ABSTRACT
The paper presents analysis of the generic transfer function (TF) between Electrical Bioimpedance (EBI) measured non-invasively on the wrist and Central Aortic Pressure (CAP) invasively measured at the aortic root. Influence of the Heart Rate (HR) variations on the generic TF and on reconstructed CAP waveforms is investigated. The HR variation analysis is provided on a single patient data to exclude inter-patient influences at the current research stage. A new approach for the generic TF estimating from a data ensemble is presented as well. Moreover, an influence of the cardiac period beginning point selection is analyzed and empirically optimal solution for its selection is proposed.
Subject(s)
Heart Rate , Aorta , Arterial Pressure , Electricity , HumansABSTRACT
The paper presents a method for adaptive decomposition of an electrical bio-impedance (BI) signal into two components: cardiac and respiratory. The decomposition of a BI signal is not a trivial process because of the non-stationarity of the signal components and overlapping of their harmonic spectra. An application specific orthonormal basis (ASOB) was designed to solve the decomposition task using the Jacobi weighting function in the standard Gram-Schmidt process. The key element of the bio-impedance signal decomposer (BISD) is a model of the cardiac BI signal, which is constructed from the components of the ASOB and is intended for use in the BISD for on-line tracking of the cardiac BI signal. It makes it possible to separate the cardiac and respiratory components of the total BI signal in non-stationary conditions. In combination with the signal-shape locked loop (SSLL), the BISD allows us to decompose the BI signals with partially overlapping spectra. The proposed BISD based method is accomplished as a PC software digital system, but it is oriented towards applications in portable and stationary cardiac devices and in clinical settings.
