Blind Identification of Two-Channel IIR Systems With Application to Central Cardiovascular Monitoring

This paper presents a new approach to blind identification of a class of two-channel infinite impulse response (IIR) systems with applicability to clinical cardiovascular monitoring. Specifically, this paper deals with a class of two-channel IIR systems describing wave propagation dynamics. For this class of systems, this paper first derives a blind identifiability condition and develops a blind identification algorithm, which is able to determine both the numerator and denominator polynomials of the channel dynamics uniquely. This paper also develops a new input signal deconvolution algorithm that can reconstruct the input signal from the identified two-channel dynamics and the associated two-channel measurements. These methods are applied to identify the pressure wave propagation dynamics in the cardiovascular system and reconstruct the aortic blood pressure and flow signals from blood pressure measurements taken at two distinct extremity locations. Persistent excitation, model identifiability, and asymptotic variance are analyzed to quantify the method's validity, accuracy, and reliability without employing direct measurement of the aortic blood pressure and flow signals. The experimental results based on 83 data segments obtained from a swine subject illustrate how the cardiovascular dynamics can be identified accurately and reliably, and the aortic blood pressure and flow signals can be stably reconstructed from two distinct peripheral blood pressure signals under diverse physiologic conditions.