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Automatic radar-based 2-D localization exploiting vital signs signatures

Articolo
Data di Pubblicazione:
2022
Citazione:
Automatic radar-based 2-D localization exploiting vital signs signatures / Mercuri, M., Russo, P., Glassee, M., Castro, I.D., De Greef, E., Rykunov, M., Bauduin, M., Bourdoux, A., Ocket, I., Crupi, F., Torfs, T.. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 12:7651(2022). [10.1038/s41598-022-11671-1]
Abstract:
In light of the continuously and rapidly growing senior and geriatric population, the research of new technologies enabling long-term remote patient monitoring plays an important role. For this purpose, we propose a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system and a signal processing technique to automatically detect the number and the 2-D position (azimuth and range information) of stationary people (seated/lying down). This is achieved by extracting the vital signs signatures of each single individual, separating the Doppler shifts caused by the cardiopulmonary activities from the unwanted reflected signals from static reflectors and multipaths. We then determine the number of human subjects present in the monitored environment by counting the number of extracted vital signs signatures while the 2-D localization is performed by measuring the distance from the radar where the vital signs information is sensed (i.e., locating the thoracic region). We reported maximum mean absolute errors (MAEs) of 0.1 m and 2.29[Formula: see text] and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04[Formula: see text] in measuring respectively the ranges and azimuth angles. The experimental validation demonstrated the ability of the proposed approach in monitoring paired human subjects in a typical office environment.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Mercuri, Marco; Russo, Pietro; Glassee, Miguel; Castro, Ivan Dario; De Greef, Eddy; Rykunov, Maxim; Bauduin, Marc; Bourdoux, André; Ocket, Ilja; Crupi, Felice; Torfs, Tom
Autori di Ateneo:
Mercuri Marco
Link alla scheda completa:
https://iris.unirc.it/handle/20.500.12318/149970
Link al Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/149970/396197/Mercuri_2022_SciReports_Automatic_Editor.pdf
Pubblicato in:
SCIENTIFIC REPORTS
Journal
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URL

https://www.nature.com/articles/s41598-022-11671-1
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