Obstructive Sleep Apnea (OSA) is traditionally diagnosed via Polysomnography (PSG), which relies on multiple wired sensors in an unfamiliar hospital setting. In this study, a compact home-sleep-test system is proposed, integrating a fringing-field capacitive sensor for wireless respiratory-effort monitoring system(Formula: see text, and a nasal airflow sensing system (2 cm×2 cm) with an connected 2 cm × 1 cm temperature sensor (both wired to the processing unit). A customized signal-processing algorithm was developed to denoise both channels and automatically identify apnea and hypopnea events. Validation with subjects (n = 31) demonstrated performance metrics (SN = 0.846, SP = 0.944, Precision = 0.917, and Accuracy = 0.903, Formula: see text ) in classifying OSA severity. By combining novel capacitive fringing-field sensing and temperature-based airflow measurement into a largely wireless wearable, a practical and accurate alternative to traditional PSG for at-home OSA detection is offered.
Kim et al. (2025) studied this question.