Date of Award

Summer 1999

Document Type


Degree Name

Master of Science in Biomedical Engineering - (M.S.)


Biomedical Engineering Committee

First Advisor

Stanley S. Reisman

Second Advisor

John Tavantzis

Third Advisor

Ronald H. Rockland


Long-term heart rate variability measurement is important in understanding the activities of the autonomic nervous system. Many methods and implications of long-terrn HRV were available in the literature. The first two studies focused on two data analysis techniques that were used on a normal subject. The first study focused on the 1/f fluctuations. For this analysis, three 1 1h heart rate variability data sets were collected with the Polar Vantage NV. A LabVIEW program was used to calculate the power spectrum of the heart rate, and then the 1/f line was calculated by taking the log of the power spectrum versus the log of the frequency. The second study focused on the 24h circadian rhythm characteristics from the low frequency and high frequency portions of the HRV spectrum. The same watch was used to collect three 22h heart rate variability data sets. The 22h data sets were divided in to 15min segments. The same computer algorithm was used to calculate the low and high frequency portions of the power spectrum. The plot of the low frequency and high frequency versus time was determined.

The third study focused on the non-linear dynamics of the HRV. For this analysis, fifteen long-term ECG data sets were collected with the Polar NV watch from 2 cardiac patients and 3 healthy subjects. 1h interval was obtained from each data set, and each data set was analyzed using the Benoit 1.1 R/S analysis program and the LabVIEW standard deviation program. The results showed that in normal subjects at rest, the 1/f fluctuation was observed and the 2-hour circadian rhythm was present. The non-linear dynamics of HRV was useful in separating the healthy from the cardiac patients.