Analysis of Signal Processing Methods to Reject the DC Offset Contribution of Static Reflectors in FMCW Radar-Based Vital Signs Monitoring

Sensors (Basel). 2022 Dec 10;22(24):9697. doi: 10.3390/s22249697.

Abstract

Frequency-modulated continuous wave (FMCW) radars are currently being investigated for remote vital signs monitoring (measure of respiration and heart rates) as an innovative wireless solution for healthcare and ambient assisted living. However, static reflectors (furniture, objects, stationary body parts, etc.) within the range or range angular bin where the subject is present contribute in the Doppler signal to a direct current (DC) offset. The latter is added to the person's information, containing also a useful DC component, causing signal distortion and hence reducing the accuracy in measuring the vital sign parameters. Removing the sole contribution of the unwanted DC offset is fundamental to perform proper phase demodulation, so that accurate vital signs monitoring can be achieved. In this work, we analyzed different DC offset calibration methods to determine which one achieves the highest accuracy in measuring the physiological parameters as the transmitting frequency varies. More precisely, by using two FMCW radars, operating below 10 GHz and at millimeter wave (mmWave), we applied four DC offset calibration methods to the baseband radar signals originated by the cardiopulmonary activities. We experimentally determined the accuracy of the methods by measuring the respiration and the heart rates of different subjects in an office setting. It was found that the linear demodulation outperforms the other methods if operating below 10 GHz while the geometric fitting provides the best results at mmWave.

Keywords: DC offset calibration; Doppler; FMCW; heart rate; mmWave; phase demodulation; remote radar sensing; respiration rate; sub-10 GHz radar; vital signs monitoring.

MeSH terms

  • Algorithms
  • Heart Rate / physiology
  • Humans
  • Monitoring, Physiologic / methods
  • Radar*
  • Respiration
  • Signal Processing, Computer-Assisted*
  • Vital Signs

Grants and funding

The work of M.M. and S.L. was funded by Programma Operazione Nazionale e Innovazione 2014-2020, Fondo Sociale Europeo, Azione 1.2 “Attrazione e Mobilità Internazionale dei Ricercatori”-CUP: H24I19000410005.