睡眠(系统调用)
活动追踪器
回忆偏差
活动记录
队列
模式
生活质量(医疗保健)
BitTorrent跟踪器
物理疗法
医学
物理医学与康复
心理学
计算机科学
精神科
体力活动
人工智能
眼动
失眠症
内科学
社会科学
护理部
病理
社会学
操作系统
作者
Luan Chen,Xujun Ma,Meenakshi Chatterjee,Juha Kortelainen,Teemu Ahmaniemi,Walter Maetzler,Pei Wang,Daqing Zhang
标识
DOI:10.1109/embc48229.2022.9870923
摘要
For the patient community with neurodegenerative disorders (NDD) and immune-mediated inflammatory diseases (IMID), fatigue and sleep disturbances stand out as two of the most common and disabling symptoms, which mightily impair patient's quality of life. Traditional questionnaire-oriented approaches to reflect such symptoms suffer from recall bias and poor sensitivity to change. By virtue of multiple sensing modalities at home, IDEA-FAST project aims to identify novel digital endpoints of fatigue and sleep disturbances, that are objective, reliable and sensitive to change. This article presents and discusses results from a pilot study of IDEA-FAST to evaluate the feasibility of capturing sleep and fatigue measures from three sleep trackers. Data collected from 143 participants (age range: 21–82) across 6 disease groups and healthy cohort for a period of 9 months, were investigated using our proposed sensor analytical pipeline. The overall performance reveals that the median coverage rate of sleep trackers ranged from 48.3% to 76.9%. Furthermore, the digital measures obtained from each device, indicated a higher association with sleep related patient reported outcomes (PROs) than fatigue related ones, when taking all participants into account.
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