ArticleMedical science monitor : international medical journal of experimental and clinical research2025
Comparative Accuracy of Millimeter-Wave Radar and Polysomnography in Sleep Apnea Detection.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a common and serious sleep disorder characterized by recurrent episodes of partial or complete airway obstruction during sleep. Polysomnography is considered the gold standard for diagnosing OSAHS and evaluating its severity. However, traditional sensory monitoring methods, while effective, are often cumbersome, expensive, and unsuitable for home use. The present study introduces a non-sensory millimeter-wave radar sleep monitor, which provides a contactless, portable, and cost-effective alternative for assessing sleep apnea. The goal was to evaluate the consistency of results from the radar-based system with those from polysomnography, in monitoring sleep apnea. MATERIAL AND METHODS Sixty-eight subjects who met the inclusion criteria were recruited from our center. Each subject underwent simultaneous sleep monitoring with both polysomnography and the radar system. The collected data were analyzed using the chi-square test, Kappa coefficient, and sensitivity and specificity calculations. A significance level of P<0.05 was used for all statistical tests. RESULTS The radar-based sleep monitor demonstrated a sensitivity of 92.7%, specificity of 84.6%, and a Kappa coefficient of 0.731 (P<0.01). For moderate-to-severe OSAHS cases, the Kappa value increased to 0.831 (P<0.01), indicating high consistency with polysomnography. CONCLUSIONS The novel sensorless millimeter-wave radar sleep apnea monitoring technology offers several advantages, including non-invasiveness, ease of use, and comfort. It provides a reliable and convenient alternative for OSAHS diagnosis, particularly in resource-limited settings, and can complement traditional sleep studies.
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