失眠症
睡眠(系统调用)
医学
睡眠障碍
重症监护医学
精神科
计算机科学
操作系统
作者
Hannah Scott,Bastien Lechat,Jack Manners,Nicole Lovato,Andrew Vakulin,Peter Catcheside,Danny J. Eckert,Amy C. Reynolds
标识
DOI:10.1016/j.sleep.2022.10.030
摘要
Self-reported sleep difficulties are the primary concern associated with diagnosis and treatment of chronic insomnia. This said, in-home sleep monitoring technology in combination with self-reported sleep outcomes may usefully assist with the management of insomnia. The rapid acceleration in consumer sleep technology capabilities together with their growing use by consumers means that the implementation of clinically useful techniques to more precisely diagnose and better treat insomnia are now possible. This review describes emerging techniques which may facilitate better identification and management of insomnia through objective sleep monitoring. Diagnostic techniques covered include insomnia phenotyping, better detection of comorbid sleep disorders, and identification of patients potentially at greatest risk of adverse outcomes. Treatment techniques reviewed include the administration of therapies (e.g., Intensive Sleep Retraining, digital treatment programs), methods to assess and improve treatment adherence, and sleep feedback to address concerns about sleep and sleep loss. Gaps in sleep device capabilities are also discussed, such as the practical assessment of circadian rhythms. Proof-of-concept studies remain needed to test these sleep monitoring-supported techniques in insomnia patient populations, with the goal to progress towards more precise diagnoses and efficacious treatments for individuals with insomnia.
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