The presence of long-range (fractal) correlations for healthy heartbeat fluctuations has important implications for understanding and modeling neuroautonomic regulation, as discussed below. A corollary question is whether pathologic states and aging are associated with distinctive alterations in these scaling properties which could be of practical diagnostic and prognostic use.
Analysis of data from patients with congestive heart failure is likely
to be particularly informative in assessing correlations under
pathologic conditions since these individuals have abnormalities in
both the sympathetic and parasympathetic control mechanisms
that regulate beat-to-beat variability [22]. Previous studies have
demonstrated marked changes in short-range heart rate dynamics in
heart failure compared to healthy function, including the emergence of
intermittent relatively low frequency (
cycle/minute) heart
rate oscillations associated with the well-recognized syndrome of
periodic (Cheyne-Stokes) respiration, an abnormal breathing pattern
often associated with low cardiac output [6, 22]. Of note is the
fact that patients with congestive heart failure are at very high risk
for sudden cardiac death.
Figure:
Plot of 
vs 
for three interbeat interval time
series: healthy young subject, elderly subject, and a subject with
congestive heart failure. Compared with the healthy young subject, the heart failure and healthy elderly subjects show different patterns of altered scaling behavior (see text).
Figure 6 compares a representative result of fractal scaling
analysis of representative 24-hour interbeat
interval time series from a healthy subject and a patient with
congestive heart failure. Notice that for large time scales
(asymptotic behavior), the healthy subject shows almost perfect
power-law scaling over more than two decades (
)
with 
(i.e., 1/f noise), while for the heart failure data set,
(closer to Brownian noise). This result indicates
that there is a significant difference in the scaling behavior between
healthy and diseased states, consistent with a breakdown in long-range
correlations.
To systematically study the alteration of long-range correlations with
life-threatening pathologies, we have analyzed cardiac interbeat data
from three different groups of subjects [12, 23]: (i) 29
adults (17 male and 12 female) without clinical evidence of heart
disease (age range: 20-64 years, mean 41), (ii) 10 subjects with
fatal or near-fatal sudden cardiac death syndrome (age range: 35-82
years) and (iii) 15 adults with severe heart failure (age range: 22-71
years; mean 56). Data from each subject contained approximately 24
hours of ECG recording encompassing 
heartbeats.
For the normal control group, we observed 
(mean
value 
S.D.). These results confirm that healthy heart rate
fluctuations exhibit long-range power-law (fractal) correlation
behavior over three decades, similar to that observed in many
dynamical systems far from equilibrium [24, 25]. Furthermore,
both pathologic groups showed significant deviation of the long-range
correlations exponent 
from the normal value, . For
the group of heart failure subjects, we found that
, while for the group of sudden cardiac death
syndrome subjects, we found that 
. Of particular
note, we obtained similar results when we divided the time series into
three consecutive subsets (of 
hours each) and repeated the
above analysis. Therefore our findings are not simply attributable to
different levels of daily activities.
Similar analysis was applied to study the effect of physiologic aging. Ten young (21-34 yr) and ten elderly (68-81 yr) healthy subjects underwent 2 hours of continuous supine resting ECG recording (Fig. 6). In healthy young subjects, the scaling exponent had an value close to 1.0. In the group of healthy elderly
subjects, the interbeat interval time series showed two scaling
regions. Over the short range, interbeat interval fluctuations
resembled a random walk process (Brownian noise, 
),
whereas over the longer range they resembled white noise
(
) Short-range (
) and long-range (
)
exponents were significantly different in the elderly subjects
compared with young [27]. Of interest, the alterations of
scaling behavior associated with physiologic aging exhibited different patterns
compared to the changes associated with heart failure.