Contact-free vital sign monitoring, which uses wireless signals for
recognizing human vital signs (i.e, breath and heartbeat), is an attractive
solution to health and security. However, the subject's body movement and the
change in actual environments can result in inaccurate frequency estimation of
heartbeat and respiratory. In this paper, we propose a robust mmWave radar and
camera fusion system for monitoring vital signs, which can perform consistently
well in dynamic scenarios, e.g., when some people move around the subject to be
tracked, or a subject waves his/her arms and marches on the spot. Three major
processing modules are developed in the system, to enable robust sensing.
Firstly, we utilize a camera to assist a mmWave radar to accurately localize
the subjects of interest. Secondly, we exploit the calculated subject position
to form transmitting and receiving beamformers, which can improve the reflected
power from the targets and weaken the impact of dynamic interference. Thirdly,
we propose a weighted multi-channel Variational Mode Decomposition (WMC-VMD)
algorithm to separate the weak vital sign signals from the dynamic ones due to
subject's body movement. Experimental results show that, the 90th
percentile errors in respiration rate (RR) and heartbeat rate (HR) are less
than 0.5 RPM (respirations per minute) and 6 BPM (beats per minute),
respectively