自主监督加速仪数据的学习为睡眠及其与死亡率的关联提供了新的见解
Hang Yuan1,2, Tatiana Plekhanova3, Rosemary Walmsley1,2
1Nuffield Department of Population Health, University of Oxford, UK.
medRxiv : the preprint server for health sciences
|July 18, 2023
概括
睡眠时间短 (<6小时) 会增加死亡风险,即使睡眠效率良好. 腕式加速度计为睡眠分类和人口健康研究提供了可行的方法.
科学领域:
- 睡眠科学 睡眠科学
- 生物医学工程 生物医学工程
- 公共卫生 公共卫生
背景情况:
- 准确的睡眠阶段分类对于诊断睡眠障碍和监测幸福感至关重要.
- 现有的非多梦法方法通常依赖于小队列和启发式方法.
- 这项研究旨在验证用于睡眠分类的手腕加速度计,并评估它们与死亡率的关联.
结论:
- 当用深度学习分析时,手腕穿戴的加速度计为睡眠分类提供了可靠的方法.
- 短暂的睡眠时间是死亡的一个独立风险因素,强调了充足的睡眠的重要性.
- 这种方法使得大规模的人群研究睡眠和健康结果成为可能.
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