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Advisor(s)
Abstract(s)
Introduction:Sleep is vital for health as it has regenerative and protective functions. During sleep, there is a cyclicity of different phases that are analysed and classified for clinical purposes using polysomnography (PSG), a costly and technically demanding method. The tremendous growth of sleep medicine, where demand for studies far outstrips supply, opens a window for the development of accurate, low-threshold sleep monitoring solutions that can be self-administered at home and could help avoid these issues of convenience, accessibility and reproducibility.
Objective:This study aims to analyse the existing literature on the feasibility of wearable devices as an alternative to PSG for the classification of sleep stages.
Methods: The literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). All studies published in English or Portuguese with healthy adults who used wearables to record sleep were included. A meta-analysis was also performed to assess the mean values of the sleep metrics: total sleep time (TST), sleep latency (SL) and wake after sleep onset (WASO), all in minutes and time per stage (in minutes and as relative frequency of TST), as well as sleep efficiency (SE) (in %) and the corresponding statistics between the wearables used and the PSG.
Results: Given the high variability of wearables, the analysed metrics whose values were closest to the PSG came from different devices. Nevertheless, the meta-analysis revealed that most wearables tend to overestimate these variables
Conclusions:
The performance of wearables demonstrates remarkable accuracy in sleep staging, rivalling the gold standard PSG in some variables while providing a more convenient and unobtrusive alternative. This review enriches our global knowledge of sleep measurement and summarizes the limitations that need to be overcome, as informed decision making depends on understanding the different device options, validation contexts and cost implications.
Description
Keywords
Sleep PRISMA
Citation
Agostinho, M., Borges, M., Pereira, T., Borges, D.F., Soares, J.I. (2024, outubro). Wearable sleep staging technology as an alternative to polysomnography: a systematic review and meta-analysis. Livro de resumos do Congresso Nacional de Neurologia 2024, Cascais, Portugal.
Publisher
Sociedade Portuguesa de Neurologia