Wearable Sensor Design for Real-Time Obstructive Sleep Apnea Monitoring

Repeated breath cessation during sleep due to the closure of the airway passage is a condition known as obstructive sleep apnea (OSA). Untreated OSA elevates occupational-related fatal incidents, motor vehicle accidents, severe depression, cardiac and cerebrovascular ailments, and reduced survival expectancy. The gold standard for diagnosing OSA is polysomnography (PSG), which is an overnight sleep study. PSG is associated with higher costs and relative discomfort for the subject. In this work, a dedicated device is designed and developed to screen the individual for probable OSA. The proposed device incorporates a pressure sensor and an Arduino Nano 33 BLE Sense controller to capture the respiratory pressure signals the subject generates. An algorithm is developed to calculate essential breath metrics that include parameters such as the respiration rate (RR), the inspiratory time ( $I_{t}$ ), the expiratory time ( $E_{t}$ ), and the apnea-hypopnea index (AHI). These metrics serve as indicators to grade and assess the likelihood of OSA in the subject. In addition, the proposed system also monitors the sleeping position of the subject, temperature, and humidity as supplementary parameters to evaluate their sleep patterns comprehensively during the study. The proposed methodology offers a direct and efficient means of measuring respiratory signals for OSA assessment, thereby eliminating the need for extensive overnight sleep studies and complex multiparameter analyses. The proposed method also allows individuals to sleep naturally without the requirement for physical restraints during monitoring, as in traditional method. This approach holds promise for more convenient and accessible OSA screening while simultaneously enabling parallel monitoring through the CPAP mask.