Noise-resistant vascular parameter identification for artery testing

Abstract

Artery testing prevents us from atherosclerotic disease and several methods to evaluate physiological change are performed. However, comprehensive estimation methods of physiological characteristics of blood vessel are not well established and measured data are influenced by physiological conditions. Vascular system model can improve artery testing because parameters of the model indicate the characteristics of blood vessel. Our laboratory has been developing vascular system model and identification method of the model, which can estimate the characteristics of blood vessel. The purpose of this study is to construct and verify a noise-resistant method of vascular parameter identification for artery testing that can identify the parameter accurately regardless of noise. We developed a physiological model of vascular system and parameter identification method. The identification method includes filter that can eliminate noise. In order to verify the performance of the identification method, we carried out a computer simulation experiments. We constructed a physiological model on a computer with preset parameters. Simulations were performed in several different parameter settings with data that contain 10% white noise. We also performed simulations using data with 5% and 20 % white noise. Identification results showed that maximum values of errors were 0.7200%, 4.947% and 11.56% for data with 5%, 10% and 20% noise intensity, respectively. Those results showed that our method was able to reduce influence of noise and to identify the vascular parameters accurately regardless of noise.