2002, Vol.5, No.4, pp.418-427
One of the most successful applications of synergetics
is the analysis and modelling of human movement coordination. The
celebrated Haken-Kelso-Bunz [1] model has had a profound
impact in the field of kinesiology. Here we want to discuss a
generalization of a modelling concept that was first introduced
in [2],[3] to the study of non-linear, chaotic
behavior under the influence of stochastic perturbations. Instead
of ordinary differential equations (ODEs) the use of iterative
maps has several advantages in a number of applications. The
particular class of models that we want to focus on here, are
piece-wise linear maps that capture important features of smooth
non-linear maps and are especially appropriate for the study of
stochastic systems. Finally we will generalize the concept of
iterative maps of low-dimensional systems to a general class of
models of systems of arbitrary dimension with multiple
time-scales. We apply these models to the situation of human
isometric force production. For most types of coordinated movement
or force production various sensory-motor control loops are
involved (see e.g. [4]. Our main result is that the model
was shown to simulate the basic findings of the structure of human
force variability that decreasing variability is correlated with
an increase in dynamical complexity as measured with the
"Approximate Entropy (ApEn)" statistics [5].
Furthermore we could demonstrate how stochastic perturbations can
actually increase movement accuracy.
Key words: discrete stochastic nonlinear dynamics, iterative maps,
kinesiology, human movement
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