强大的多模式咳检测,优化了可穿戴设备的分布外检测
IEEE journal of biomedical and health informatics
|October 2, 2025
概括
一个新的多式咳检测系统使用音频和IMU传感器与OOD检测,提高了远程呼吸监测的准确性. 该系统增强了隐私,并且在现实环境中性能强.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 可穿戴技术可穿戴技术
背景情况:
- 持续监测咳对于诊断呼吸道疾病至关重要.
- 可穿戴设备提供远程症状监测,但面临隐私和音频质量差等挑战.
- 现有的系统在与现实世界的声学复杂性和背景噪音作斗争.
研究的目的:
- 开发和优化使用音频和惯性测量单元 (IMU) 信号的紧型多式联络咳检测系统.
- 通过OOD检测算法来增强系统,以提高稳定性.
- 解决隐私问题和在现实世界远程监控设置中音频质量差的问题.
主要方法:
- 开发了一个集音频和IMU传感器的多式联网系统.
- 使用增强数据集和加权多损失方法优化了系统,用于In-Distribution (ID) 分类器.
- 通过重建训练数据组件,实现了一个OOD检测算法.
主要成果:
- 优化的系统在各种窗口大小 (1-5秒) 中表现出稳健性,在低音频频率下表现出效率.
- 在16kHz时保持高精度 (90.08%) 和咳F1得分 (0.7548),在750Hz时保持87.3%的精度 (0.7015F1得分),即使有50%的OOD数据.
- 具有OOD检测的多式模式优于单式模式模型,在咳检测方面显著改善.
结论:
- 具有OOD检测的Audio-IMU多式模式模型为现实世界声学咳检测提供了强大的解决方案.
- 该系统通过高效的低频音频处理来增强用户隐私.
- 通过结合更多多样化的非语音发音数据,可以实现进一步的改进.
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