Abstract: Non-stationary trend in R-R interval series is
considered as a main factor that could highly influence the evaluation
of spectral analysis. It is suggested to remove trends in order to obtain
reliable results. In this study, three detrending methods, the
smoothness prior approach, the wavelet and the empirical mode
decomposition, were compared on artificial R-R interval series with
four types of simulated trends. The Lomb-Scargle periodogram was
used for spectral analysis of R-R interval series. Results indicated that
the wavelet method showed a better overall performance than the other
two methods, and more time-saving, too. Therefore it was selected for
spectral analysis of real R-R interval series of thirty-seven healthy
subjects. Significant decreases (19.94±5.87% in the low frequency
band and 18.97±5.78% in the ratio (p
Abstract: A five-class density histogram with an index named cumulative density was proposed to analyze the short-term HRV. 150 subjects participated in the test, falling into three groups with equal numbers -- the healthy young group (Young), the healthy old group (Old), and the group of patients with congestive heart failure (CHF). Results of multiple comparisons showed a significant differences of the cumulative density in the three groups, with values 0.0238 for Young, 0.0406 for Old and 0.0732 for CHF (p