In a new study initiated by the Klinikum Gro\u00dfhadern of LMU Munich, our in-ear sensor technology is used to monitor COVID-19 patients.<\/p>\n<\/div><\/div><\/div><\/div><\/div>
The overall goal of the project is predictive modeling of COVID-19 disease progression using continuously recorded cardio-respiratory parameters and automated pattern recognition by artificial intelligence (AI). The vital signs measured by sensor technology are body temperature and body movement.<\/p>\n
Long-term recording with the cosinuss\u00b0 Two in-ear sensor will be used to model different courses of COVID-19 disease. The aim is to identify potentially serious forms of the disease in order to be able to provide predictive therapy measures, in particular intensive care capacities.<\/p>\n<\/div><\/div><\/div><\/div><\/div>
It is planned to include almost 200 patients with proven SARS-CoV-2 infection, all of whom will be monitored with the cosinuss\u00b0 Two in-ear sensor throughout the entire course of the disease (approx. 8-12 weeks) – including treatment and recovery in the post-stationary period (project arm II).<\/p>\n
Prior to this, a validation of the sensor against the gold standard will take place in the intensive care unit (project arm I). In addition, a further application is planned following the study: Here, our sensor technology<\/a> will be tested for monitoring healthcare workers showing SARS-CoV-2 associated symptoms (project arm III).<\/p>\n The non-interventional observational study will be conducted at the Klinikum Gro\u00dfhadern of the LMU Munich<\/a>, coordinated by PD Dr. R. Schniepp (Department of Neurology) and Dr. Ines Speck (Department of Anesthesiology). The study is funded by own budget.<\/p>\n<\/div><\/div><\/div><\/div><\/div>More information<\/h2><\/div>