Signal quality detection towards practical non-touch vital sign monitoring
Signal quality detection towards practical non-touch vital sign monitoring
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DOI：
10.1145/3459930.3469526
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Zongxing Xie;Bing Zhou;Fan Ye
中科院分区：
文献类型：
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作者：
Zongxing Xie;Bing Zhou;Fan Ye
非触摸生命体征感测正变得流行，因为它不需要用户的合作努力（例如，充电、佩戴），便于纵向监测。在最近使用Wi-Fi、毫米波（mmWave）或超宽带（UWB）的基于无线电的心脏和呼吸率（HR和RR）感测中，不可避免的用户移动或背景移动对象对弱得多的呼吸和心脏信号造成大的干扰。必须检测并排除这种“损坏的”信号，以避免进行错误的测量。尽管进行了多次尝试，但可靠的信号质量检测（SQD）仍然没有得到解决。在本文中，我们花了80多个小时手动检查从8个参与者收集的50268个数据样本。我们发现，心脏和呼吸信号并不总是同时可用，这打破了以前的工作中的一个重要假设。我们提出了一个2位的SQD来分别对它们的“可用性”进行分类。我们进一步量化的贡献和一组全面的功能在时域和频域之间的相关性，并使用前向选择策略，以确定一个最佳的和更小的功能集多个常见的分类算法。大量的实验表明，我们的2位SQD在检测可用的RR/HR信号时达到91/95%的精度，88/91%的召回率，与先前工作中的平坦谱检测器（FSD）[3]和谱平均谐波路径检测器（SHAPA）[24]相比，并将80百分位RR/HR误差从10/18 bpm降低到3.5/4.0 bpm，降低了3~4倍。
Non-touch vital sign sensing is gaining popularity because it does not require users' cooperative efforts (e.g., charging, wearing) thus convenient for longitudinal monitoring. In recent radio-based heart and respiration rate (HR and RR) sensing using Wi-Fi, millimeter wave (mmWave), or ultra-wideband (UWB), inevitable user movements or background moving objects cause large disturbances to the much weaker respiratory and heart signals. Such "corrupted" signals must be detected and excluded to avoid making erroneous measurements. Despite several attempts, reliable signal quality detection (SQD) remains unresolved. In this paper, we spent over 80 hours to manually examine 50268 data samples collected from 8 participants. We find that heart and respiration signals are not always simultaneously available, which breaks an important assumption in prior work. We propose a 2-bit SQD to classify their "availability" separately. We further quantify the contributions of and correlation among a comprehensive set of features in both time and frequency domains, and use a forward selection strategy to identify an optimal and much smaller feature set for multiple common classification algorithms. Extensive experiments show that our 2-bit SQD achieves 91/95% precision, 88/91% recall in detecting available RR/HR signals, as compared to a flat spectrum detector (FSD) [3] and a spectrum-averaged harmonic path detector (SHAPA) [24] in prior work, and reduces the 80-percentile RR/HR errors from 10/18 bpm to 3.5/4.0 bpm, 3~4 fold reductions.