CardioFi

Abstract

Heart rate is one of the most important vital signals for personal health tracking. A number of approaches were proposed to monitor heart rate, ranging from wearables to device-less systems. While WiFi has been shown to track heart rate accurately, existing solutions rely on directional antennas to improve the signal quality and ultimately the accuracy of heart rate estimation. Special hardware used in these approaches limits their applicability and truly device-less and ubiquitous heart rate monitoring is yet to be achieved.In this paper, we propose CardioFi: a system that can accurately monitor vital signs through COTS WiFi hardware with omnidirectional antennas. Our key challenge is the substantial radio frequency noise that affects WiFi transmissions in real-world environments. However, we observe that a few sub-carriers are typically less affected by multipath and the heart beating motion can be accurately detected in their frequency spectrum. We present a novel sub-carrier selection scheme that allows us to detect and amplify signal from these sub-carriers even in low signal-to-noise ratio scenarios. We show that CardioFi estimates heart rate with 1.1 beats per minute (bpm) median error, which compares favorably with systems equipped with directional antennas. Furthermore, we show that state-of-art heart rate estimation algorithms do not perform well in low SNR scenarios and CardioFi improves their 50- and 90-th percentile error by 40% and 176%, respectively.