Personalized treatment and smart telerehabilitation for obstructive sleep apnea
Developing a Precision Health Approach for Obstructive Sleep Apnea: Treatment Responses Analysis and Smart Telerehabilitation Systems
This project will test whether an AI tool can pick the best treatment for people with obstructive sleep apnea and whether a smartphone app helps them stick to throat exercises.
Quick facts
| Phase | Not applicable |
|---|---|
| Study type | Interventional |
| Enrollment | 300 (estimated) |
| Ages | 20 Years and up |
| Sex | All |
| Sponsor | National Cheng-Kung University Hospital Academic / other |
| Locations | 1 site (Tainan) |
| Trial ID | NCT07254026 on ClinicalTrials.gov |
What this trial studies
The research combines retrospective machine learning on polysomnography records with a prospective clinical phase to improve treatment selection and adherence in obstructive sleep apnea (OSA). In Phase I, investigators will apply machine learning to a large PSG dataset from National Cheng Kung University Hospital to find features that predict response to CPAP, surgery, or oropharyngeal rehabilitation (OPR). In Phase II, newly diagnosed patients will be allocated to CPAP, surgery, or OPR (with either an exercise diary or a smartphone application) guided by the AI recommendation alongside physician judgment and patient preference, with each intervention lasting 12 weeks. Outcomes include treatment efficacy on repeat PSG and clinical measures, plus adherence to OPR when delivered by app versus diary.
Who should consider this trial
Good fit: Adults aged 20 or older newly diagnosed with mild-to-severe pure obstructive sleep apnea on polysomnography who meet eligibility criteria (for example BMI ≤31 and no major cardiopulmonary, neurologic, musculoskeletal, or other non-respiratory sleep disorders).
Not a fit: People with BMI >31, significant nasal/sinus disease, pregnancy, recent substance abuse, severe lung or high‑risk cardiac disease, neurologic or musculoskeletal conditions that prevent exercise, other non‑respiratory sleep disorders, or those unable/unwilling to attend the hospital or use a smartphone app may not benefit from or be eligible for this approach.
Why it matters
Potential benefit: If successful, this approach could help match each patient to the treatment most likely to work and increase exercise adherence via a mobile app, improving symptoms and sleep health.
How similar studies have performed: Prior work shows modest benefits from oropharyngeal exercises and some mHealth tools can improve adherence, but using AI to personalize treatment choice for OSA is relatively novel and not yet well established.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * 20 years old and above * Newly diagnosed with mild to severe pure obstructive sleep apnea based on polysomnography Exclusion Criteria: * Severe allergic rhinitis * Sinusitis with nasal polyps * Body Mass Index (BMI) \> 31 * Alcohol or drug abuse within the past year * Pregnancy * Severe obstructive or restrictive pulmonary diseases * High-risk cardiovascular diseases during exercise (e.g., angina, myocardial infarction, heart failure, valvular heart disease) * History of central or peripheral neurological disorders that interfere with exercise prescription * Musculoskeletal or psychological disorders that interfere with exercise prescription * Other non-respiratory sleep disorders * Sleep disorders with concomitant central sleep apnea
Where this trial is running
Tainan
- National Cheng Kung University Hospital — Tainan, Taiwan (Recruiting)
Study contacts
- Principal investigator: Ching-Hsia Hung, PhD — National Cheng Kung University
- Study coordinator: Jun-Hui Ong, MS
- Email: junhui.ong611@gmail.com
- Phone: +886-9-37839992
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.