Journal of Biomedical Engineering Research (대한의용생체공학회:의공학회지)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
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An Adaptive Classification Algorithm of Premature Ventricular Beat With Optimization of Wavelet Parameterization

웨이블릿 변수화의 최적화를 통한 적응형 조기심실수축 검출 알고리즘

  • Kim, Jin-Kwon (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Kang, Dae-Hoon (Department of Electrical and Electronic Engineering, Yonsei University) ;
  • Lee, Myoung-Ho (Department of Electrical and Electronic Engineering, Yonsei University)
  • 김진권 (연세대학교 전기전자공학과) ;
  • 강대훈 (연세대학교 전기전자공학과) ;
  • 이명호 (연세대학교 전기전자공학과)
  • Published : 2009.08.30
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Abstract

The bio signals essentially have different characteristics in each person. And the main purpose of automatic diagnosis algorithm based on bio signals focuses on discriminating differences of abnormal state from personal differences. In this paper, we propose automatic ECG diagnosis algorithm which discriminates normal heart beats from premature ventricular contraction using optimization of wavelet parameterization to solve that problem. The proposed algorithm optimizes wavelet parameter to let energy of signal be concentrated on specific scale band. We can reduce the personal differences and consequently highlight the differences coming from arrhythmia via this process. The proposed algorithm using ELM as a classifier show high discrimination performance between normal beat and PVC. From the experimental results on MIT-BIH arrhythmia database the performances of the proposed algorithm are 98.1% in accuracy, 93.0% in sensitivity, 96.4% in positive predictivity, and 0.8% in false positive rate. This results are similar or higher then results of existing researches in spite of small human intervention.

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References

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