睡眠质量
可穿戴计算机
透视图(图形)
手腕
心理学
应用心理学
物理医学与康复
质量(理念)
计算机科学
医学
人工智能
嵌入式系统
精神科
认知
哲学
认识论
放射科
作者
Benjamin D. Yetton,Daniel McDuff,Andrew Barakat,Allen Jiang,Nicholas B. Allen,Logan Schneider,Ari Winbush,Conor Heneghan
出处
期刊:IntechOpen eBooks
[IntechOpen]
日期:2024-10-14
标识
DOI:10.5772/intechopen.1006932
摘要
Researchers are interested in measuring both objective and subjective assessments of sleep, and associated phenomena such as sleepiness, quality and restoration. Predicting perceived sleep quality accurately from objective measurements remains an unsolved and interesting problem. Previous studies using polysomnograms and actigraphy have shown poor concordance between objective metrics and subjective sleep quality, but were often limited by study duration (e.g., one or two nights of PSG, study population in low 100 s). In this chapter, we consider whether consumer sleep trackers could significantly improve the assessment of subjective sleep quality through longer periods of assessment and larger data scale. We describe a recent study that modeled two subjective sleep quality metrics (PROMIS Sleep-Related Impairment (SI) and Sleep Disturbance (SD) Index) from objective sleep metrics acquired from a consumer wearable device (Fitbit). However, the goodness-of-fit parameter remains relatively low, even with the increased data availability and scale of data provided by consumer wearables. Specifically, for a well-characterized normative population of 2106 adults, we see that a linear multivariate model produces an R2 of 0.107 for predicting SI and R2 of 0.147 for SR, consistent with prior results using PSG and actigraphy. We conclude that subjective sleep quality remains broadly a psychological construct that cannot be fully modeled solely by objective sleep metrics.
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