WiResP: A Robust WiFi-Based Respiration Monitoring via Spectrum Enhancement

Respiration monitoring has been attracting substantial attention because of its potential for assessing sleep stages and quality.Traditional approaches for respiratory rate tracking require dedicated wearable devices, which can intrude upon and create an unwelcoming experience for users. To address this, researchers have proposed WiFi-based respiration monitoring systems which capitalize on WiFi's ubiquity, cost-effectiveness, and non-contact nature, effectively converting existing infrastructure into ubiquitous sensors. However, existing systems often struggle with the subtle signal to noise ratio of embedded breathing signals, leading to limited coverage and inflexible deployment in noisy environments. This paper presents WiResP (WiFi Respiration Perception), an ingenious and pragmatic WiFi-based system for tracking respiration, employing the spectrum enhancement approach to boost respiration detection. By treating the spectrum of the breathing signal obtained from channel state information as an image, the system is able to leverage image processing techniques to greatly enhance the respiration signal trace, improving detectability and increasing sensing coverage for respiratory rate estimation. Moreover, an image-based continuity checker module is proposed to verify the signal trace continuity to reduce false alarms. We conducted extensive experiments and assessed WiResP under different settings. The experiments demonstrate that WiResP can reliably capture respiratory rate during sleep and achieve a detection rate of 92% and a false alarm rate < 5%, leading to significantly improved sleep stage recognition under flexible device placements. The promising performance positions WiResP as a candidate for real-world in-home respiration tracking system.