Proceedings of the KOSOMBE Conference (대한의용생체공학회:학술대회논문집)

The Korean Society of Medical and Biological Engineering (대한의용생체공학회)
권호 표지

ECG Pattern Classification Using Back-Propagation Neural Network

역전달 신경회로망을 이용한 심전도 패턴분류

  • Lee, Je-Suk (Dept. of Electrical Engineering, Yonsei University) ;
  • Kwon, Hyuk-Je (Dept. of Electrical Engineering, Yonsei University) ;
  • Lee, Jung-Whan (Dept. of Electrical Engineering, Yonsei University) ;
  • Lee, Myoung-Ho (Dept. of Electrical Engineering, Yonsei University)
  • 이제석 (연세대학교 전기공학과) ;
  • 권혁제 (연세대학교 전기공학과) ;
  • 이정환 (연세대학교 전기공학과) ;
  • 이명호 (연세대학교 전기공학과)
  • Published : 1992.11.13
Download PDF
⟨ Previous Next ⟩

Abstract

This paper describes pattern classification algorithm of ECG using back-propagation neural network. We presents new feature extractor using second order approximating function as the input signals of neural network. We use 9 significant parameters which were extracted by feature extractor. 5 most characterized ECG signal pattern is classified accurately by neural network. We use AHA database to evaluate the performance ol the proposed pattern classification algorithm.

Keywords