摘要：SummaryShift workers and many other groups experience irregular sleep-wake patterns. This can induce excessive daytime sleepiness that decreases productivity and elevates the risk of accidents. However, the degree of daytime sleepiness is not correlated with standard sleep parameters like total sleep time, suggesting other factors are involved. Here, we analyze real-world sleep-wake patterns of shift workers measured with wearables by developing a computational package that simulates homeostatic sleep pressure – physiological need for sleep – and the circadian rhythm. This reveals that shift workers who align sleep-wake patterns with their circadian rhythm have lower daytime sleepiness, even if they sleep less. The alignment, quantified by the sleep parameter, circadian sleep sufficiency, can be increased by dynamically adjusting daily sleep durations according to varying bedtimes. Our computational package provides flexible and personalized real-time sleep-wake patterns for individuals to reduce their daytime sleepiness and could be used with wearables to develop smart alarms.Graphical abstractDisplay OmittedHighlights•Sleep-wake patterns measured by wearables are analyzed with a mathematical model•A new sleep parameter CSS measures the circadian alignment of sleep-wake patterns•Sleep-wake patterns more aligned with circadian rhythm decrease daytime sleepiness•Our computational package calculates the CSS to provide personalized sleep schedulesBiological sciences; Neuroscience; Behavioral neuroscience; Mathematical biosciences; Systems biology.
