透气软生物电子产品用于增强阻塞性睡眠呼吸暂停的自动检测
Seunghyeb Ban1, Youngjin Kwon2, Ikhwan Shin3
1George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Wearable Intelligent Systems and Healthcare Center (WISH Center) at the Institute for Matter and Systems, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
Biosensors & bioelectronics
|July 3, 2025
概括
一个新的无线可穿戴设备可以使用AI检测儿童的阻塞性睡眠呼吸暂停 (OSA). 该系统为诊断儿科OSA提供了传统睡眠研究的舒适,可访问的替代方案.
科学领域:
- 生物医学工程 生物医学工程
- 人工智能的人工智能
- 睡眠医学 睡眠医学
背景情况:
- 阻塞性睡眠呼吸暂停 (OSA) 影响1%至5%的儿童,口唇/ palatal裂和dentofacial形患者的发病率更高.
- 目前的诊断方法,如多睡眠学是昂贵的,复杂的,不舒服的,限制了儿童患者的访问.
- 需要为儿科OSA提供可访问的,非侵入性的诊断工具.
研究的目的:
- 推出一种新的无线,柔软和透气的生物电子系统,用于检测儿童的阻塞性睡眠呼吸暂停 (OSA).
- 开发一个深度学习框架,用于自动分类睡眠阶段和检测呼吸暂停事件.
- 为诊断儿科OSA和监测整形外科手术结果提供基础.
主要方法:
- 开发一种可穿戴生物电子系统,具有穿孔,可变形的结构,以改善皮肤符合性和减少运动工件.
- 使用可穿戴设备测量来自脸部的电生理信号.
- 应用深度学习框架,结合多流卷积神经网络和双向长短期记忆模型进行数据分析.
主要成果:
- 开发的系统通过分析电生理信号,成功检测阻塞性睡眠呼吸暂停 (OSA).
- 深度学习模型准确地分类睡眠阶段,并识别呼吸暂停事件.
- 可穿戴设备的设计最大限度地减少了不适和运动工件,提高了数据质量.
结论:
- 无线生物电子系统为诊断儿科阻塞性睡眠呼吸暂停 (OSA) 提供了一个有希望的,易于使用的解决方案.
- 这项技术有可能改善高风险儿科群体OSA的早期诊断和管理.
- 该系统还可以用于区分手术前和手术后的睡眠模式,在患者进行骨架手术.
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