Model based analysis of the effects of respiration signal parameters on heart rate variability
2006 IEEE 14th Signal Processing and Communications Applications Conference
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In this study, Ursino and Magosso model that includes respiration effect on cardiovascular system is implemented using Matlab. The simulations are performed to investigate the effects of respiration rate, tidal volume and expiration-inspiration time ratio on Heart Rate Variability (HRV) signals. Power Spectral Density (PSD) of HRV signals that are obtained from model simulation was determined by Periodogram and Yule-Walker methods. There is not a significant difference between the PSDs, obtained by the two methods. The simulation results that are obtained by changing respiration rate and tidal volume, are consistent with previous experimental studies reported in the literature. However the model does not include a mechanism that accounts for the effect on HRV of the rate of change of lung volume. This is conjectured to be the reason for why model results and experimental observations are not in complete conformity when the effect of inspiration-expiration time ratio on HRV is studied. © 2006 IEEE.
KeywordsHeart Rate Variability (HRV) signals
Model based analysis
Power spectral density