Remote Health Monitoring System for Bedbound Patients

Abstract There are many patients who require continuous monitoring of vital signs and their sleep position such as bedbound patients and hospitalized patients. Also, in some cases, like COVID-19, it is critical for a caregiver to keep a safe distance to the patient. For remote monitoring, radar technologies have been shown to be promising. Thus, in this paper, we present a novel solution for the remote breath and sleep position monitoring by using a multi-input-multi-output (MIMO) radar. Our proposed system could monitor a number of people simultaneously, and therein we use a high-resolution direction of arrival (DOA) detection for finding close targets. Furthermore, the sleep position of each target is determined using a support vector machine (SVM) classifier. The breath analysis involves designing an optimum filter for estimating both the breathing rate and the noiseless breathing waveform. Furthermore, we tested the system by hand-made targets and real human targets. The radar placed in a bedroom environment above a bed where two subjects were sleeping next to each other. For the breathing rate, the accuracy of the radar is more than 97% for human subjects compared with a reference sensor. Also, the sleep position correct detection is more than 83%.