An innovative platform to monitor stroke patients during the first phase of the pandemic from March to April 2020. The project is called Cassia-Cloud Assisted for Health and Safety and was born with the aim of monitoring, measuring and transmitting parameters vital data and data relating to the movement of elderly people, subjects with Parkinson’s, subjects at risk after a transient ischemic attack (Tia) or after minor ischemic cerebral stroke. The preliminary results of the project, still in progress, are presented today at Trieste Next, the scientific research festival, during the meeting “Smart health for the health and well-being of citizens”.
The results of home monitoring of stroke patients were published in Elsevier’s International Journal of Medical Informatics and the project, which develops smart alarms, supports operators and healthcare professionals in remotely monitoring the health of patients with specific needs. Cassia uses an integrated system that associates sensors with a set of artificial intelligence algorithms, the Dss-Decision Support System. Thanks to the data collected, an analysis of the patient’s status is obtained, which is essential to allow the activation of a personal remote assistance service if anomalies are detected. Cassia, explain from the University of Trieste, “represents a contribution to supporting a more autonomous aging and the maintenance of an active life, with less recourse to services and in some cases to institutionalization, increasing the emotional and psychological security of the citizen and of his family members “.
Cassia is co-financed with the European Regional Development Fund of the Regional Operational Program of Friuli Venezia Giulia, is led by the Trieste-based startup Feature Jam and also involves Televita, the Biomedical Engineering group of the Department of Engineering and Architecture of the University of Trieste, ‘Giuliano Isontina University Health Authority (Asugi) and the Science Park Area. Cassia uses an integrated system that associates sensors with a set of artificial intelligence algorithms, the Dss-Decision Support System. Thanks to the data collected, an analysis of the patient’s status is obtained, which is essential to allow the activation of a personal remote assistance service if anomalies are detected.