New Unobtrusive Tidal Volume Monitoring System Using Channel State Information in Wi-Fi Signal: Preliminary Result

In this paper, we propose a respiration monitoring system based on the channel state information received from a commercial off-the-shelf Wi-Fi device. We develop data processing modules for extracting respiration parameters from the Wi-Fi signal and estimate the relative tidal volume. In order to verify the performance of the proposed monitoring system, we use a human patient simulator and also test one real human subject in various experimental settings. With the human patient simulator, we evaluate the monitoring performance at various tidal volume levels and compare our monitoring results with the simulator settings. In testing with a human subject, we test our approach on different sleep postures and positions, Wi-Fi router's positions, and monitoring environments and compare our performance with the spirometer measurement. The results with both the human patient simulator and real human subject demonstrate the strong and robust estimation performance of the proposed approach in various monitoring conditions, indicating the high promise for non-intrusive respiration monitoring in practice.