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This study makes use of control system model identification techniques to examine the relationship between thermoregulation and sleep regulation. Specifically, data-based mechanistic (DBM) modelling is used to formulate and experimentally test the hypothesis, put forth by Gilbert et al., that there exists a connection between distal heat loss and sleepiness. Six healthy sleepers each spent three nights and the following day in the sleep laboratory: an adaptation, a cognitive arousal and a neutral testing day. In the cognitive arousal condition, a visit of a television camera crew took place and subjects were asked to be interviewed. During each of the three 25-min driving simulator tasks per day, the distal-to-proximal gradient and the electroencephalogram are recorded. It is observed from these experimental data that there exists a feedback connection between thermoregulation and sleep. In addition to providing experimental evidence in support of the Gilbert et al. (2004) hypothesis, the authors propose that the nature of the feedback connection is determined by the nature of sleep/wake state (i.e. NREM sleep versus unwanted sleepiness in active subjects). Besides this, an individualized and time-variant model for the linkage between thermoregulation and sleep onset is presented. This compact model feeds on real-time data regarding distal heat loss and sleepiness and contains a physically meaningful parameter that delivers an individual- and time-depending quantification of a well known biological features in the field of thermoregulation: the thermoregulatory error signal T(hypo)(t)-T(set)(t). A validation of these physical/biological features emphasizes the reliability and power of DBM in describing individual differences related to the sleep process.

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