Detection of ST-T Episode Based on the Global Curvature of Isoelectric Level in ECG

ECG 신호의 global curvature를 이용한 ST-T 에피소드 검출

  • 강동원 (연세대 보건과학대학 의공학과) ;
  • 전대근 (연세대 보건과학대학 의공학과) ;
  • 이경중 (연세대 보건과학대학 의공학과) ;
  • 윤형로 (연세대 보건과학대학 의공학과)
  • Published : 2001.04.01

Abstract

This paper describes an automated detection algorithm of ST-T episodes using global curvature which can connect the isoelectric level in ECG and can eliminate not only the slope of ST segment, but also difference of the baseline and global curve. This above method of baseline correction is very faster than the classical baseline correction methods. The optimal values of parameters for baseline correction were found as the value having the highest detection rate of ST episode. The features as input of backpropagation Neural Network were extracted from the whole ST segment. The European ST-T database was used as training and test data. Finally, ST elevation, ST depression and normal ST were classified. The average ST episode sensitivity and predictivity were 85.42%, 80.29%, respectively. This result shows the high speed and reliability in ST episode detection. In conclusion, the proposed method showed the possibility in various applications for the Holter system.

Keywords

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