用于非接触式呼吸频率监测的智能床传感器系统
An Intelligent Bed Sensor System for Non-Contact Respiratory Rate Monitoring
摘要：
我们提出了一种基于物联网的智能床传感器系统，可以收集和分析与呼吸相关的信号，以便在家庭、医院和护理单位进行不引人注目的监控。使用非接触式设备，其中包含四个安装在床下的负载传感器和一个数据处理单元（数据记录器）。各种机器学习方法应用于从数据记录器流出的数据，以检测呼吸率（RR）。我们已经实现了支持向量机（SVM），也神经网络（NN）为基础的模式识别方法，这是结合峰值检测或希尔伯特变换鲁棒RR计算。实验结果表明，我们的方法可以有效地提取RR使用非接触式床传感器收集的数据。所提出的方法是鲁棒的离群值和噪声，这是由身体运动引起的。该监测系统提供了一种灵活和可扩展的方式，使用嵌入式传感器连续和远程监测睡眠，运动和体重。
英文摘要：
We present an IoT-based intelligent bed sensor system that collects and analyses respiration-associated signals for unobtrusive monitoring in the home, hospitals and care units. A contactless device is used, which contains four load sensors mounted under the bed and one data processing unit (data logger). Various machine learning methods are applied to the data streamed from the data logger to detect the Respiratory Rate (RR). We have implemented Support Vector Machine (SVM) and also Neural Network (NN)-based pattern recognition methods, which are combined with either peak detection or Hilbert transform for robust RR calculation. Experimental results show that our methods could effectively extract RR using the data collected by contactless bed sensors. The proposed methods are robust to outliers and noise, which are caused by body movements. The monitoring system provides a flexible and scalable way for continuous and remote monitoring of sleep, movement and weight using the embedded sensors.
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