Obstructive Sleep Apnea
Conditions
Brief summary
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.
Interventions
DEVICEUltrasonic Jaw Tracking Device
This study investigates the effectiveness of the Ultrasonic Jaw Tracking Device, a novel non-invasive diagnostic tool designed to monitor dynamic jaw movements during sleep. The device is equipped with advanced ultrasonic sensors and proprietary algorithms to track jaw position and motion in real time. The intervention involves placing the device on the participant's mandible during polysomnography (PSG) sessions to simultaneously measure jaw movement data alongside standard PSG parameters. The primary goal is to evaluate the accuracy and efficacy of the device in detecting sleep-related conditions such as obstructive sleep apnea (OSA) compared to traditional PSG metrics.
Sponsors
Taipei Medical University WanFang Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
20 Years to 75 Years
Healthy volunteers
Yes
Inclusion criteria
1. Subjects aged between 20 and 75 years. 2. 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. 3. Subjects assessed by healthcare professionals to require polysomnography (PSG) evaluation. 4. 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. 5. Subjects agree that the principal investigator and their medical team may review their past medical records and extract sleep apnea-related medical history into the case report form during their participation in the trial, as per the condition or trial needs.
Exclusion criteria
1. 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. 2. 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. 3. 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. 4. Patients taking medications that may interfere with sleep patterns or muscle tone (e.g., sedatives or muscle relaxants) should be excluded from the study. 5. Patients with physical abnormalities or conditions that may interfere with the placement or function of the mandibular tracking device (e.g., noticeable facial hair, dental appliances, or severe dental problems) should be excluded. 6. Individuals with neurological conditions that may affect mandibular muscle control or present symptoms similar to sleep apnea (e.g., Parkinson's disease, severe post-stroke neurological damage). 7. Patients diagnosed with DSM-IV and DSM-V disorders and any other potential emotional issues or psychological history. 8. Other exclusions as determined by the principal investigator/sleep technician who deems the subject unsuitable for participation in the trial.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Baseline Demographic and Anthropometric Data | Assessment will be conducted prior to subject enrollment (baseline). | Collect baseline data of the subjects, including height (in meters), weight (in kilograms), age (in years), and gender; simultaneously calculate BMI (weight (kg)/height² (m²)). Data will be analyzed using descriptive statistics. |
| Apnea-Hypopnea Index (AHI) measured by Polysomnography (PSG) | Measured during the overnight sleep study session at baseline. | Record the average number of events per hour of sleep during which there is complete cessation of airflow (apnea) and partial reduction of airflow (hypopnea) using PSG. Data will be presented as the mean (events/hour) with standard deviation. |
| Respiratory Disturbance Index (RDI) measured by Polysomnography (PSG) | Measured during the overnight sleep study session at baseline. | Record all respiratory disturbance events, including apnea, hypopnea, and other abnormal breathing patterns using PSG. Data will be presented as the mean (events/hour) with standard deviation. |
| ECG-Derived Heart Rate Variability (HRV) Parameters | Measured during the overnight sleep study session at baseline. | ECG recordings will be performed concurrently, and heart rate variability indices will be calculated. Data will be presented as the mean with standard deviation. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Device Attachment Discomfort | Assessed from the moment of device attachment until 10 minutes post-attachment. | Record the discomfort experienced by subjects during the attachment of the ultrasonic mandibular movement recording device. |
| Trial Withdrawal Rate | Assessed from the date of enrollment until trial completion, over an estimated period of up to 41 weeks (i.e., from 2024/09/19 to 2025/06/30). | Calculate the proportion of subjects who withdraw from the trial from the date of enrollment until trial completion (or until withdrawal occurs, whichever comes first). |
Countries
Taiwan
Contacts
Primary ContactJowy Tani, MD, PhD
Outcome results
None listed