Obstructive sleep apnea (OSA) affects over 936 million adults worldwide, leading to significant morbidity and reduced quality of life. Traditional diagnostic methods such as polysomnography (PSG), although effective, rely on hospital equipment and human resources and are not widely accessible. Emerging technologies such as the jaw tracking device developed by Sunrise have appeared, using gyroscopes and accelerometers to monitor jaw movements during sleep, showing high diagnostic accuracy compared to PSG. These devices use AI algorithms, providing a practical alternative for OSA diagnosis and monitoring. However, due to the high hardware cost of Sunrise and its rental-based business model, there are logistical challenges and limited monitoring capabilities. This prospective clinical study aims to offer the same capabilities through a novel ultrasonic transmitter for tracking jaw movements during sleep, which can be directly received by using a smartphone microphone, reducing the complexity of setup operations. This study will evaluate the sensitivity of the ultrasonic jaw tracking device in detecting apnea and compare it with PSG standards, developing a deep learning AI-driven algorithm to analyze data from jaw movements, breathing sounds, and apnea-related arousal events, as a basis for continuous home monitoring and evaluation of treatment effects for OSA patients.
Subjects aged between 20 and 75 years.
Potential sleep apnea cases: individuals referred by healthcare professionals due to suspected sleep apnea. Indicators may include excessive daytime sleepiness, noticeable loud snoring, witnessed apneas, or high-risk assessments on standard sleep apnea screening questionnaires.
Subjects assessed by healthcare professionals to require polysomnography (PSG) evaluation.
Subjects willing to sign the informed consent form and have been informed about the trial procedures. Participants must have the psychological capacity to provide informed consent and comply with study protocols.
Patients currently receiving treatment for sleep apnea (e.g., CPAP therapy or oral appliances) who cannot sleep without these devices or face potential risks without them.
Major respiratory risk conditions: including patients with chronic obstructive pulmonary disease (COPD), unstable asthma, or other significant respiratory conditions that may affect the accuracy of sleep study results should be excluded.
Patients with unstable cardiac conditions or recent hospitalization related to cardiac issues should be excluded from this clinical trial for the safety of conducting sleep assessments.
Patients taking medications that may interfere with sleep patterns or muscle tone (e.g., sedatives or muscle relaxants) should be excluded from the study.