njit-etd2003-081 - New Jersey Institute of Technology

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In addition, group-average transfer function estimates were derived for all the studies by
using a weighting algorithm based on the coherence estimates 7 2 (f) for each individual
transfer function [29].
However, in this research the MATLAB System Identification toolbox is used to
estimate the transfer function. As one can see below, with minor modification to the
programs in the toolbox, the model transfer function can be easily obtained and the results
are quite acceptable. Once the transfer function is obtained, the cardiovascular system
model for normal subjects is estimated. It can now be examined and be used for further
investigation. This estimated model of normal subjects would also be used as reference
in developing the diseased cardiovascular model for COPD patients.
Figures 5.55 — 5.59 present the case of a file from a normal subject resting and
breathing at 14 breaths per minute (bpm). The HRV iibi signal was derived from the
ECG signal and the first half of this signal was used as output of the cardiovascular model
while the first half of the respiration signal was used as the single input. The two halves
of the input/output were used to calculate the coefficients of the transfer function for the
model.
Figure 5.55 shows the rsp input and the iibi signal derived from the actual ECG as
output. Below the figure are the transfer function coefficients of the estimated model in
System Identification format. The basic format for representing models in the System
Identification Toolbox is called the theta format. It stores all relevant information about
the model structure used, including the values of the estimated parameters, the estimated