论文标题
使用门控变压器的非接触式氧气监测
Contactless Oxygen Monitoring with Gated Transformer
论文作者
论文摘要
随着远程医疗的日益普及，至关重要的是要确保可以在家中准确监控基本的生理信号，而患者的头顶最少。在本文中，我们提出了一种非接触式方法，可以通过分析房间中的无线电信号，而无需任何可穿戴设备，以监测患者在家中的血液氧。我们从无线电信号中提取患者的呼吸，这些无线电信号从他们的身体中反弹，并设计出一种新型的神经网络，从而从呼吸信号中估计患者的氧气。我们的模型称为\ emph {门控BERT-UNET}，旨在适应患者的医疗指数（例如，性别，睡眠阶段）。它具有多个预测头，并通过由人的生理指数控制的栅极选择最合适的头。广泛的经验结果表明，我们的模型在医疗和无线电数据集上都具有很高的精度。
With the increasing popularity of telehealth, it becomes critical to ensure that basic physiological signals can be monitored accurately at home, with minimal patient overhead. In this paper, we propose a contactless approach for monitoring patients' blood oxygen at home, simply by analyzing the radio signals in the room, without any wearable devices. We extract the patients' respiration from the radio signals that bounce off their bodies and devise a novel neural network that infers a patient's oxygen estimates from their breathing signal. Our model, called \emph{Gated BERT-UNet}, is designed to adapt to the patient's medical indices (e.g., gender, sleep stages). It has multiple predictive heads and selects the most suitable head via a gate controlled by the person's physiological indices. Extensive empirical results show that our model achieves high accuracy on both medical and radio datasets.
