State space modeling of cardiovascular regulation

A linear state-space model (LSSM) of cardiovascular regulation was developed using measurements of instantaneous lung volume (ILV), heart rate (HR) and arterial blood pressure (APE) in 6 normal human volunteers (male, age: 22-30 yr., median 24 yr). The system order and an orthogonal basis for the state space of the system were estimated using the singular value decomposition (SVD) of a data matrix. The LSSM parameters were then found from the solution of an over-determined set of equations in least squares. The LSSM improves the phase function estimate and shows that (1) HR and ABP is most responsive to slow changes in ILV tidal volume when mean breathing frequency is 0.2-0.4 Hz (p>0.95) although system gain at these frequencies is reduced. (2) ANS responsiveness to changes in tidal volume increases linearly with frequency at slow (0.05-0.1 Hz) breathing rates (p>0.95). It is concluded that paced breathing system identification is a fast and non-invasive way to accurately characterize some of the physiological links between respiration, blood pressure and heart rate variability