Smartwatch-Based Artificial Intelligence Model for Obstructive Sleep Apnea Prediction
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 147
- 试验地点
- 1
- 主要终点
- Predictive Accuracy of the AI Model for Moderate-to-Severe Obstructive Sleep Apnea
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 22 Years 至 85 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Predictive Accuracy of the AI Model for Moderate-to-Severe Obstructive Sleep Apnea
时间窗: Up to 2 weeks prior to the polysomnography test.
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.
次要结局
- 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.)
研究者
Jaeyoung Cho
Associate Professor
Seoul National University Hospital