Smartwatch-Based AI Model for OSA Prediction (SWOSA)

NCT06792188 | Recruiting

• 1 other identifier: 24111291590
• Study Type: observational
• Target: 147
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to develop an artificial intelligence (AI) model for more accurately diagnosing obstructive sleep apnea (OSA) by collecting blood oxygen saturation and other health information during sleep using a smartwatch. OSA is common but often underdiagnosed, and the gold-standard diagnostic test, polysomnography, is costly and time-consuming. Smartwatches can provide a variety of health data, such as sleep patterns, blood oxygen saturation, and heart rate, which can help detect key symptoms and signs of OSA. By developing an AI model that uses smartwatch data to screen for OSA, this study seeks to offer a cost-effective and accessible diagnostic method, ultimately contributing to the early detection and improved treatment rates of OSA.

Conditions

Obstructive Sleep Apnea of Adult; Screening; Smart Watch

Outcome Measures

Primary Outcomes (1)

• Predictive Accuracy of the AI Model for Moderate-to-Severe Obstructive Sleep Apnea

  Evaluation of how well the AI model, developed using clinical data and smartwatch-recorded information including nocturnal oxygen saturation, predicts moderate-to-severe obstructive sleep apnea (defined as apnea-hypopnea index ≥15/hour) diagnosed by polysomnography.

  Up to 2 weeks prior to the polysomnography test.

Secondary Outcomes (3)

• Predictive Accuracy of the Galaxy Watch Sleep Apnea Feature (SAF)

  Up to 2 weeks prior to the polysomnography test.

• Comparison of AI Model and Galaxy Watch Sleep Apnea Feature (SAF) Performance

  Up to 2 weeks prior to the polysomnography test.

• Comparison of AI Model and STOP-Bang Questionnaire Performance

  Up to 2 weeks prior to the polysomnography test.

Study Arms (1)

Smart Watch Group

Men and women aged 22 to 85 years who visited Seoul National University Hospital with suspected sleep apnea due to symptoms such as snoring, apnea, or excessive daytime.

Device: Galaxy Watch 4, Samsung Electronics Co., Ltd., South Korea

Interventions

Galaxy Watch 4, Samsung Electronics Co., Ltd., South Korea DEVICE

Use of the Galaxy Watch 4 during sleep for approximately two weeks prior to the polysomnography test, including the night of the test.

Smart Watch Group

Eligibility Criteria

• Age: 22 Years - 85 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Men and women aged 22 to 85 years who visited Seoul National University Hospital with suspected sleep apnea due to symptoms such as snoring, apnea, or excessive daytime sleepiness.

You may qualify if:

• Men and women aged 22 to 85 years who visited Seoul National University Hospital with suspected sleep apnea due to symptoms such as snoring, apnea, or excessive daytime sleepiness.

You may not qualify if:

• Patients previously diagnosed with sleep apnea who are currently undergoing treatment (e.g., positive airway pressure \[PAP\] therapy, mechanical ventilation, oral appliances, or surgery).
• Patients with neuromuscular diseases or a history of chronic opioid medication use.
• Patients with severe insomnia that is not controlled by medication.
• Patients receiving supplemental oxygen therapy due to underlying conditions such as heart failure, chronic obstructive pulmonary disease, interstitial lung disease, hypoventilation syndrome, or stroke, or whose baseline oxygen saturation is less than 90%.
• Patients with implanted cardiac pacemakers, defibrillators, or other electronic devices.
• Patients inexperienced in using smartphones, apps, or smartwatches.
• Pregnant women.
• Patients unable or unwilling to provide written informed consent.

Sponsors & Collaborators

• Seoul National University Hospital: lead

Study Sites (1)

Seoul National University Hospital

Seoul, 03080, South Korea

RECRUITING

Study Officials

• Jaeyoung Cho, M.D., Ph.D.

  Seoul National University Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jaeyoung Cho, M.D., Ph.D.

CONTACT

+82-2-2072-2503; apricot6@snu.ac.kr

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Associate Professor

Study Record Dates

• First Submitted: January 19, 2025
• First Posted: January 24, 2025
• Study Start: February 3, 2025
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: May 15, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL

Locations

KR (1)