Biomedical Engineering Reference
In-Depth Information
bdSVW (bridge detrended scaled windowed variance)
(21)
.The
intensity-coded parameter is the percent estimates falling into the
range of
H
true
±
0.05. The light areas on the plot designate the
range of signal lengths where reliable values of
H
were obtained
from the respective methods. It should be noted, however, that
dynamic signals present themselves as complex only if the fractal
methods for their analysis assume proper application of a complex
protocol, as suggested earlier.
6. Temporal
(1 Dimensional)
Fractal Analysis
As first choice of applying fractal analysis to characterize tempo-
ral complexity of a dynamically fluctuating physiological parame-
ter, we chose the cortical perfusion signal obtained by LDF from
the brain cortex of anesthetized rats (
Fig. 2.3
)
(14, 16, 22)
.The
dynamics in this signal is present at rest without any change in the
functional state of the brain, and in spite of its random appear-
ance, proved representative of the self-similar order of a tem-
poral fractal. When the cerebrovascular system is challenged by
graded arterial hypotension, the fractal correlation in the signal
was found to persist
(16)
. In spite of the challenge in perfu-
sion pressure, the fractal correlation of presumably the flowmo-
tion pattern remains stable as demonstrated by Hurst exponents
falling into the narrow range of 0.25-0.29. This can be taken as
an indication of a strong self-organization
(23, 24)
of the regional
flowmotion emerging from rhythms intrinsic to the vascular seg-
ments and proved quite immune to strong drop in perfusion
pressure.
The presence of a fractal, spontaneous, hemodynamic fluc-
tuation in the brain cortex was later demonstrated in humans
(25)
. Cerebral blood volume (CBV) was found to fluctuate in
a manner dependent on age and gender alike
(15)
(
Fig. 2.5
).
The motivation behind these studies was to demonstrate -
using a noninvasive measurement of a cardinal cerebrovascu-
lar parameter (CBV by a single NIRS probe) and the above
described set of fractal tools - whether age-related stiffening
of the cerebral vessels would have any significant influence on
the fluctuation patterns thought to be impacted by vasomo-
tion and/or flowmotion within the arterial tree. An impor-
tant finding of this study was that a gradual shift in this pat-
tern as characterized by the spectral index began to develop in
the young adult male, while this tendency was found absent in
the age-matched female groups of the premenopausal female.
However, when the female hormonal protection of the cere-
bral vasculature was presumably removed by menopause, the
spectral index emerged to be more powerful (
Fig. 2.5
)
(15)
.
