Remote vital signs monitoring using a mm-wave FMCW radar

Abstract

A vision on the migration from contact standard health monitoring measurement devices to non-contact measurement technologies has gained a tremendous attention in literature and in industry. A promising method for realizing the remote measurement of vital signs is using electromagnetic radars such as frequency modulated continuous wave (FMCW) radars. However, using these radars has challenges to precisely acquire the respiration and heart rates. A solution for higher accurate measurement of the vital signs can be the use of mm-wave frequencies, which gives a high-resolution sensing of displacements in an environment in the order of sub-mm changes. On the other hand, being in mm-wave bands increases both hardware and signal processing designs and implementations.

In this work, a mm-wave radar is used to monitor the breathing and the heart rates as well as their waveforms for further clinical diagnostics. To that end, we established a complete analysis of the FMCW radars principles by considering hardware impairments. The analysis considers the effect of antenna coupling, RF cross-talk, stationary clutters, phase noise, IQ imbalances, and the thermal noise. Also, the effect of the individual hardware imperfections on the phase quality is shown by simulations and experiments. The simulations are carried out with a Matlab Simulink model. For the experiments, Texas Instruments (TI) mm-wave FMCW radars have been used.

To earn insight into vital signs monitoring, different experiments are designed. In the experiments, the effect of the thermal instability of the RF parts on the phase is shown. In addition, to mimic the behaviour of the chest vibration due to respiration and the heartbeats, a two-pendulum system is designed and tested. Particularly, the pendulum system performance in terms of vibration frequency estimations of the two pendulums versus distance is then measured. In the simulations, the system performance is obtained for different signal to noise ratios (SNR) and different phase noise levels, as well as different stationary clutters.

Finally, to test the TI sensors for different directions to the subjects, Hexoskin smart garment is used as a reference sensor, which is a reliable commercial product. Our results show great system improvement in terms of accuracy of the vital signs detection in comparison to other similar research. For different sleep positions, the accuracy of HR and BR are greater than 94\% and 96\%, respectively. In addition to detecting the vital rates, we have shown that their waveforms can also be reconstructed by using an adaptive optimum filter.