12
V. Blazek
1.6 Comparing Measured Arterial rPPG and tPPG Signal
Waveform with Blood Pressure Waveform, Generated
with Arterial Tree Model in the Finger Tip
A computer model of hemodynamics in the human vascular system has been developed at the RWTH Aachen University in 1993 [38, 39] to investigate blood pressure,
blood flow and blood volume waveforms in major branches of the arterial tree as
well as in smaller digital arteries and arterioles of microvascular networks. The basic
units of the simulation model are vascular segments which are considered as thickwalled viscoelastic tubes with fixed coupling to the surrounding tissue. Blood motion
in moving elastic tubes is well described by the Navier–Stokes equation, which is
equivalent to conservation of momentum, and by the continuity equation, which is
equivalent to conservation of mass. A linear approximation Navier–Stokes equation leads to a relation between pressure gradient and flow. With an expression of
pressure diameter relation, utilizing the shell theory, hemodynamics is described in
completely analogous terms of electrical transmission line theory.
The growing algorithm used in the RWTH model of the human vascular tree is
based on the assumption that each dichotomous branching fulfils several bifurcation
rules while the entire tree fulfils the criterion of minimum blood volume and several
boundary conditions formed by anatomical constrains. The model grows successively
by adding new vessels to the pre-existing tree; each new vessel is connected to the
optimum side with respect to the growth criterion.
A detailed model of finger arteries of the index finger was published in [40].
This spherical network consists of 4000 arterial segments. In a study, photoplethysmographic measurements in reflection (rPPG) and transmission (tPPG) mode are
compared with peripheral blood pressure waveform. Subsequent to the size of vessels,
the calculated blood pressure waveforms are similar to the photoplethysmograms
detected in t- and r-sensor mode as shown in Fig. 1.8.
These results clearly demonstrate that using the T-mode sensor technology, dominantly microvessel hemodynamics are recorded. With the R-mode PPG sensors,
however, more hemodynamics in terminal microvessels are recorded (see Chap. 9).
In the evaluation of peripheral arterial pulse shape, it is, therefore, necessary to
always declare with which sensor modality the analyzed photoplethysmograms were
recorded (see Sect. 1.11.5 in this chapter).
1.7 Principle of Quantitative Photoplethysmography
The perfusion signal intensity detected by a PPG invariably depends on the following
parameters:
• The intensity of the input light,
• the wavelength of the input light,
V. Blazek
1.6 Comparing Measured Arterial rPPG and tPPG Signal
Waveform with Blood Pressure Waveform, Generated
with Arterial Tree Model in the Finger Tip
A computer model of hemodynamics in the human vascular system has been developed at the RWTH Aachen University in 1993 [38, 39] to investigate blood pressure,
blood flow and blood volume waveforms in major branches of the arterial tree as
well as in smaller digital arteries and arterioles of microvascular networks. The basic
units of the simulation model are vascular segments which are considered as thickwalled viscoelastic tubes with fixed coupling to the surrounding tissue. Blood motion
in moving elastic tubes is well described by the Navier–Stokes equation, which is
equivalent to conservation of momentum, and by the continuity equation, which is
equivalent to conservation of mass. A linear approximation Navier–Stokes equation leads to a relation between pressure gradient and flow. With an expression of
pressure diameter relation, utilizing the shell theory, hemodynamics is described in
completely analogous terms of electrical transmission line theory.
The growing algorithm used in the RWTH model of the human vascular tree is
based on the assumption that each dichotomous branching fulfils several bifurcation
rules while the entire tree fulfils the criterion of minimum blood volume and several
boundary conditions formed by anatomical constrains. The model grows successively
by adding new vessels to the pre-existing tree; each new vessel is connected to the
optimum side with respect to the growth criterion.
A detailed model of finger arteries of the index finger was published in [40].
This spherical network consists of 4000 arterial segments. In a study, photoplethysmographic measurements in reflection (rPPG) and transmission (tPPG) mode are
compared with peripheral blood pressure waveform. Subsequent to the size of vessels,
the calculated blood pressure waveforms are similar to the photoplethysmograms
detected in t- and r-sensor mode as shown in Fig. 1.8.
These results clearly demonstrate that using the T-mode sensor technology, dominantly microvessel hemodynamics are recorded. With the R-mode PPG sensors,
however, more hemodynamics in terminal microvessels are recorded (see Chap. 9).
In the evaluation of peripheral arterial pulse shape, it is, therefore, necessary to
always declare with which sensor modality the analyzed photoplethysmograms were
recorded (see Sect. 1.11.5 in this chapter).
1.7 Principle of Quantitative Photoplethysmography
The perfusion signal intensity detected by a PPG invariably depends on the following
parameters:
• The intensity of the input light,
• the wavelength of the input light,