Predictability analysis of the heart rate variability

Author

Cai, Zhijie ; Tang, Liping ; Ruan, Jiong ; Xu, Shixiong ; Gu, Fanji

Author_Institution

Nonlinear Sci. Res. Center, Fudan Univ., Shanghai, China

Volume

3

fYear

2001

fDate

2001

Firstpage

1642

Abstract

Sixteen acute myocardial infarction (AMI) inpatients were selected randomly. Sixteen normal subjects were selected as a control group, their age and sex matched to the AMI group. The patient´s HRV were recorded 9 times after AMI in half a year. Some predictability measures based on neural network learning were used to analyze these data. It was found that for normal subjects, their HRVs were chaotic, but for AMI patients, their HRVs could be either periodic or stochastic. For all the sixteen AMI patients, some of the predictability measures kept one order lower than the one for normal subjects at least for six months after AMI. Therefore, it can be a sensitive index for measuring the damage of the heart due to the AMI attack

Keywords

cardiology; learning (artificial intelligence); medical computing; neural nets; AMI patients; acute myocardial infarction; heart rate variability; learning; neural network; predictability; Ambient intelligence; Cardiac disease; Chaos; Data analysis; Electrocardiography; Heart rate variability; Hospitals; Myocardium; Neural networks; Stochastic processes;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.938407

Filename

938407