Full metadata
Title
Vital sign estimation through Doppler radar
Description
Doppler radar can be used to measure respiration and heart rate without contact and through obstacles. In this work, a Doppler radar architecture at 2.4 GHz and a new signal processing algorithm to estimate the respiration and heart rate are presented. The received signal is dominated by the transceiver noise, LO phase noise and clutter which reduces the signal-to-noise ratio of the desired signal. The proposed architecture and algorithm are used to mitigate these issues and obtain an accurate estimate of the heart and respiration rate. Quadrature low-IF transceiver architecture is adopted to resolve null point problem as well as avoid 1/f noise and DC offset due to mixer-LO coupling. Adaptive clutter cancellation algorithm is used to enhance receiver sensitivity coupled with a novel Pattern Search in Noise Subspace (PSNS) algorithm is used to estimate respiration and heart rate. PSNS is a modified MUSIC algorithm which uses the phase noise to enhance Doppler shift detection. A prototype system was implemented using off-the-shelf TI and RFMD transceiver and tests were conduct with eight individuals. The measured results shows accurate estimate of the cardio pulmonary signals in low-SNR conditions and have been tested up to a distance of 6 meters.
Date Created
2013
Contributors
- Khunti, Hitesh Devshi (Author)
- Kiaei, Sayfe (Thesis advisor)
- Bakkaloglu, Bertan (Committee member)
- Bliss, Daniel (Committee member)
- Kitchen, Jennifer (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
viii, 57 p. : ill. (some col.)
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.18711
Statement of Responsibility
by Hitesh Devshi Khunti
Description Source
Viewed on Jan. 27, 2014
Level of coding
full
Note
thesis
Partial requirement for: M.S., Arizona State University, 2013
bibliography
Includes bibliographical references (p. 55-57)
Field of study: Electrical engineering
System Created
- 2013-10-08 04:23:24
System Modified
- 2021-08-30 01:38:34
- 3 years 3 months ago
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