Optimizing Patient–Ventilator Synchrony Utilizing Radar-Based Respiratory Features for Monitoring COVID-19 Patients

During this COVID-19 pandemic time, an unprecedented number of patients with severe respiratory illness require intensive care units (ICUs) under mechanical ventilation (MV) for sustaining life. Patient–ventilator asynchrony (PVA) is very common, and it occurs due to the mismatch between normal variability patients’ breathing patterns ventilator parameters. Asynchronies during invasive are causing discomfort, fatigue, anxiety, neurovascular nerve damage, mortality. However, currently, only way detect through visual inspections by healthcare professionals adjust manually. In article, we propose opinion on conceptual framework a system composed radio frequency (RF)-based noncontact life-sensing technology that can extract different features unobtrusively continuously reduce patient–ventilator asynchrony. After extracting from radar data, provide optimally supplemental oxygen adjusting function existing ventilator. This will sufferings mortalities, as well less stress emergency nurses doctors handle more effectively.