在大学生群体中使用智能手机数据监测睡眠
Carsten Langholm1, Andrew Jin Soo Byun1,2, Janet Mullington3
1Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA.
Npj mental health research
|April 12, 2024
概括
智能手机传感器数据可以准确估计睡眠时间,为心理健康监测提供了可扩展的替代代代价高昂的可穿戴设备. 这种数字表型化方法有助于了解睡眠模式并改善医疗保健的可访问性.
科学领域:
- 数字健康数字健康
- 睡眠科学 睡眠科学
- 心理健康技术 心理健康技术
背景情况:
- 睡眠监测对整体健康,特别是心理健康至关重要.
- 目前的可穿戴睡眠追踪器面临着可访问性和可负担性挑战.
- 智能手机为广泛的睡眠监测提供了一个可扩展的解决方案.
研究的目的:
- 调查使用智能手机传感器数据来估计睡眠时间的可行性.
- 评估智能手机衍生的睡眠时间和自我报告的睡眠之间的相关性.
- 用智能手机数据和调查评估睡眠质量的预测模型.
主要方法:
- 对67名大学生28天的睡眠行为进行了分析.
- 使用mindLAMP智能手机应用程序进行调查和被动传感器数据收集.
- 使用被动电话传感器数据流来估计睡眠时间.
主要成果:
- 基于智能手机的睡眠时间估计与自我报告的睡眠时间有很强的相关性 (r=0.83).
- 一个预测模型准确地估计了匹兹堡睡眠质量指数 (PSQI) 的得分在1点以内.
- 智能手机衍生数据被证明是用于睡眠时间估计和数字表型的实用数据.
结论:
- 智能手机传感器数据为监测睡眠时间提供了一种可行且易于使用的方法.
- 这种方法可以大大促进心理健康评估的数字表型化.
- 这些发现支持使用消费者技术进行可扩展的健康监测.
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