Collage of published research papers

Citation

BibTex format

@inproceedings{Chen:2021:10.1109/NER49283.2021.9441392,
author = {Chen, Z and Bannon, A and Rapeaux, A and Constandinou, TG},
doi = {10.1109/NER49283.2021.9441392},
pages = {866--871},
publisher = {IEEE},
title = {Towards robust, unobtrusive sensing of respiration using UWB impulse Radar for the care of people living with dementia},
url = {http://dx.doi.org/10.1109/NER49283.2021.9441392},
year = {2021}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - The unobtrusive monitoring of vital signals and behaviour can be used to gather intelligence to support the care of people living with dementia. This can provide insights into the person's wellbeing and the neurogenerative process, as well as enable them to continue to live safely at home, thereby improving their quality of life. Within this context, this study investigated the deployability of non-contact respiration rate (RR) measurement based on an Ultra-Wideband (UWB) radar System-on-Chip (SoC). An algorithm was developed to simultaneously and continuously extract the respiration signal, together with the confidence level of the respiration signal and the target position, without needing any prior calibration. The radar-measured RR results were compared to the RR results obtained from a ground truth measure based on the breathing sound, and the error rates were within 8% with a mean value of 2.5%. The target localisation results match to the radar-to-chest distances with a mean error rate of 5.8%. The tested measurement range was up to 5m. The results suggest that the algorithm could perform sufficiently well in non-contact stationary respiration rate detection.
AU - Chen,Z
AU - Bannon,A
AU - Rapeaux,A
AU - Constandinou,TG
DO - 10.1109/NER49283.2021.9441392
EP - 871
PB - IEEE
PY - 2021///
SN - 1948-3546
SP - 866
TI - Towards robust, unobtrusive sensing of respiration using UWB impulse Radar for the care of people living with dementia
UR - http://dx.doi.org/10.1109/NER49283.2021.9441392
UR - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000681358200171&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR - http://hdl.handle.net/10044/1/91498
ER -

Awards

  • Finalist: Best Paper - IEEE Transactions on Mechatronics (awarded June 2021)

  • Finalist: IEEE Transactions on Mechatronics; 1 of 5 finalists for Best Paper in Journal

  • Winner: UK Institute of Mechanical Engineers (IMECHE) Healthcare Technologies Early Career Award (awarded June 2021): Awarded to Maria Lima (UKDRI CR&T PhD candidate)

  • Winner: Sony Start-up Acceleration Program (awarded May 2021): Spinout company Serg Tech awarded (1 of 4 companies in all of Europe) a place in Sony corporation start-up boot camp

  • “An Extended Complementary Filter for Full-Body MARG Orientation Estimation” (CR&T authors: S Wilson, R Vaidyanathan)

UK DRI


Established in 2017 by its principal funder the Medical Research Council, in partnership with Alzheimer's Society and Alzheimer’s Research UK, The UK Dementia Research Institute (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.