@inproceedings{77b079a526b24c099bed9dc1fc8748f7,
title = "Vector quantization for ECG beats classification",
abstract = "Reducing the feature dimensionality can improve the computational efficiency of electrocardiogram (ECG) beats classification system. In the long term ECG classification task, vector quantization has demonstrated its advantage in both dimensionality reduction and accuracy increase, but the existing vector quantization methods are not capable of representing the difference of each waveform among ECG beats. To make vector quantization available for ECG beats classification, in this paper, we propose a strategy that aligns each wave of all beats, and then build a dictionary corresponding to each wave segment. Thus vector quantization can distinguish each waveform of different beats. We compare our method with the popular beats features such as sampling point feature, fast Fourier transform feature, and discrete wavelet transform feature. The classification results show that our feature has high accuracy and is capable of reducing computational complexity of beats classification system, which demonstrate that the proposed method can provide an effective vector quantization feature for beats classification.",
keywords = "Classification, ECG beats, Feature extraction, K-means, Vector quantization",
author = "Tong Liu and Yujuan Si and Dunwei Wen and Mujun Zang and Weiwei Song and Liuqi Lang",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 17th IEEE International Conference on Computational Science and Engineering, CSE 2014 - Jointly with 13th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2014, 13th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2014 and 8th International Conference on Frontier of Computer Science and Technology, FCST 2014 ; Conference date: 19-12-2014 Through 21-12-2014",
year = "2015",
month = jan,
day = "26",
doi = "10.1109/CSE.2014.37",
language = "English",
series = "Proceedings - 17th IEEE International Conference on Computational Science and Engineering, CSE 2014, Jointly with 13th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2014, 13th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2014 and 8th International Conference on Frontier of Computer Science and Technology, FCST 2014",
pages = "13--20",
editor = "Xingang Liu and {El Baz}, Didier and Ching-Hsien Hsu and Kai Kang and Weifeng Chen",
booktitle = "Proceedings - 17th IEEE International Conference on Computational Science and Engineering, CSE 2014, Jointly with 13th IEEE International Conference on Ubiquitous Computing and Communications, IUCC 2014, 13th International Symposium on Pervasive Systems, Algorithms, and Networks, I-SPAN 2014 and 8th International Conference on Frontier of Computer Science and Technology, FCST 2014",
}