Wi-Fi Beyond Communications: Experimental Evaluation of Respiration Monitoring and Motion Detection Using COTS Devices

TL;DR

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, and compares the performance of Wi-Fi sensing across different frequency bands.

Abstract

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.

Figures (4)

• Figure 1: The experimental layout and environment of respiration monitoring.
• Figure 2: The experimental layout and environment of motion detection.
• Figure 3: Experimental results of respiration monitoring using Wi-Fi signals in the $2.4$$\mathrm{GHz}$ and $6$$\mathrm{GHz}$ frequency bands. The experiments capture both normal breathing patterns and breath-holding periods, demonstrating the effectiveness of using Wi-Fi sensing for non-invasive respiration monitoring. The $6$$\mathrm{GHz}$ signals provide clearer and more pronounced respiration patterns compared to the $2.4$$\mathrm{GHz}$ signals.
• Figure 4: Experimental results of motion detection using Wi-Fi signals in the $2.4$$\mathrm{GHz}$ and $6$$\mathrm{GHz}$ bands. The experiments demonstrate the effectiveness of Wi-Fi sensing for non-invasive motion detection, with $6$$\mathrm{GHz}$ signals providing sharper motion patterns compared to $2.4$$\mathrm{GHz}$. The processed signals indicate the participant's movement along the predefined path, showcasing the feasibility of Wi-Fi sensing for real-time motion detection.