Overview

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

Inclusion Criteria:

• 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.

Exclusion Criteria:

• 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.