mmFlow: Facilitating At-Home Spirometry with 5G Smart Devices
mmFlow: Facilitating At-Home Spirometry with 5G Smart Devices
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DOI：
10.1109/secon52354.2021.9491616
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Aakriti Adhikari;A. Hetherington;Sanjib Sur
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文献类型：
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作者：
Aakriti Adhikari;A. Hetherington;Sanjib Sur
几十年来，哮喘、慢性阻塞性肺病等呼吸道疾病一直是公共卫生面临的重大挑战。便携式肺活量计在门诊连续监测呼吸综合征方面是有效的。然而，现有的系统要么成本高昂，要么提供的信息有限，需要额外的硬件。在本文中，我们介绍了MmFlow，一种使用5G智能设备在家中执行肺活量测试的低障碍手段。MmFlow的工作原理类似于常规的肺活量计，用户可以对着设备用力呼气；但MmFlow不依赖于特殊用途的硬件，而是利用通用、无处不在的移动设备中的内置毫米波技术。MmFlow分析设备表面气流产生的微小振动，并将无线信号处理与深度学习相结合，以实现仅限软件的肺活量测量解决方案。通过实证评估，我们发现，当设备距离固定时，MmFlow可以预测肺活量指标，其预测性能与临床肺活量计相当，预测误差为5%。此外，MMFlow在不同的环境和人体条件下都具有很好的通用性，因此它在门诊日常监测中很有前途。
Respiratory diseases, like Asthma, COPD, have been a significant public health challenge over decades. Portable spirometers are effective in continuous monitoring of respiratory syndromes out-of-clinic. However, existing systems are either costly or provide limited information and require extra hardware. In this paper, we present mmFlow, a low-barrier means to perform at-home spirometry tests using 5G smart devices. mmFlow works like regular spirometers, where a user forcibly exhales onto a device; but instead of relying on special-purpose hardware, mmFlow leverages built-in millimeter-wave technology in general-purpose, ubiquitous mobile devices. mmFlow analyzes the tiny vibrations created by the airflow on the device surface and combines wireless signal processing with deep learning to enable a software-only spirometry solution. From empirical evaluations, we find that, when device distance is fixed, mmFlow can predict the spirometry indicators with performance comparable to inclinic spirometers with <5% prediction errors. Besides, mmFlow generalizes well under different environments and human conditions, making it promising for out-of-clinic daily monitoring.