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Heartbeat Classification for Detecting Arrhythmia using Normalized Beat Mophology Features

Title
Heartbeat Classification for Detecting Arrhythmia using Normalized Beat Mophology Features
Author
강경태
Keywords
ECG; heartbeat classification; beat morphology
Issue Date
2015-11
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation
2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Page. 1743-1744
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.
URI
https://ieeexplore.ieee.org/document/7359947http://repository.hanyang.ac.kr/handle/20.500.11754/101908
ISSN
978-1-4673-6799-8
DOI
10.1109/BIBM.2015.7359947
Appears in Collections:
COLLEGE OF COMPUTING[E] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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