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Objectives: Rapid Eye Movement Sleep Behaviour Disorder (RBD) is regarded as a prodrome of neurodegeneration, with a high conversion rate to α–synucleinopathies such as Parkinson’s Disease (PD). The clinical diagnosis of RBD co–exists with evidence of REM Sleep Without Atonia (RSWA), a parasomnia that features loss of physiological muscular atonia during REM sleep. The objectives of this study are to implement an automatic detection of RSWA from polysomnographic traces, and to propose a continuous index (the Dissociation Index) to assess the level of dissociation between REM sleep stage and atonia. This is performed using Euclidean distance in proper vector spaces. Each subject is assigned a dissociation degree based on their distance from a reference, encompassing healthy subjects and clinically diagnosed RBD patients at the two extremes. Methods: Machine Learning models were employed to perform automatic identification of patients with RSWA through clinical polysomnographic scores, together with variables derived from electromyography. Proper distance metrics are proposed and tested to achieve a dissociation measure. Results: The method proved efficient in classifying RSWA vs. not-RSWA subjects, achieving an overall accuracy, sensitivity and precision of 87%, 93% and 87.5%, respectively. On its part, the Dissociation Index proved to be promising in measuring the impairment level of patients. Conclusions: The proposed method moves a step forward in the direction of automatically identifying REM sleep disorders and evaluating the impairment degree. We believe that this index may be correlated with the patients’ neurodegeneration process; this assumption will undergo a robust clinical validation process involving healthy, RSWA, RBD and PD subjects.

Environmental temperature can strongly affect sleep. The habitual sleep phase is usually located between evening decline and morning rise of the circadian rhythm of core body temperature (CBT). However, the thermophysiological mechanisms promoting or disturbing sleep are not yet fully understood. The purpose of this study was to examine the effects of a high heat capacity mattress (HHCM) on CBT, skin temperatures and sleep in comparison to a conventional low heat capacity mattress (LHCM). Based on the higher heat capacity of HHCM an increase in conductive body heat loss enhances the nocturnal decline in CBT can be expected. Based on previous findings this may then be accompanied by an increase in slow wave sleep (SWS). The mattresses were studied in a randomized single-blind crossover design in fifteen healthy young men (Age: 26.9±2.1yr, BMI: 22.2±0.4kg/m2) by overnight in laboratory standard video-polysomnography in a temperature stabilized setting. CBT, room temperature, and skin and mattress surface temperatures were continuously recorded in order to get information about inner and outer body heat flow. Additionally, subjective sleep quality was estimated by visual analogue scale. In comparison to LHCM sleep on HHCM exhibited a selective increase in SWS (16%, p