Biomedical radar system for real-time contactless fall detection and indoor localization

Mercuri, Marco; Soh, Ping Jack; Mehrjouseresht, Pouya; Crupi, Felice; Schreurs, Dominique (2023-05-26)
 
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https://doi.org/10.1109/JERM.2023.3278473

Mercuri, Marco
Soh, Ping Jack
Mehrjouseresht, Pouya
Crupi, Felice
Schreurs, Dominique
Institute of Electrical and Electronics Engineers
26.05.2023

M. Mercuri, P. J. Soh, P. Mehrjouseresht, F. Crupi and D. Schreurs, "Biomedical Radar System for Real-Time Contactless Fall Detection and Indoor Localization," in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol. 7, no. 4, pp. 303-312, Dec. 2023, doi: 10.1109/JERM.2023.3278473

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doi:https://doi.org/10.1109/jerm.2023.3278473
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Abstract

Fall incidents represent a major public health problem among elderly people. This resulted in a significant increase of the number of investigated systems aiming at detecting falls promptly. In this respect, in this work, a biomedical radar system is proposed for remote real-time fall detection and indoor localization. The system, consisting of a sensor and a base station, combines radar and wireless communication techniques, and uses a data processing technique to distinguish between fall events and normal movements. The classification, based on a Least-Square Support Vector Machine (LS -SVM), combined with the sliding window principle allows to perform fall detection in real-time. Moreover, it is capable to localize the subjects when the fall incident has been detected. The in-vivo validation showed a high success rate in detecting fall events, with a maximum delay of 340 ms. Moreover, a maximum mean absolute errors (MAE) of 3.8 cm and a maximum root-mean-square error (RMSE) of 7.5 cm were reported in measuring the subject’s absolute distance.

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