Document Type
Thesis
Date of Award
Fall 1-31-2001
Degree Name
Master of Science in Biomedical Engineering - (M.S.)
Department
Biomedical Engineering Committee
First Advisor
Ronald H. Rockland
Second Advisor
Stanley S. Reisman
Third Advisor
Richard A. Foulds
Abstract
Cardiovascular disease is the primary cause of death in the adult population. Half of these cardiac deaths occur as sudden death. Some of the parameters from the surface ECG recording (a noninvasive technique) carry important information and have special significance in research, as they are good indicators of diseases leading to heart attacks, sudden cardiac death and other similar cardiac problems. Measurement of QT interval variability and heart rate variability are two such parameters, which has received much attention of researchers.
An algorithm has been developed to measure and compare the two significant parameters, the QT interval variability and the heart rate variability. Agilent's VEE Pro© 6.0 software is used as graphical tool to implement signal processing operations. This algorithm detects peaks from the ECG including the Q, R, S, T and the end of the T wave. These peaks are use to calculate both, the heart rate variability and QT interval variability. The algorithms have been tested on normal and diseased patient data from the standard MIT ECG library to prove the accuracy and reproducibility of the system. Observations about the amount of influence of the autonomic nervous system on the heart rate variability and QT interval variability have been carried out. Results indicate that behavior of the autonomic nervous system is different for normal patient and diseased patients. Diagnosis of Coronary Artery Disease is done very reliably using this system.
Recommended Citation
Oza, Taral, "An automated approach for comparative analysis of interval and heart rate variability" (2001). Theses. 726.
https://digitalcommons.njit.edu/theses/726
