Mathematical Modeling Techniques of the Cardiorespiratory System and Quantification of the Autonomous Nerve System: Frequency Domain Analysis
AbstractThe analysis of heart rate variability (HRV) has been commonly used as a tool for the generation of quantitative measures of the autonomic nervous system. The study of HRV is based on the analysis of the spectrum of the R-R interval (RRI), obtained from the electrocardiogram (ECG). Studies based on HRV have brought about important insights into disorders in the regulation of autonomic function. However, this technique presents certain limitations. For instance, it assumes that observed variations in frequency are due only to changes in the cardiac autonomic system. Nonetheless, variations in respiratory depth and frequency are known to influence RRI spectrum. On the other hand, by using mathematical modeling techniques of the cardiorespiratory system, causal relationship between the different variables can be imposed. This allows the investigator to focus on the relationships between pairs of cardiorespiratory variables, such as on the influences of respiration on the RRI signal. Through data available on the Physionet website, the work aims to determine age dependent changes in the cardiorespiratory system, using data from healthy patients, using both HRV analysis and a technique based on a model of the cardiorespiratory system. For this study, the concepts of signal processing, power spectral density and system identification were used. From the data obtained through both techniques, quantitative measures of the autonomic system were obtained for younger and older subjects and subsequently compared. The results show the effectiveness of both techniques in distinguishing the different groups. This supports the concept that for a better understanding of the cardiorespiratory system both techniques should be employed in the study.