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Comparison of feature selection methods in ECG signal classification

Authors:

Zhen-Xing Zhang,

Sang-Hong Lee,

Joon S. LimAuthors Info & Claims

ICUIMC '10: Proceedings of the 4th International Conference on Uniquitous Information Management and Communication

Article No.: 73, Pages 1 - 5

https://doi.org/10.1145/2108616.2108704

Published: 14 January 2010 Publication History

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Abstract

In past years, the Principal Component Analysis (PCA) has been applied to select features for classification applications. This paper presents a performance comparison between PCA and Non-overlap Area Distribution Measurement (NADM), which is based on a neural fuzzy network. This paper performs an experiment on Normal Sinus Rhythm (NSR) and Ventricular Tachycardia/Fibrillation (VT/VF) classification with the two feature selection methods. The performance result is 89.34% while the number of initial features is projected from six to four by the PCA method. The performance result is 91.02% while the number of initial features is decreased from six to two by NADM. The results clearly show that NADM outperforms PCA by 1.68% with fewer features.

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Viswanathan MZhang ZTian XLim JLee SHanzo LChung MLee SCho K(2011)A fatigue detection algorithm by heart rate variability based on a neuro-fuzzy networkProceedings of the 5th International Conference on Ubiquitous Information Management and Communication10.1145/1968613.1968712(1-6)Online publication date: 21-Feb-2011
https://dl.acm.org/doi/10.1145/1968613.1968712
Zhang ZTian XLim J(2011)New algorithm for the depression diagnosis using HRV: A neuro-fuzzy approachInternational Symposium on Bioelectronics and Bioinformations 201110.1109/ISBB.2011.6107702(283-286)Online publication date: Nov-2011
https://doi.org/10.1109/ISBB.2011.6107702
Zhen-Xing Zhang Xue-Wei Tian Lim J(2010)Real-time algorithm for a mobile cardiac monitoring system to detect life-threatening arrhythmias2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)10.1109/ICCAE.2010.5451715(232-236)Online publication date: Feb-2010
https://doi.org/10.1109/ICCAE.2010.5451715

Index Terms

Comparison of feature selection methods in ECG signal classification
1. Computing methodologies
  1. Machine learning

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ICUIMC '10: Proceedings of the 4th International Conference on Uniquitous Information Management and Communication

January 2010

550 pages

ISBN:9781605588933

DOI:10.1145/2108616

Conference Chairs:
Kwan-Ho You
Sungkyunkwan University, Korea
,
Sang-Won Lee
Sungkyunkwan University, Korea
,
General Chairs:
Won Kim
Sungkyunkwan University, Korea
,
Dongho Won
SungKyunkwan University, Korea

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Published: 14 January 2010

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ICUIMC '10: The 4th International Conference on Ubiquitous Information Management and Communication

January 14 - 15, 2010

Suwon, Republic of Korea

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Viswanathan MZhang ZTian XLim JLee SHanzo LChung MLee SCho K(2011)A fatigue detection algorithm by heart rate variability based on a neuro-fuzzy networkProceedings of the 5th International Conference on Ubiquitous Information Management and Communication10.1145/1968613.1968712(1-6)Online publication date: 21-Feb-2011
https://dl.acm.org/doi/10.1145/1968613.1968712
Zhang ZTian XLim J(2011)New algorithm for the depression diagnosis using HRV: A neuro-fuzzy approachInternational Symposium on Bioelectronics and Bioinformations 201110.1109/ISBB.2011.6107702(283-286)Online publication date: Nov-2011
https://doi.org/10.1109/ISBB.2011.6107702
Zhen-Xing Zhang Xue-Wei Tian Lim J(2010)Real-time algorithm for a mobile cardiac monitoring system to detect life-threatening arrhythmias2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)10.1109/ICCAE.2010.5451715(232-236)Online publication date: Feb-2010
https://doi.org/10.1109/ICCAE.2010.5451715

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A summative survey on ECG and PPG signal analysis

Novel ECG Signal Classification Based on KICA Nonlinear Feature Extraction

A novel method for ECG signal classification via one-dimensional convolutional neural network

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A summative survey on ECG and PPG signal analysis

Novel ECG Signal Classification Based on KICA Nonlinear Feature Extraction

A novel method for ECG signal classification via one-dimensional convolutional neural network

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