Abstract
In this paper, an adaptive temporal-causal network model is presented for a normal night’s sleep and for how disturbances and their timing interfere with such a normal night of sleep. The goal of this computational model is to explore the area of how sleep disturbances influence a person’s health. This was achieved by simulating single and multiple sleep disturbances during sleep episodes and measuring the effect on light, deep, and REM sleep. The main finding from the simulated scenarios in this study is that disturbances, depending on their timing, can cause a lack of deep and/or REM sleep. This implies that sleep disturbances might lead to insufficient physical and/or emotional recovery.
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Hee, Q.L., Hogendorp, L., Warnaars, D., Treur, J. (2023). The Effect of Sleep Disturbances on the Quality of Sleep: An Adaptive Computational Network Model. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the Second International Conference on Innovations in Computing Research (ICR’23). Lecture Notes in Networks and Systems, vol 721. Springer, Cham. https://doi.org/10.1007/978-3-031-35308-6_9
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