2011/09/18 by Neal Patwari, Patwari, Neal, Joey Wilson +7
Computer Science · Medicine · #Emerging Technologies (cs.ET) #Energy Efficient Wireless Sensor Networks #FOS: Computer and information sciences #Networking and Internet Architecture (cs.NI) #Respiratory viral infections research #Wireless Networks and Protocols
paper · pdf · doi:10.48550/arxiv.1109.3898
openalex publication_date 2011/09/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper shows experimentally that standard wireless networks which measure received signal strength (RSS) can be used to reliably detect human breathing and estimate the breathing rate, an application we call "BreathTaking". We show that although an individual link cannot reliably detect breathing, the collective spectral content of a network of devices reliably indicates the presence and rate of breathing. We present a maximum likelihood estimator (MLE) of breathing rate, amplitude, and phase, which uses the RSS data from many links simultaneously. We show experimental results which demonstrate that reliable detection and frequency estimation is possible with 30 seconds of data, within 0.3 breaths per minute (bpm) RMS error. Use of directional antennas is shown to improve robustness to motion near the network.