The Community for Technology Leaders
2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2015)
Washington, DC, USA
Nov. 9, 2015 to Nov. 12, 2015
ISBN: 978-1-4673-6798-1
pp: 1743-1744
Juyoung Park , Department of Computer Science & Engineering, Hanyang University, Ansan, Republic of Korea
Mingon Kang , Department of Computer Science & Information Systems, Texas A&M University - Commerce, USA 75428
Younghoon Kim , Department of Computer Science & Engineering, Hanyang University, Ansan, Republic of Korea
Kyungtae Kang , Department of Computer Science & Engineering, Hanyang University, Ansan, Republic of Korea
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.
INDEX TERMS
beat morphology, ECG, heartbeat classification
CITATION

J. Park, M. Kang, Y. Kim and K. Kang, "Heartbeat classification for detecting arrhythmia using normalized beat morphology features," 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA, 2015, pp. 1743-1744.
doi:10.1109/BIBM.2015.7359947
96 ms
(Ver 3.3 (11022016))