Journal of Biomedical Physics and Engineering (Sep 2014)
Quantification the Effect of Ageing on Characteristics of the Photoplethysmogram Using an Optimized Windkessel Model
Abstract
Background: With increasing age, some changes appeared in specifications of vessels which including dimensions and elasticity in theirs. The changes in parameters such as resistance, inertance and compliance vessels appear and eventually changes in the environmental pulse releases are in circulation. These changes clearly appear in specification of photoplethysmogram particularly in the size and position signals second peak is observed. Aim and scope: The aim of study was to Circulatory system modeling using windkessel electrical model for evalution blood flow and Its matching with the photoplethysmogram’s signal for investigate the reasons for changes of Characteristics of the Photoplethysmogram. The first purpose of this paper is to examine the age-related parameters in the Photoplethysmogram’s signal and finally the diagnosis of cardiovascular disease using the model and photoplethysmogram’s signal. Methods: In this study we followed some of these effects to the circulatory system by using the windkessel electrical model. The algorithm in this project appeared by optimization with the matrix coefficients of state space windkessel electrical model. Optimize of the coefficients matching with the output of the model and the photoplethysmogram’s signal. Photoplethysmogram’s signals from 50 healthy subjects with the age range of 20 to 50 years, shows that outputs the model and photoplethysmogram’s signal in terms of error rate and cross-correlation algorithm in a fully automate, was consistent. Wavelength of the Photoplethysmogram’s signals were 950 nm and The sampling rate was set at 50 Hz. Results: Simulation results show that aging reduces the signal amplitude and delay of the second peak occurs. These changes were seen as reduce the rate of compliance and increase the rate of resistance and inertance windkessel electrical model of circulation. Conclusion: The high accuracy of the results led to being able to identify the age range and some cardiac arrhythmias in individuals. All the simulations were done in matlab software environment.
