  Radio signals are sensitive to changes in the environment, which for example
is reflected on the received signal strength (RSS) measurements of low-cost
wireless devices. This information has been used effectively in the past years
e.g. in device-free localization and tracking. Recent literature has also shown
that the fading information of the wireless channel can be exploited to
estimate the breathing rate of a person in a non-invasive manner; a research
topic we address in this paper. To the best of our knowledge, we demonstrate
for the first time that the respiration rate of a person can be accurately
estimated using only a single IEEE 802.15.4 compliant TX-RX pair. We exploit
channel diversity, low-jitter periodic communication, and oversampling to
enhance the breathing estimates, and make use of a decimation filter to
decrease the computational requirements of breathing estimation. In addition,
we develop a hidden Markov model (HMM) to identify the time instances when
breathing estimation is not possible, i.e., during times when other motion than
breathing occurs. We experimentally validate the accuracy of the system and the
results suggest that the respiration rate can be estimated with a mean error of
0.03 breaths per minute, the lowest breathing rate error reported to date using
IEEE 802.15.4 compliant transceivers. We also demonstrate that the breathing of
two people can be monitored simultaneously, a result not reported in earlier
literature.
