A nonlinear model for predicting ECG R-R interval variation based on the evolutionary computation approach

Bo Yeon Kim, Yun Seok Chang, Kwang Suk Park

Research output: Contribution to journalArticle

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Abstract

The study proposes a modeling method for nonlinear system, which predicts characteristics of the ECG R-R interval variation. For determining model equation, we adopted genetic programming method that the chromosome represented the model equation consisting of time-delayed variables, constants, and four arithmetic operators. By the genetic programming the regressive nonlinear equations were produced and evolved to find the optimal model equation which could simulate the spectral, statistical and nonlinear behavior of the given R-R interval dynamics. Experimental results showed that the evolutionary approach could find the equation that simulates the spectral and chaotic dynamics of the given signal. Therefore the proposed evolutionary approach is useful for the system identification of the nonlinear biological system.

Original languageEnglish
Pages (from-to)378-386
Number of pages9
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2657
StatePublished - 1 Dec 2003

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