Real-Time Medical Radar-based Vital Sign Monitoring System Implemented with Signal Quality Classification Algorithm

Abstract

Owing to the Covid-19 epidemic, medical radar has become a potential non-contact method in patient monitoring. However, this radar type is sensitive to external interference. The output signal obtained by the radar when a patient makes random body movements can significantly reduce the accuracy of vital sign detection algorithms. In addition, algorithms should be developed for actual application. In this study, we present an improved model of the 24-GHz radar signal quality classification system and a technique to enhance the resolution of respiration rate (RR) and heart rate (HR) for short time interval signals. Moreover, a complete system including signal quality assessment and vital signs extraction is implemented in real time on the Lab-VIEW software. The signal quality classification was evaluated on the measured signals of 10 healthy subjects. Accordingly, the obtained results indicate that with specific features, the accuracy of signal quality classification reaches 89.8%-100% while real-time RR and HR extraction results demonstrate significant agreement between radar measurement and the contact-type sensor.