โก Quick Summary
This review article explores the evolution of sleep apnea detection, highlighting the transition from traditional polysomnography (PSG) to innovative under-the-mattress biosensing devices. These advancements suggest that such devices could serve as cost-effective and user-friendly alternatives for detecting sleep apnea.
๐ Key Details
- ๐ Studies Reviewed: 15 studies on under-the-mattress biosensing devices
- ๐งฉ Technologies Assessed: Load Cells, Emfit, PVDF, advanced radar, and machine learning
- โ๏ธ Traditional Method: Polysomnography (PSG)
- ๐ Performance Metrics: Good overall performance compared to PSG, with variability across devices
๐ Key Takeaways
- ๐ก Innovative Sensors: Various sensor technologies have shown promise in accurately detecting sleep apnea events.
- ๐ฅ User-Friendly: Under-the-mattress devices are less obtrusive and easier to use than traditional methods.
- ๐ Cost-Effective: These devices may offer a more affordable solution for sleep apnea detection.
- ๐ค AI Integration: Advanced machine learning methods enhance the accuracy of sleep apnea detection.
- ๐ Clinical and Home Use: These devices are suitable for both clinical settings and home monitoring.
- ๐ Research Scope: The review included literature from PubMed, Embase, Web of Science, and Scopus.
- ๐ Publication: The study was published in the journal Sleep Breath in 2025.
๐ Background
Sleep apnea is a serious condition that can lead to various health complications if left undiagnosed. Traditionally, it has been diagnosed using polysomnography (PSG), a method that, while effective, is often costly, time-consuming, and obtrusive. The need for more accessible and less invasive detection methods has spurred research into alternative technologies.
๐๏ธ Study
The review conducted by Daneshvar et al. aimed to assess the efficacy of under-the-mattress biosensing devices as alternatives to traditional PSG. By analyzing 15 studies, the authors highlighted the advancements in sensor technologies and their potential to transform sleep apnea detection.
๐ Results
The findings indicated that most studies reported good overall performance of mattress-based systems when compared to traditional PSG. However, there was some variability across devices, suggesting that while promising, further refinement and standardization may be necessary.
๐ Impact and Implications
The implications of this research are significant. The development of under-the-mattress biosensing devices could lead to a paradigm shift in how sleep apnea is diagnosed and monitored. By providing a less intrusive and more accessible option, these devices could improve patient compliance and outcomes, making sleep apnea detection more widely available.
๐ฎ Conclusion
This review underscores the potential of innovative biosensing technologies in the realm of sleep apnea detection. As these devices continue to evolve, they may offer a viable alternative to traditional methods, paving the way for enhanced patient care and monitoring. Continued research and development in this area are essential to fully realize their capabilities.
๐ฌ Your comments
What are your thoughts on the shift towards under-the-mattress biosensing devices for sleep apnea detection? We would love to hear your insights! ๐ฌ Leave your comments below or connect with us on social media:
Tracing the evolution in sleep apnea detection: a review from traditional non-contact under-the-mattress devices to advanced AI-driven methods.
Abstract
BACKGROUND: Sleep 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.
METHODS: We 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.
RESULTS: Our 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.
CONCLUSION: Under-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.
Author: [‘Daneshvar S’, ‘Rahimi M’, ‘Ansarin K’]
Journal: Sleep Breath
Citation: Daneshvar S, et al. Tracing the evolution in sleep apnea detection: a review from traditional non-contact under-the-mattress devices to advanced AI-driven methods. Tracing the evolution in sleep apnea detection: a review from traditional non-contact under-the-mattress devices to advanced AI-driven methods. 2025; 29:332. doi: 10.1007/s11325-025-03500-2