COVID-19 pandemic has put a high strain on health systems all across the globe. The virus can cause sudden deterioration in health, making it a challenge to bring patients to the point of care in time. However, critical and continuous health monitoring of the patient is only possible in ICUs. 

Perhaps we could alleviate a lot of burden on ICUs through remote patient monitoring in general hospital wards and even in an out-of-hospital setting. This idea led to the initiation of project M3Infekt that aimed to devise a system and equipment for AI-controlled, decentralized patient monitoring. The acquisition and analysis of relevant medical data from remote settings could help with rapid diagnosis and analysis of the progression of diseases. Through this concept, ICUs would only be required for emergencies. Spirometry is a common method to test and monitor the breathing capabilities of patients.

A part of project M3Infekt included spirometric breath analysis through a MEMS-based ultrasonic system. Researchers created the 3Spiro Rev03 spirometer system to allow continuous monitoring of patients with respiratory conditions in pre-clinical settings. The transportable sensor system was successfully tested on 33 patients in a clinical study at the University Hospital Carl Gustav Carus in Dresden (UKDD). Note that spirometry is a common method to test and monitor breathing in patients. While the feasibility of the 3Spiro Rev03 spirometer system was successfully demonstrated in the tests conducted, scientists are still working on the research and development in sensor optimization, system sizing, and AI algorithms.

Other than the diagnosis of medical conditions such as asthma, COVID-19, and chronic obstructive pulmonary disease (COPD), the ultrasonic system also allows remote analysis of heart rate, ECG, and oxygen saturation. The remote, AI system for remote monitoring of patients with respiratory conditions — especially COVID-19 — sounds promising in resolving one of the biggest health system concerns of the time: overload of hospital capacity.