Arrhythmia classification with reduced features by linear discriminant analysis.

Arrhythmia classification with reduced features by linear discriminant analysis. Research Abstract Details 

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Arrhythmia classification with reduced features by linear discriminant analysis. Abstract Text:

J Lee,K Park,M Song,K Lee,

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.

Arrhythmia classification with reduced features by linear discriminant analysis. Publishing Authors By Initials

J Lee,K Park,M Song,K Lee,

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Arrhythmia classification with reduced features by linear discriminant analysis. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Conference proceedings : ... Annual International

VOLUME: 2

Page Numbers: 1142-4

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ISSN: 1557-170X

DAY: 6

MONTH: 02

YEAR: 2005

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LANGUAGE: eng

NlmUniqueID: 101243413

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Grant and Affiliation Information for Arrhythmia classification with reduced features by linear discriminant analysis.

AFFILIATION: Dept. of Biomed. Eng., Yonsei Univ., Kangwon.

Country: United States

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MEDLINETA: Conf Proc IEEE Eng Med Biol So

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