Please use this identifier to cite or link to this item:
Physiological Parameter Sensing with Wearable Devices and Non-Contact Dopper Radar.
|Title:||Physiological Parameter Sensing with Wearable Devices and Non-Contact Dopper Radar.|
|Authors:||Lee, Alexander G. S. K.|
|Contributors:||Electrical Engineering (department)|
Vital Sign Sensing
|Date Issued:||May 2017|
|Publisher:||University of Hawaiʻi at Mānoa|
|Abstract:||Vital sign measurement with wearable devices is an important need in the|
paradigm shift occurring with health care. The Internet of things (IoT) is a concept that
will allow healthcare providers to keep up to date continuously on the health of their
patients through accurate wearable sensors and non-contact sensing in their homes. In
order to meet this growing need for robust sensors, there are currently many devices that
sense physiological parameters through photo-plethysmography (PPG) and piezoelectric
methods. These methods of sensing have their own inherent limitations which include
low flexibility, inaccuracy at higher rates, and susceptibility to motion artifact.
Elastomeric sensors are another material being explored because of it’s potential for
higher flexibility than piezoelectric pressure sensors. A wearable elastomeric arm sensor,
that was designed and tested on the upper arm of 3 subjects, showed capability of
measuring respiratory and heart rate with a low voltage DC power source.
In addition to wearable sensors, there is a need for non-contact sensing in home
health monitoring. Previous research with Doppler radar physiological sensing has
focused mostly on measuring respiratory rate and displacement accurately. Recent work
with radar cross-section (RCS) measurements, have shown that it is possible to determine
body position of a subject based on the RCS. A study was done to investigate the
dynamic RCS of a human subject during varying respiration depth. Measurement with a
retro-reflective infrared camera marker on the sternum of the subject was used as a
reference and compared with a 2.4GHz continuous wave Doppler radar system. Results
showed that the RCS of a subject facing the radar changed between deep and shallow
breathing. A further study with 13 reference markers revealed that there were two main
areas, sternum and abdomen, that contributed to the overall dynamic RCS. The
implications of this study are important for accurately determining subject position,
medical diagnosis, and unique identification with Doppler radar
|Description:||M.S. Thesis. University of Hawaiʻi at Mānoa 2017.|
|Rights:||All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
M.S. - Electrical Engineering|
Please email firstname.lastname@example.org if you need this content in ADA-compliant format.
Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.