Human Alertness Optimization with a Three-Process Dynamic Model

• Published in: Mathematics (Basel) Vol. 10; no. 11; p. 1916
• Main Authors: Yin, Jiawei, Julius, Agung, Wen, John T., Wang, Zhen, He, Chuanlin, Kou, Lei
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2022
• Subjects: Alertness; Alertness (Psychology); Algorithms; Biological activity; Body temperature; Calculus of variations; Circadian rhythm; Circadian rhythms; Computer simulation; Dynamic models; Fatigue; Food science; Gene expression; Homeostasis; Human subjects; Hybrid systems; Light; Optimization; Physiology; Schedules; Sleep; sleep regulation; Sleepiness; switched systems; Tuning; Zeitgeber; Iran
• ISSN: 2227-7390; 2227-7390
• DOI: 10.3390/math10111916

Circadian rhythm is an important biological process for humans as it modulates a wide range of physiological processes, including body temperature, sleep-wake cycle, and cognitive performance. As the most powerful external stimulus of circadian rhythm, light has been studied as a zeitgeber to regulate the circadian phase and sleep. This paper addresses the human alertness optimization problem, by optimizing light exposure and sleep schedules to relieve fatigue and cognitive impairment, in cases of night-shift workers and subjects with certain mission periods based on dynamics of the circadian rhythm system. A three-process hybrid dynamic model is used for simulating the circadian rhythm and predicting subjective alertness and sleepiness. Based on interindividual difference in sleep type and living habits, we propose a tunable sleep schedule in the alertness optimization problem, which allows the appropriate tuning of sleep and wake times based on sleep propensity. Variational calculus is applied to evaluate the impacts of light and sleep schedules on the alertness and a gradient descent algorithm is proposed to determine the optimal solutions to maximize the alertness level in various cases. Numerical simulation results demonstrate that the cognitive performance during certain periods can be significantly improved by optimizing the light input and tuning sleep/wake times compared to empirical data.