Shift 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.

轮班工人和许多其他群体会经历不规律的睡眠-觉醒模式。这会导致白天过度嗜睡，从而降低生产力并增加发生事故的风险。然而，白天嗜睡的程度与总睡眠时间等标准睡眠参数无关，这表明还涉及其他因素。在这里，我们通过开发一个模拟稳态睡眠压力（睡眠的生理需求）和昼夜节律的计算包来分析使用可穿戴设备测量的轮班工人的真实睡眠-觉醒模式。这表明，使睡眠-觉醒模式与昼夜节律保持一致的轮班工人白天的困倦程度较低，即使他们睡得更少。对齐，由睡眠参数量化，昼夜节律睡眠充足，可以通过根据不同的就寝时间动态调整每日睡眠时间来增加。我们的计算包为个人提供灵活和个性化的实时睡眠-觉醒模式，以减少他们白天的困倦，并可与可穿戴设备一起使用以开发智能警报。