Name
Abstract | ||
|---|---|---|
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.
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Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3241539.3241560 | MobiCom '18: The 24th Annual International Conference on Mobile Computing and Networking
New Delhi
India
October, 2018 |
Field | DocType | ISBN |
Signal processing,Wireless,Computer science,Communication channel,Computer network,Real-time computing,Bistatic radar,Breathing,Respiratory monitoring,Wireless sensor network,Channel state information | Conference | 978-1-4503-5903-0 |
Citations | PageRank | References |
1 | 0.35 | 34 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter Hillyard | 1 | 8 | 4.01 |
| Anh Luong | 2 | 1 | 0.69 |
| Alemayehu Solomon Abrar | 3 | 11 | 3.02 |
| Neal Patwari | 4 | 3805 | 241.58 |
| Krishna Sundar | 5 | 1 | 0.35 |
| Robert J. Farney | 6 | 1 | 0.69 |
| Jason Burch | 7 | 1 | 0.35 |
| Christina A. Porucznik | 8 | 1 | 0.35 |
| Sarah Hatch Pollard | 9 | 1 | 0.35 |