njit-etd2003-081 - New Jersey Institute of Technology

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5. To use the best choice of the time-frequency distribution and wavelet distribution
performed on the heart rate variability signal to quantify the area under the low
frequency and high frequency ranges during different breathing conditions (room air, 30
% oxygen supplement) at rest and exercise as reflected in the heart rate variability signal
of COPD subjects.
6. To use coherence and partial coherence in learning the relationships between heart
rate variability, blood pressure variability and respiration as well as the sympatho-vagal
balance of the autonomic nervous system.
7. To develop a general class of Exogenous Input AutoRegressive (ARX) models for
the cardiovascular system from experimental data using system identification
techniques. Once the model is obtained it can be used for COPD parameter testing
(since the values of some of these parameters may not be attainable for COPD patients).
This may provide COPD cardiovascular models for further study of the disease
noninvasively.
8. To use principal component analysis and cluster analysis as tools that allow
diagnosing the COPD severity noninvasively and accurately. This may help physicians
further in deciding who may be best suited for lung reduction surgery.
This work clarifies some of the questions about heart rate variability on COPD
subjects which are of fundamental importance in diagnosing the severity of the disease,
in assessing the benefit of the rehabilitation procedure and ultimately in determining
who may benefit the most from lung reduction surgery. The major contributions of this
work can be summarized as follows: