Arrhythmia classification with reduced features by linear discriminant analysis

J. Lee, K. L. Park, M. H. Song, K. J. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this study, we proposed 17 input features based on wavelet coefficients for arrhythmia detection and, by applying linear discriminant analysis to these, reduced the feature dimension to be 4. Then, with newly constructed 4 dimension input feature, a multi-layer perceptrons classifier was tried to detect 6 types of arrhythmia beats. For evaluation of input features by linear discriminant analysis, the arrhythmia detection efficiency with these (LDA) was compared to that with original input features (ORG) and that with of input features by principle component analysis (PCA) respectively. When LDA was compared to ORG, the former showed similar or a little higher values than the latter for different types of arrhythmia beats except SVT. And, LDA showed to be persistently higher than PCA. By theses cross-validations, for the detection of several types of arrhythmia beats, the reduction of input feature dimension by linear discriminant analysis was revealed to be prior to that by principle component analysis. Even if LDA was compared to ORG, it maintained the acceptable level efficiency so that the time and computational costs would be expected to be cutdown dramatically. Finally, by the proposed algorithm, we could obtain the good accuracy of arrhythmia detection and that of NSR, SVT, PVC and VF was 99.52%, 99.43%, 98.59% and 99.88%, respectively.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1142-1144
Number of pages3
ISBN (Print)0780387406, 9780780387409
DOIs
StatePublished - 2005
Externally publishedYes
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: Sep 1 2005Sep 4 2005

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume7 VOLS
ISSN (Print)0589-1019

Other

Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Country/TerritoryChina
CityShanghai
Period9/1/059/4/05

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint

Dive into the research topics of 'Arrhythmia classification with reduced features by linear discriminant analysis'. Together they form a unique fingerprint.

Cite this