132
H. Schmid-Schönbein
7.5 Summarising Discussion—Physiological Analysis
by Way of Identification of Temporal Patterns
It is trivial to state that the measurements of the dynamics of cardiovascular reactions
are hampered, as it were, by three simple “facts” of life: the data obtained
• are notoriously noise afflicted,
• are derived from reactions with very pronounced nonlinearity (i.e. unpredictable
cause–effect relationship typical for vasomotor activities and
• are naturally non-stationary.
Each and every measurement reported in this review reflects the situation topologically dominated by Koepchen’s and Haken’s “quasi-attractors”, which is perhaps
a triviality reflecting the obvious fact that “transiency is normalcy” in all systems
driven by central nervous systems. It is also trivial to state that once the natural “nonlinearity” and, most importantly, the eruptivity of cardiovascular movement patterns
have been accepted as “fact of life”, all attempts to use conventional data compression stratagems must be discontinued: the “calculation” of average and mean can be
said to represent illegitimate destruction of information (“data murder”), and even
the calculation of “power” in conventional Fourier spectra leads to serious information distortion (“involuntary data slaughter”). In the future, such procedures will
no longer be acceptable: in the project of physiological synergetics, much more
“system appropriated” data compression stratagems have been developed, which on
the one hand are intuitively comprehensible for physicians (most of them are excellent pattern recognisers) and still convey the kind of information used in nonlinear
sciences. Re-reviewed under the synergetic and physiological “logic” here delineated,
one must take biological “ordering” in the realm of the cutaneous and the mucosal
microcirculation as the consequence of “drive dependent consensualisation” of a
priori existing movement patterns. In being able to identify quite easily the temporal
ordering in the “double plots”, one can apply conventional physiological concepts
in terms of “latent information” extractable from simple non-invasive measurement.
The logic presented concerns the dynamics of cardiac and non-cardiac determinants
for the displacement modes of blood cells in the microvascular beds. The techniques
used in “computer-based non-invasive cardiovascular diagnostics” indeed prove to
be ideal for the task of providing kinetic long term information from a wide spectrum
of “sources”. As one can monitor both the movement patterns of accelerated erythrocytes and the variations in blood content of microvascular beds, one can quite easily
identify the main “attractors” for rhythmically modulated processes. They depend on
the periodically varying influence of other physiological systems onto the dynamics
of a hypercomplex flow situation which cannot possibly be assessed by direct means.
Simple concept makes it comprehensible that there must be a superposition of the
movement pattern of these “attractors” upon the cardially accelerated basic acceleration–deceleration scenarios in the blood movement driven by the heart through
microvessels. The pragmatics results of such a straightforward logic spring to the eye:
since in the normal cutaneous microcirculation there are no sinusoidal fluctuations (in
H. Schmid-Schönbein
7.5 Summarising Discussion—Physiological Analysis
by Way of Identification of Temporal Patterns
It is trivial to state that the measurements of the dynamics of cardiovascular reactions
are hampered, as it were, by three simple “facts” of life: the data obtained
• are notoriously noise afflicted,
• are derived from reactions with very pronounced nonlinearity (i.e. unpredictable
cause–effect relationship typical for vasomotor activities and
• are naturally non-stationary.
Each and every measurement reported in this review reflects the situation topologically dominated by Koepchen’s and Haken’s “quasi-attractors”, which is perhaps
a triviality reflecting the obvious fact that “transiency is normalcy” in all systems
driven by central nervous systems. It is also trivial to state that once the natural “nonlinearity” and, most importantly, the eruptivity of cardiovascular movement patterns
have been accepted as “fact of life”, all attempts to use conventional data compression stratagems must be discontinued: the “calculation” of average and mean can be
said to represent illegitimate destruction of information (“data murder”), and even
the calculation of “power” in conventional Fourier spectra leads to serious information distortion (“involuntary data slaughter”). In the future, such procedures will
no longer be acceptable: in the project of physiological synergetics, much more
“system appropriated” data compression stratagems have been developed, which on
the one hand are intuitively comprehensible for physicians (most of them are excellent pattern recognisers) and still convey the kind of information used in nonlinear
sciences. Re-reviewed under the synergetic and physiological “logic” here delineated,
one must take biological “ordering” in the realm of the cutaneous and the mucosal
microcirculation as the consequence of “drive dependent consensualisation” of a
priori existing movement patterns. In being able to identify quite easily the temporal
ordering in the “double plots”, one can apply conventional physiological concepts
in terms of “latent information” extractable from simple non-invasive measurement.
The logic presented concerns the dynamics of cardiac and non-cardiac determinants
for the displacement modes of blood cells in the microvascular beds. The techniques
used in “computer-based non-invasive cardiovascular diagnostics” indeed prove to
be ideal for the task of providing kinetic long term information from a wide spectrum
of “sources”. As one can monitor both the movement patterns of accelerated erythrocytes and the variations in blood content of microvascular beds, one can quite easily
identify the main “attractors” for rhythmically modulated processes. They depend on
the periodically varying influence of other physiological systems onto the dynamics
of a hypercomplex flow situation which cannot possibly be assessed by direct means.
Simple concept makes it comprehensible that there must be a superposition of the
movement pattern of these “attractors” upon the cardially accelerated basic acceleration–deceleration scenarios in the blood movement driven by the heart through
microvessels. The pragmatics results of such a straightforward logic spring to the eye:
since in the normal cutaneous microcirculation there are no sinusoidal fluctuations (in