Scientific Reports (May 2022)

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

  • Marco Mercuri,
  • Pietro Russo,
  • Miguel Glassee,
  • Ivan Dario Castro,
  • Eddy De Greef,
  • Maxim Rykunov,
  • Marc Bauduin,
  • André Bourdoux,
  • Ilja Ocket,
  • Felice Crupi,
  • Tom Torfs

DOI
https://doi.org/10.1038/s41598-022-11671-1
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 11

Abstract

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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 $$^{\circ }$$ ∘ and maximum root-mean-square errors (RMSEs) of 0.12 m and 3.04 $$^{\circ }$$ ∘ 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.