基于无线耳机的呼吸练习实时监测:一种深度学习方法
概括
这项研究引入了一种新的框架,使用无线耳机在家监测呼吸练习. 该系统准确地检测呼吸阶段和通道,帮助治疗遵守.
科学领域:
- 生物医学工程 生物医学工程
- 医疗保健中的人工智能
背景情况:
- 深呼吸练习对于许多疗法至关重要,但由于缺乏专门设备,在家监测患者的遵守是具有挑战性的.
- 现有的治疗合规性监测方法通常仅限于临床环境,阻碍了患者的一致参与.
研究的目的:
- 开发和验证一个框架,使用消费级硬件准确监测家庭呼吸练习.
- 评估患者在家庭环境中遵守呼吸疗法.
主要方法:
- 一个使用无线耳机和智能手机进行实时呼吸监测的新框架.
- 使用了两个卷积神经网络 (CNN):一个通道分类器 (鼻腔,口腔,暂停) 和一个阶段分类器 (吸入,呼出).
- 处理500毫秒的音频信号,用于准确的呼吸阶段和通道检测.
主要成果:
- 频道分类器获得了97.99%的F1最高分数,区分了鼻腔,口腔呼吸和暂停.
- 阶段分类器在确定吸入和呼气时获得了最高F1分数的89.46%.
- 使用商品耳机在实时呼吸通道和相位检测方面表现出高准确性.
结论:
- 商品耳机可以有效地用于实时呼吸通道和相位检测.
- 拟议的系统显示了在家庭环境中促进呼吸疗法合规性监测的巨大潜力.
- 这项技术可以提高需要定期呼吸练习的治疗方法的管理和结果.
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