ArticleBMJ open2025
Roles and features of smart control and sensing applications for sleep quality improvement: a scoping review.
Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
objectivesThis scoping review synthesises evidence on the measures and characteristics of the components of combined smart control and sensing technologies, and their impact on sleep quality.
designScoping review following Joanna Briggs Institute (JBI) methodology and reports using the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews (PRISMA-ScR). DATA SOURCES: A comprehensive literature search was conducted in PubMed, Web of Science, EMBASE, Ovid, China National Knowledge Infrastructure, Wanfang Data and VIP Information from the inception of the databases to November 2024 following the PRISMA-ScR statement and updated in June 2025. ELIGIBILITY CRITERIA: This review included peer-reviewed studies evaluating smart home products integrating smart control and sensing technologies to improve sleep quality, with outcomes focused on sleep duration, efficiency or satisfaction. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers screened the title, abstracts and full texts of the selected studies based on the inclusion criteria. Data extraction was performed by two independent reviewers. The data were summarised in tabular format and a narrative summary.
resultsAll original studies (N=13) investigated the role and features of these technologies. Seven types of sensors and five smart control methods were identified. These were: biosignal, environmental, chemical sensors, contact and motion sensors, imaging and vision sensors, integrated smart sensors and specialised sensors, along with audio-based, pressure-based, temperature-based, vibration-based and physician-guided control methods. These technologies improved sleep-related health metrics including total sleep time, sleep onset latency, sleep efficiency, deep sleep percentage and subjective sleep quality.
conclusionThe findings highlight the potential of these technologies for improving sleep, emphasising the role and usability. Future research and product development can build on these insights to design sleep improvement products to innovative, personalised smart home solutions for better sleep. ETHICS AND DISSEMINATION: As a review, ethical approval is not required. The results from this study will be presented at international conferences and disseminated through peer-reviewed publications. Patients and the public will be involved in the dissemination plans. REGISTRATION DETAILS: The Open Science Framework (https://doi.org/10.17605/OSF.IO/FC236).
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