探索睡眠感知的变化:聊天机器人睡眠日志和Fitbit睡眠数据的比较研究
Hyunchul Jang1, Siwoo Lee1, Yunhee Son1
1KM Data Division, Korea Institute of Oriental Medicine, Daejeon, Republic of Korea.
JMIR mHealth and uHealth
|November 21, 2023
概括
像Fitbits这样的可穿戴设备提供了有价值的睡眠数据,但个人的时间感知差异意味着主观的患者输入对于准确的睡眠管理至关重要. 这凸显了仅仅是客观措施的局限性.
科学领域:
- 数字健康数字健康
- 睡眠科学 睡眠科学
- 人与计算机的交互
背景情况:
- 来自可穿戴设备的患者生成的健康数据 (PGHD) 对疾病管理越来越重要.
- 像Fitbits这样的可穿戴设备可以跟踪睡眠指标 (例如,睡眠开始,偏移,总睡眠时间),但在睡眠评估的准确性和深度上有局限性.
- 主观的患者报告是必不可少的,不能被可穿戴设备数据完全取代.
研究的目的:
- 与可穿戴设备数据相比,分析睡眠中的个人时间感知特征.
- 了解用户如何感知和报告睡眠时间与客观测量.
- 为有效使用与时间相关的PGHD提供信息,特别是睡眠数据.
主要方法:
- 使用Fitbit设备在两周内收集睡眠数据.
- 通过聊天机器人对话从参与者那里收集每日睡眠记录.
- 统计比较Fitbit测量睡眠数据与聊天机器人交互的自我报告数据.
主要成果:
- 分析包括543名参与者 (年龄在30-59岁),数据超过7天.
- 参与者经常报告每小时或30分钟的睡眠时间,通常在Fitbit数据的60-90分钟内.
- 聊天机器人和Fitbit数据之间的平均差异约为15分钟;然而,个体变化很大,使得预测变得困难.
- 报告睡眠良好的参与者倾向于估计睡眠时间比Fitbit测量更长.
结论:
- 聊天机器人报告的睡眠时间和Fitbit测量显示平均相似性,但个人的感知有很大差异.
- 对睡眠质量良好的主观报告与感知睡眠持续时间更长相关.
- 睡眠时间感知的显著个体差异强调了仅依靠可穿戴设备进行客观睡眠评估的局限性.
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