College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.
The International Joint Laboratory on Intelligent Health Monitoring Systems, Fuzhou University, Fuzhou 350108, China.
Biosensors (Basel). 2022 Oct 27;12(11):934. doi: 10.3390/bios12110934.
The respiratory rate is one of the crucial indicators for monitoring human physiological health. The purpose of this paper was to introduce a head-mounted respiratory monitoring solution based on electrical impedance sensing. Firstly, we constructed a finite element model to analyze the feasibility of using head impedance for respiratory sensing based on the physiological changes in the pharynx. After that, we developed a circuit module that could be integrated into a head-mounted respiratory monitoring device using a bioelectrical impedance sensor. Furthermore, we combined adaptive filtering and respiratory tracking algorithms to develop an app for a mobile phone. Finally, we conducted controlled experiments to verify the effectiveness of this electrical impedance sensing system for extracting respiratory rate. We found that the respiration rates measured by the head-mounted electrical impedance respiratory monitoring system were not significantly different from those of commercial respiratory monitoring devices by a paired t-test (p > 0.05). The results showed that the respiratory rates of all subjects were within the 95% confidence interval. Therefore, the head-mounted respiratory monitoring scheme proposed in this paper was able to accurately measure respiratory rate, indicating the feasibility of this solution. In addition, this respiratory monitoring scheme helps to achieve real-time continuous respiratory monitoring, which can provide new insights for personalized health monitoring.
呼吸频率是监测人体生理健康的关键指标之一。本文旨在介绍一种基于电阻抗感应的头戴式呼吸监测解决方案。首先，我们构建了一个有限元模型，基于咽腔生理变化分析了使用头部阻抗进行呼吸感应的可行性。然后，我们开发了一个可以集成到头戴式呼吸监测设备中的电路模块，该模块使用生物电阻抗传感器。此外，我们结合自适应滤波和呼吸跟踪算法，开发了一个适用于手机的应用程序。最后，我们进行了对照实验，以验证该电阻抗感应系统提取呼吸率的有效性。我们发现，通过配对 t 检验（p＞0.05），头戴式电阻抗呼吸监测系统测量的呼吸率与商业呼吸监测设备测量的呼吸率没有显著差异。结果表明，所有受试者的呼吸率都在 95%置信区间内。因此，本文提出的头戴式呼吸监测方案能够准确测量呼吸率，表明该解决方案具有可行性。此外，这种呼吸监测方案有助于实现实时连续呼吸监测，为个性化健康监测提供新的见解。
