research-article

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

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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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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