ArticleBioengineering (Basel, Switzerland)2025
Event-Level Identification of Sleep Apnea Using FMCW Radar.
Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
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Who cites it
3 citing papers in PubMed.
- Non-contact on-device detection of obstructive sleep apnea from infrared video.Nature communications · 2026Article
- Cross-Modality Transfer Learning from PSG to FMCW Radar for Event-Level Apnea-Hypopnea Segmentation.Bioengineering (Basel, Switzerland) · 2026Article
- Spatiotemporal Feature Learning for Daily-Life Cough Detection Using FMCW Radar.Bioengineering (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Sleep apnea, characterized by its high prevalence and serious health consequences, faces a critical bottleneck in diagnosis. Polysomnography (PSG), the gold standard, is costly and cumbersome, while wearable devices struggle with quality control and patient compliance, rendering them as unsuitable for both large-scale screening and continuous monitoring. To address these challenges, this research introduces a contactless, low-cost, and accurate event-level sleep apnea detection method leveraging frequency-modulated continuous-wave (FMCW) radar technology. The core of our approach is a novel deep-learning model, built upon the U-Net architecture and augmented with self-attention mechanisms and squeeze-and-excitation (SE) modules, meticulously designed for the precise event-level segmentation of sleep apnea from FMCW radar signals. Crucially, we integrate blood oxygen saturation (SpO
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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.