ReviewSleep & breathing = Schlaf & Atmung2025
Tracing the evolution in sleep apnea detection: a review from traditional non-contact under-the-mattress devices to advanced AI-driven methods.
Review in Sleep & breathing = Schlaf & Atmung, 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Corrections and comments
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Authors and funding
3 authors.
Funding
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Abstract
backgroundSleep apnea is traditionally diagnosed with polysomnography (PSG), which, while effective, is costly, time-consuming, and obtrusive. Recent advancements in biosensing technologies have facilitated the development of under-the-mattress devices as potential alternatives for detecting sleep apnea.
methodsWe reviewed the literature across PubMed, Embase, Web of Science, and Scopus, focusing on studies that assessed mattress-like or under-the-mattress biosensing devices for sleep apnea. 15 studies were included as illustrative examples of recent progress.
resultsOur review assessed studies on innovative sensor technologies for sleep apnea detection. These studies demonstrated the efficacy of various sensors-such as Load Cells, Emfit, and PVDF-along with advanced radar and machine learning methods, in accurately identifying sleep apnea events. Results indicated that most studies reported good overall performance of mattress-based systems compared to traditional polysomnography, though variability across devices was observed.
conclusionUnder-the-mattress biosensing devices appear to be promising as cost-effective, user-friendly, and unobtrusive alternatives to PSG for sleep apnea detection. Their high-performance metrics suggest that these devices are viable options for both clinical settings and home use.
Indexed as
Identifiers
41139169What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.