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Heartbeat classification for detecting arrhythmia using normalized beat morphology features
- Title
- Heartbeat classification for detecting arrhythmia using normalized beat morphology features
- Author
- 강경태
- Keywords
- beat morphology; ECG; heartbeat classification
- Issue Date
- 2015-11
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Citation
- Proceedings - 2015 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2015, article no. 7359947, Page. 1743.0-1744.0
- 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.
- URI
- https://ieeexplore.ieee.org/document/7359947https://repository.hanyang.ac.kr/handle/20.500.11754/182279
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