Document Type
Thesis
Date of Award
Fall 1-31-1996
Degree Name
Master of Science in Biomedical Engineering - (M.S.)
Department
Biomedical Engineering Committee
First Advisor
Stanley S. Reisman
Second Advisor
David S. Kristol
Third Advisor
Thomas W. Findley
Abstract
Power spectral analysis of heart rate and systolic arterial blood pressure variability provides a window to the activity of the autonomic nervous system. To derive power spectra from raw blood pressure and electrocardiogram signals, many steps of signal processing must be performed. Most popular methods of spectral analysis require evenly spaced samples; therefore interpolation and resampling techniques must be used.
The results of the present study indicate that different interpolation techniques result in spectral distortions that vary depending upon the interpolation methods used as well as physiological parameters such as heart and respiration rate. Different interpolation methods applied to heart rate and systolic blood pressure data are compared and evaluated in an attempt to determine optimal interpolation methods for each type of data. Algorithms designed to derive systolic arterial pressure variability spectra from raw blood pressure data based on these results are also presented.
These algorithms were used to perform analysis of blood pressure signals. The resulting systolic arterial pressure variability spectra were then compared to respiratory data as well as spectra of heart rate variability. A method was developed that provides a means of explaining the interaction of the parasympathetic and sympathetic influence on heart rate in terms of systolic arterial blood pressure and heart rate variability spectra.
Recommended Citation
O'Bara, Christopher, "Signal processing techniques in heart rate and systolic arterial blood pressure variability studies" (1996). Theses. 1108.
https://digitalcommons.njit.edu/theses/1108
