; ECG; heartbeat classification
- Citation
- Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, pp 1743 - 1744
- Pages
- 2
- Indexed
- OTHER
- Journal Title
- Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015
- Start Page
- 1743
- End Page
- 1744
- Abstract
- We propose a method of arrhythmia detection based on beat morphology, which offers a new set of features for heartbeat classification. This can be performed by nearest-neighbor search, which we applied to heartbeats from the MIT-BIH arrhythmia database. Our classifier achieved an overall accuracy of 98.18% on 103,923 heartbeats. © 2015 IEEE.
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Collections - COLLEGE OF COMPUTING > DEPARTMENT OF ARTIFICIAL INTELLIGENCE > 1. Journal Articles
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Related Researcher
- Kang, Kyung tae
- ERICA 소프트웨어융합대학 (DEPARTMENT OF ARTIFICIAL INTELLIGENCE)