TITLE:
The Compound Indexing of Human Self-Similar Behavioural Patterns
AUTHORS:
Petr Kloucek, Pavel Zakharov, Armin von Gunten
KEYWORDS:
Behavioural Complexity, Physiological and Behavioural Surrogate Data, Behavioural Entropy, Behavioural Hysteresis, Seld-Similar Normally Distributed Precesses, Non-Integer Hausdorff-Besicovitch Dimension, Hurst Exponent
JOURNAL NAME:
Applied Mathematics,
Vol.7 No.17,
November
23,
2016
ABSTRACT: Applications of a constitutive framework
providing compound complexity analysis and indexing of coarse-grained
self-similar time series representing behavioural data are presented. A notion
of behavioural entropy and hysteresis is introduced as two different forms of
compound measures. These measures provide clinically applicable complexity
analysis of behavioural patterns yielding scalar characterisation of time-varying
behaviours registered over an extended period of time. The behavioural data are
obtained using body attached sensors providing non-invasive readings of heart
rate, skin blood perfusion, blood oxygenation, skin temperature, movement and
steps frequency. The results using compound measures of behavioural patterns of
fifteen healthy individuals are presented. The application of the compound
measures is shown to correlate with complexity analysis. The correlation is
demonstrated using two healthy subjects compared against a control group. This
indicates a possibility to use these measures in place of fractional dimensions
to provide a finer characterisation of behavioural patterns observed using
sensory data acquired over a long period of time.