demonstration

RUBreathing: non-contact real time respiratory rate monitoring system

Authors:

Anh Luong,

Spencer Madsen,

Michael Empey,

Neal PatwariAuthors Info & Claims

IPSN '15: Proceedings of the 14th International Conference on Information Processing in Sensor Networks

Pages 412 - 413

https://doi.org/10.1145/2737095.2737133

Published: 13 April 2015 Publication History

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Abstract

The respiration rate of a person provides critical information about their well-being. Conventionally, contact sensing is used for breathing monitoring; however, it is expensive, uncomfortable, and immobile. In-home non-contact breathing monitoring is now possible via Doppler radar and motion capture video sensors, yet these technologies are limited in mobility, among other limitations. When monitoring a patient who is free to move around his or her home, it is dificult to scale current non-contact sensors to cover the large area. Our RUBreathing sensor system uses RF received signal strength (RSS) in a network to estimate breathing rate in real-time with high accuracy over a wide area. In this demonstration, we show the sensor continuously estimating a patient's respiration rate from non-contact RSS measurements between wireless devices.

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O. J. Kaltiokallio, H. Yigitler, R. Jäntti, and N. Patwari. Non-invasive respiration rate monitoring using a single cots tx-rx pair. In Proceedings of the 13th international symposium on Information processing in sensor networks, pages 59--70. IEEE Press, 2014.

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Li YZhu TChen XWang XHuang X(2016)Gait-Based Wi-Fi Signatures for Privacy-PreservingProceedings of the 11th ACM on Asia Conference on Computer and Communications Security10.1145/2897845.2897909(571-582)Online publication date: 30-May-2016
https://dl.acm.org/doi/10.1145/2897845.2897909
Li YZhu T(2016)Using Wi-Fi Signals to Characterize Human Gait for Identification and Activity Monitoring2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE.2016.20(238-247)Online publication date: Jun-2016
https://doi.org/10.1109/CHASE.2016.20

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RUBreathing: non-contact real time respiratory rate monitoring system

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Information & Contributors

Information

Published In

IPSN '15: Proceedings of the 14th International Conference on Information Processing in Sensor Networks

April 2015

430 pages

ISBN:9781450334754

DOI:10.1145/2737095

General Chair:
Suman Nath
Microsoft Research
,
Program Chairs:
Bhaskar Krishnamachari
University of Southern California
,
Anthony Rowe
Carnegie Mellon University

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 April 2015

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Qualifiers

Demonstration

Conference

IPSN '15

Sponsor:

IEEE-SPS
IEEE-CSS
ACM
SIGBED
IEEE-CS IRTS

IPSN '15: The 14th International Conference on Information Processing in Sensor Networks

April 13 - 16, 2015

Washington, Seattle

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Li YZhu TChen XWang XHuang X(2016)Gait-Based Wi-Fi Signatures for Privacy-PreservingProceedings of the 11th ACM on Asia Conference on Computer and Communications Security10.1145/2897845.2897909(571-582)Online publication date: 30-May-2016
https://dl.acm.org/doi/10.1145/2897845.2897909
Li YZhu T(2016)Using Wi-Fi Signals to Characterize Human Gait for Identification and Activity Monitoring2016 IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)10.1109/CHASE.2016.20(238-247)Online publication date: Jun-2016
https://doi.org/10.1109/CHASE.2016.20

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