Applied Mathematics

Volume 9, Issue 12 (December 2018)

ISSN Print: 2152-7385   ISSN Online: 2152-7393

Google-based Impact Factor: 0.58  Citations  

The Compound Spectral Indices of Human Stress

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DOI: 10.4236/am.2018.912090    568 Downloads   1,011 Views  Citations


Temporally fine-grained and objective measures of mental states or their surrogate states are desperately needed in clinical psychiatry. Stress, both acute and especially chronic stress, is an important mental and physiological state observed in many mental disorders. It is a potential precipitant of acute psychiatric decompensations, be they anxious, affective, psychotic, or behavioural. Thus, being able to objectively follow stress or its surrogate parameters over time in a clinician-friendly way would help predict and prevent decompensations and monitor subsequent treatment success. Thus, we introduce the Compound Spectral Stress Indices (CSSI) that are derived from sensing data of various physiological and physiological and behavioural parameters we use as surrogate stress measures. To obtain the CSSI we use a hierarchical approach provided by adaptability, congruency and derived stress coefficient matrices. Adaptability is defined as a macroscopic characterisation of physiological and physiological and behavioural performance constructed as a product of the total variation of time-segmented complexity indices multiplied by the frequency of the time-varying distribution of complexity indices of the measured physiological or physiological and behavioural parameters, where complexity is expressed in terms of the Hurst exponent. Congruency is expressed by a constant characterising a demand-resource balance and it is then expressed in the form of a stress coefficient matrix. The CSSI is given by the spectral distance of the stress coefficient matrices from the ideal demand-resource matrix.

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Kloucek, P. and Gunten, A. (2018) The Compound Spectral Indices of Human Stress. Applied Mathematics, 9, 1378-1394. doi: 10.4236/am.2018.912090.

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