An optimal term selection scheme for the Volterra system model applied to the analysis of heart rate fluctuations

Proposes a new method of selecting effective terms of Volterra type nonlinear bio-system models. An efficient algorithm combining genetic algorithm with the householder transform has been introduced for selecting terms which contribute to the AIC (Akaike´s Information Criteria) value reduction. Computer simulation confirmed that the considerable reduction of the number of necessary Volterra coefficients has been achieved by the proposed method. The method has been also applied to the estimation of transfer characteristics from the instantaneous lung volume to heart rate fluctuations as an illustrative example.