The geometric approach to human stress based on stress-related surrogate measures.

We present a predictive Geometric Stress Index (pGSI) and its relation to behavioural Entropy ([Formula: see text]). [Formula: see text] is a measure of the complexity of an organism's reactivity to stressors yielding patterns based on different behavioural and physiological variables selected as Surrogate Markers of Stress (SMS). We present a relationship between pGSI and [Formula: see text] in terms of a power law model. This nonlinear relationship describes congruences in complexity derived from analyses of observable and measurable SMS based patterns interpreted as stress. The adjective geometric refers to subdivision(s) of the domain derived from two SMS (heart rate variability and steps frequency) with respect to a positive/negative binary perceptron based on a third SMS (blood oxygenation). The presented power law allows for both quantitative and qualitative evaluations of the consequences of stress measured by pGSI. In particular, we show that elevated stress levels in terms of pGSI leads to a decrease of the [Formula: see text] of the blood oxygenation, measured by peripheral blood oxygenation SpO2 as a model of SMS.

[Psychiatry]. / Psychiatrie.

The Covid-19 pandemic has a major impact on psychiatry by its social consequences and possible direct effect of certain forms of Covid-19 on mental health. During this crisis, the accessibility of technology meets a state of necessity, which has propelled telepsychiatry from the shadows into the light. The contribution of several technologies (i.e. virtual reality, actigraphy, computational psychiatry) combining clinical data and neuroscience underlines the great neurobehavioural variability even within the same diagnostic category, calling for greater precision in therapeutic offers as suggested e.g. by developments in neurofeedback. The place of intranasal esketamin in the panoply of antidepressent drug treatments for resistant depression has not yet been defined.

La pandémie de Covid-19 bouleverse la psychiatrie par ses conséquences sociales et par de possibles séquelles psychiatriques. La crise actuelle révèle l'accessibilité de technologies digitales telles que la télépsychiatrie. Des technologies comme la réalité virtuelle, l'actigraphie, la psychiatrie computationnelle combinées aux données cliniques et aux neurosciences révèlent une importante variabilité neurocomportementale même au sein d'une catégorie diagnostique donnée, invitant à une plus grande précision des traitements comme suggéré par les recherches en neurofeedback. La place de l'eskétamine intranasale dans la panoplie thérapeutique médicamenteuse de la dépression résistante doit encore être définie.

Modelling Training Adaptation in Swimming Using Artificial Neural Network Geometric Optimisation.

This study aims to model training adaptation using Artificial Neural Network (ANN) geometric optimisation. Over 26 weeks, 38 swimmers recorded their training and recovery data on a web platform. Based on these data, ANN geometric optimisation was used to model and graphically separate adaptation from maladaptation (to training). Geometric Activity Performance Index (GAPI), defined as the ratio of the adaptation to the maladaptation area, was introduced. The techniques of jittering and ensemble modelling were used to reduce overfitting of the model. Correlation (Spearman rank) and independence (Blomqvist ß) tests were run between GAPI and performance measures to check the relevance of the collected parameters. Thirteen out of 38 swimmers met the prerequisites for the analysis and were included in the modelling. The GAPI based on external load (distance) and internal load (session-Rating of Perceived Exertion) showed the strongest correlation with performance measures. ANN geometric optimisation seems to be a promising technique to model training adaptation and GAPI could be an interesting numerical surrogate to track during a season.