심장 박동의 카오스적 분석을 위한 시계열 데이터 표현 방법

Abstract

Strange attractor can be constructed from time series data such as heart sound. In the area of the recognition and diagnosis problem, signal presentation method is very important because good features can be detected from good presentation. This paper discusses a way to extract a cycle from strange attractor and introduce new attractor construction method using autocorrelation value of the heart rate. The result shows well-formed attractor and good ability for extraction features. Largest Lyapunov Exponent is used to check whether the attractors provide distinguish abilities among different types of heart rate. The result shows good points that can be applied to some areas of human signal processing.