COVID-SENSE: Radar-Based Remote Respiratory Disorder Detection in Clinical Environment

The COVID-19 pandemic urgently requires contact-less medical monitoring to prevent human-to-human interactions. Respiratory rate and respiratory irregularity are important indicators to classify the stages of COVID-19. Thus, respiration measurement is essential for the doctors to decide on medical treatment during hospitalization. In this work, the radar-based internet of things (IoT) system was implemented in inpatient ward, and the respiratory disorder assessment algorithm was proposed to help to identify the different COVID-19 stages. Data of COVID-19 patients in different symptoms' stages were collected continuously for one week. The experimental results show the proposed system can accurately detect the real-time respiratory irregularity in a remote and convenient way. The results of detection are also consistent with the diagnosis of clinicians, which indicates the proposed system can provide a safe and reliable way for the daily health monitoring of hospitalized COVID-19 patients.