Continuous Quantification of Baroreflex and Respiratory Control of Heart Rate by Use of Bivariate Autoregressive Techniques

Background: Normal cardiovascular control involves nonstationary complex interactions between a variety of variables such as heart rate (HR), arterial blood pressure (ABP), and respiratory activity. Methods: To account for both the complexity and transient nature of these phenomena, a closed‐loop bivariate and time‐variant (moving window) model was implemented using autoregressive parametric techniques to identify the typical HR and ABP spectral parameters of low frequency power (LF, 0.03–0.15 Hz), high frequency power (HF, 0.15–0.45 Hz), and their ratio LF/HF. In addition, cross‐parameters, such as the gain, phase, and coherent power, between HR, ABP, and changes in instantaneous lung volume (ILV) were computed in both the LF and HF regions. Results: The cross‐relations included the HR baroreflex (ABP‐HR, alpha), respiratory sinus arrhythmia (ILV‐HR), the mechanical influence of respiration (ILV‐ABP), and the mechanical feedforward of HR (HR‐ABP, beta). The analyses were performed on data from a gradual tilt protocol, which simulates the physiological nonstationarities encountered in daily life. Conclusions: The results were similar to those obtained using a bivariate batch (nonmoving window) Levinson‐Wiggins‐Robinson algorithm, but the time‐variant technique was able to provide nearly continuous parameters, allowing for a real‐time continuous monitoring of circulatory control.