Radar-Based Detection of Obstructive Sleep Apnea: A Systematic Review and Network Meta-Analysis of Diagnostic Accuracy Across Frequency Bands

Background: Obstructive sleep apnea (OSA) is one of the most prevalent yet underdiagnosed sleep disorders. We evaluated the diagnostic accuracy of radar-based systems and ranked frequency bands for the non-contact detection of OSA. Methods: A systematic search of six databases was conducted from inception to May 23, 2025. Eligible studies included adults assessed for OSA using radar-based systems compared to polysomnography. Hierarchical SROC modeling, threshold-based meta-analyses, and frequency band-stratified network meta-analysis were performed. Certainty of evidence was assessed using GRADE. The PROSPERO registration number is CRD420251059236. Results: We identified 23,906 records and included 20 studies involving 1540 participants. The primary outcome included a high area under the curve (AUC) of approximately 0.91, an optimal apnea–hypopnea index (AHI) cutoff of ≥22 with a sensitivity of 0.8155 (95% confidence interval (CI): 0.6862–0.8993) and specificity of 0.8819 (95% CI: 0.7799–0.9402). At an AHI threshold of 30, X-band dual radar performed the best, followed by K-band, which yielded significant but more variable results. C-bands consistently showed lower diagnostic values. Conclusions: This study provides a novel radar band comparison for OSA detection, highlighting clinically relevant thresholds. Key limitations are indirect comparisons and limited, varied samples. Radar-based systems show high sensitivity for OSA detection, optimized by frequency, radar type, artificial intelligence support, and dual sensors within 0.2–1.5 m. Future work should expand the frequency analysis, standardize AHI thresholds, and validate results in specific subgroups.