Smartwatch-Based AI Model for OSA Prediction (SWOSA)
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age22-85
SponsorSeoul National University Hospital
About this trial
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.
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
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.
Disqualifiers
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%.
Trial 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.
Trial design
Design model
Cohort
Time perspective
Prospective
Treatments tested in this trial
Galaxy Watch 4, Samsung Electronics Co., Ltd., South Korea
DeviceUse of the Galaxy Watch 4 during sleep for approximately two weeks prior to the polysomnography test, including the night of the test.
Treatment groups
147 Participants
are divided into 1 treatment groupGroup A: Smart Watch Group1 intervention
Trial outcomes
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.
Time frame
Up to 2 weeks prior to the polysomnography test.Secondary outcomes
1
Predictive Accuracy of the Galaxy Watch Sleep Apnea Feature (SAF)
Assessment of the accuracy of the Galaxy Watch's built-in sleep apnea feature (SAF) in predicting moderate-to-severe obstructive sleep apnea diagnosed by polysomnography.
Time frame
Up to 2 weeks prior to the polysomnography test.2
Comparison of AI Model and Galaxy Watch Sleep Apnea Feature (SAF) Performance
Comparison of the predictive performance between the AI model developed in this study and the Galaxy Watch's built-in sleep apnea feature (SAF) for detecting moderate-to-severe obstructive sleep apnea.
Time frame
Up to 2 weeks prior to the polysomnography test.3
Comparison of AI Model and STOP-Bang Questionnaire Performance
Comparison of the predictive performance between the AI model developed in this study and the STOP-Bang questionnaire for detecting moderate-to-severe obstructive sleep apnea.
Time frame
Up to 2 weeks prior to the polysomnography test.Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Source ClinicalTrials.gov