HCFeb 15, 2013

Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home

arXiv:1302.3820v1146 citations
Originality Incremental advance
AI Analysis

This enables locating a non-moving breathing person without calibration, which is important for applications in search and rescue, health care, and security.

The paper tackles the problem of estimating a person's breathing rate and location in a home using wireless network RSS measurements, despite motion interference, achieving an average location error of about 2 meters in a 56 square meter apartment.

This paper explores using RSS measurements on many links in a wireless network to estimate the breathing rate of a person, and the location where the breathing is occurring, in a home, while the person is sitting, laying down, standing, or sleeping. The main challenge in breathing rate estimation is that "motion interference", i.e., movements other than a person's breathing, generally cause larger changes in RSS than inhalation and exhalation. We develop a method to estimate breathing rate despite motion interference, and demonstrate its performance during multiple short (3-7 minute) tests and during a longer 66 minute test. Further, for the same experiments, we show the location of the breathing person can be estimated, to within about 2 m average error in a 56 square meter apartment. Being able to locate a breathing person who is not otherwise moving, without calibration, is important for applications in search and rescue, health care, and security.

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