Why the study?
Vital signs detection is limited by random body movements, which significantly degrade measurement accuracy.
A novel 77GHz LFMCW radar system using a multi-channel Kalman smoother and regional hidden Markov model can accurately estimate heart and respiration rates with <2 bpm error despite random body movements.
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Enables multi-target vital signs monitoring despite RBMs; leaves open clinical validation before practice adoption.
The technology of vital signs detection has been proven of great use, whereas it is still limited by several challenges. One of the major challenges is the random body movements (RBMs), which significantly degrade the accuracy of the measurement. In this paper, a multi-channel 77GHz linear frequency modulated continuous-wave (LFMCW) radar system is investigated to perform vital signs monitoring on multiple targets with the mitigation of RBMs and a novel vital signs detection scheme is provided for the accurate estimates of the respiration rate (RR) and heart rate (HR). In the proposed scheme, a multi-channel Kalman smoother is firstly proposed to address the outliers in the extracted phase histories from the echoes in the multiple receivers, so that enhanced outlier-robust phase histories are acquired for the subsequent estimates of the RR and HR. Furthermore, a novel regional hidden Markov model is then proposed to carry out accurate estimates of RR and HR by exploiting the underlying slowly-varying characteristics of these vital signs for further mitigation of the effects of RBMs. Experimental results demonstrate that the estimated errors in the proposed scheme are less than 2 beats per minute (bpm) for both RR and HR under normal scenarios with young men in the RBMs environment.
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Wu et al. (2021) studied this question.
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