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Shi, Y., Nguyen, M.H., Blitz, P., French, B., Fisk, S., De La Torre, O, Smailagic, A., Siewiorek, D.P., Al Absi, M., Ertin, E., Kamarck, T. and Kumar, S. (2010) Personalized Stress Detection from Physiological Measurements. International Symposium on Quality of Life Technology Proceedings, Las Vegas, 28-29 June 2010, 71-75.

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• 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.