  This paper addresses the performance of systems which use commercial wireless
devices to make bistatic RF channel measurements for non-contact respiration
sensing. Published research has typically presented results from short
controlled experiments on one system. In this paper, we deploy an extensive
real-world comparative human subject study. We observe twenty patients during
their overnight sleep (a total of 160 hours), during which contact sensors
record ground-truth breathing data, patient position is recorded, and four
different RF breathing monitoring systems simultaneously record measurements.
We evaluate published methods and algorithms. We find that WiFi channel state
information measurements provide the most robust respiratory rate estimates of
the four RF systems tested. However, all four RF systems have periods during
which RF-based breathing estimates are not reliable.
