Proceedings of the KOSOMBE Conference (대한의용생체공학회:학술대회논문집)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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Classification of the ECG Beat Using ART Network Based on Linear Prediction Coefficient

선형예측계수에 근거한 ART 네트워크를 이용한 심전도 신호 분류

  • Park, K.L. (Dept. of Biomedical Eng. college of Health Science, Yonsei Univ.) ;
  • Lee, K.J. (Dept. of Biomedical Eng. college of Health Science, Yonsei Univ.)
  • 박광리 (연세대학교 보건과학대학 의용전자공학과) ;
  • 이경중 (연세대학교 보건과학대학 의용전자공학과)
  • Published : 1997.11.28
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Abstract

In this paper, we designed an ART(Adaptive Resonance Theory) network based on LPC(Linear Prediction Coefficient) for classification of PVB (Premature Ventricular Beat: PVC, LBBB, RBBB). The procedure of proposed system consists of the error calculation, feature generation and processing of the ART network. The error is calculated after processing by linear prediction algorithm and the features of ART network or classification are obtained from the binary ata determined by threshold method. In conclusion, ART network has good performance in classification of PVB.

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