Publications
4 results found
Chen Z, Bannon A, Rapeaux A, et al., 2021, Towards robust, unobtrusive sensing of respiration using UWB impulse Radar for the care of people living with dementia, 10th International IEEE-EMBS Conference on Neural Engineering (NER), Publisher: IEEE, Pages: 866-871, ISSN: 1948-3546
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.
Bannon A, Rapeaux A, Constandinou TG, 2021, Tiresias: A low-cost networked UWB radar system for in-home monitoring of dementia patients, 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), Pages: 7068-7072, ISSN: 1557-170X
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Bannon A, Capraru R, Ritchie M, 2020, Exploring gesture recognition with low-cost CW radar modules in comparison to FMCW architectures, 2020 IEEE International Radar Conference (RADAR), Publisher: IEEE
Woollard M, Bannon A, Ritchie M, et al., 2019, Synthetic aperture radar automatic target classification processing concept, Electronics Letters, Vol: 55, Pages: 1301-1303, ISSN: 0013-5194
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