Wi-Fi sensing has become an attractive option for non-invasive monitoring of human activities and vital signs. This paper explores the feasibility of using state-of-the-art commercial off-the-shelf (COTS) devices for Wi-Fi sensing applications, particularly respiration monitoring and motion detection. We utilize the Intel AX210 network interface card (NIC) to transmit Wi-Fi signals in both 2.4 GHz and 6 GHz frequency bands. Our experiments rely on channel frequency response (CFR) and received signal strength indicator (RSSI) data, which are processed using a moving average algorithm to extract human behavior patterns. The experimental results demonstrate the effectiveness of our approach in capturing and representing human respiration and motion patterns. Furthermore, we compare the performance of Wi-Fi sensing across different frequency bands, highlighting the advantages of using higher frequencies for improved sensitivity and clarity. Our findings showcase the practicality of using COTS devices for Wi-Fi sensing and lay the groundwork for the development of non-invasive, contactless sensing systems. These systems have potential applications in various fields, including healthcare, smart homes, and Metaverse.

翻译：Wi-Fi感知已成为非侵入式监测人体活动与生命体征的一种颇具吸引力的选择。本文探讨了使用先进的商用现成（COTS）设备进行Wi-Fi感知应用的可行性，特别是呼吸监测与运动检测。我们采用英特尔AX210网络接口卡（NIC）在2.4 GHz和6 GHz频段发射Wi-Fi信号。实验依赖于信道频率响应（CFR）与接收信号强度指示器（RSSI）数据，并通过移动平均算法进行处理以提取人类行为模式。实验结果证明了我们的方法在捕获和表征人体呼吸与运动模式方面的有效性。此外，我们比较了不同频段下Wi-Fi感知的性能，凸显了使用更高频率在提升灵敏度与清晰度方面的优势。我们的研究结果展示了使用COTS设备进行Wi-Fi感知的实用性，并为开发非侵入式、非接触感知系统奠定了基础。此类系统在医疗保健、智能家居及元宇宙等多个领域具有潜在应用前景。