This site exploits session and third parties cookies. Pressing on 'Accept' button, you accept cookie usage. For further information click Cookie Policy button

  • Banner

Soluzioni per il monitoraggio clinico di pazienti in isolamento fiduciario a domicilio positivi al test per Covid 19 con associate o meno patologie croniche e situazioni di fragilità

Funded under: Regione Toscana Bando COVID 19

Start date 19 February 2021     End date 18 February 2023

Keywords: Telemedicine, Multipathology, Multiparametric Monitoring, Artificial Intelligence, Decision Support System, Medical Imaging, Biomedical Computing

TiAssisto is a research and development project aiming to design, develop, and validate an innovative and intelligent service platform to improve early diagnosis and the quality of life in patients diagnosed with Covid-19 with or without multiple pathologies and to reduce hospital access.

TiAssisto features telemedicine solutions to enable treatment with high-quality standards based on ICT and artificial intelligence.

Therefore the TiAssisto project will provide:

  • Education and empowerment of patients and caregivers;
  • Integrated services for healthcare professionals, including telemonitoring, signal and image processing, notification systems;
  • Clinical decision support based on artificial intelligence algorithms, knowledge extraction and inference on clinical data;
  • Analysis algorithms to evaluate cardiac and lung echo images acquired directly at the patient's home.

Patients will be randomized into a Tele-Health and a Usual therapy group (TH + U) and into a Usual therapy only group (U). TH + U patients will be followed up at home using the telemedicine platform with the possibility of remote visits and will carry out daily monitoring of vital parameters (blood pressure, oxygen saturation, body weight), using medical devices used by the same patient or by a relative. Automatic notifications will provide appropriate advice to patients and alert physicians.

A virtual panel, accessible via the Web from the doctor's office, will provide real-time situations, thanks to automatic learning methods. All enrolled patients will be checked with a periodic follow-up.

This project will contribute to research and a potential self-financing and sustainable service for the health system.