  The CVS is composed of numerous interacting and dynamically regulated
physiological subsystems which each generate measurable periodic components
such that the CVS can itself be presented as a system of weakly coupled
oscillators. The interactions between these oscillators generate a chaotic
blood pressure waveform signal, where periods of apparent rhythmicity are
punctuated by asynchronous behaviour. It is this variability which seems to
characterise the normal state. We used a standard experimental data set for the
purposes of analysis and modelling. Arterial blood pressure waveform data was
collected from conscious mice instrumented with radiotelemetry devices over
$24$ hours, at a $100$ Hz and $1$ kHz time base. During a $24$ hour period,
these mice display diurnal variation leading to changes in the cardiovascular
waveform. We undertook preliminary analysis of our data using Fourier
transforms and subsequently applied a series of both linear and nonlinear
mathematical approaches in parallel. We provide a minimalistic linear and
nonlinear coupled oscillator model and employed spectral and Hilbert analysis
as well as a phase plane analysis. This provides a route to a three way
synergistic investigation of the original blood pressure data by a combination
of physiological experiments, data analysis viz. Fourier and Hilbert transforms
and attractor reconstructions, and numerical solutions of linear and nonlinear
coupled oscillator models. We believe that a minimal model of coupled
oscillator models that quantitatively describes the complex physiological data
could be developed via such a method. Further investigations of each of these
techniques will be explored in separate publications.
