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

Marco Mercuri1, Pietro Russo2, Miguel Glassee3

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This study introduces a radar system for remote patient monitoring of seniors. The technology accurately detects the number and 2D position of stationary individuals by analyzing vital signs.

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Geriatric Technology

Background:

  • The growing elderly population necessitates advanced remote patient monitoring solutions.
  • Existing technologies may have limitations in continuously monitoring stationary individuals.
  • Accurate detection and localization of individuals are crucial for effective healthcare.

Purpose of the Study:

  • To develop and validate a novel radar system for remote monitoring of stationary elderly individuals.
  • To automatically detect the number and two-dimensional (2D) position (azimuth and range) of people.
  • To extract vital signs signatures for individual identification and monitoring.

Main Methods:

  • Implementation of a single-input-multiple-output (SIMO) frequency-modulated continuous wave (FMCW) radar system.
  • Development of a signal processing technique to separate vital sign Doppler shifts from static reflections and multipaths.
  • Counting extracted vital signs signatures to determine the number of subjects and localizing them by sensing vital sign origin.

Main Results:

  • Accurate detection of the number of stationary individuals.
  • Precise 2D localization with maximum mean absolute errors of 0.1 m for range and 2.29° for azimuth.
  • Maximum root-mean-square errors of 0.12 m for range and 3.04° for azimuth.
  • Successful experimental validation in monitoring paired subjects in an office environment.

Conclusions:

  • The proposed SIMO FMCW radar system and signal processing technique effectively monitor stationary individuals.
  • The system accurately determines the number and 2D position of subjects by extracting vital signs.
  • This technology holds significant potential for long-term remote patient monitoring in geriatric care.