Smart sensors for AI-based management of complex chronic conditions: the TOLIFE project
The TOLIFE project will clinically validate an artificial intelligence (AI) solution to enable optimised and personalised treatment in COPD patients. TOLIFE will process daily life patient data captured by non-invasive smart devices (smartwatch, smartphone, smart mattress cover, smart-shoes, environmental unit) to predict exacerbations, assess the patients’ health outcomes and characterize the patient health status. This talk will focus on description of the non-invasive smart devices selected for use in the TOLIFE clinical studies: smartwatch, smartphone, smartshoes, smart matters cover and environmental unit. The focus is on the data collection architecture, the reasoning behind choosing each specific sensor, the raw data associated with them, and the high-level health-related parameters they capture.
Alessandro Tognetti completed his undergraduate studies in Electronic Engineering and earned his Ph.D. in Bioengineering from the University of Pisa, Italy, in 2001 and 2005, respectively. Presently, he serves as an Associate Professor of bioengineering at the Department of Information Engineering at University of Pisa, where he teaches courses on Biosensors, Bioelectric Phenomena, Bionics Senses, and Modelling Of Multi-physics Phenomena. His research primarily focuses on the development of wearable and non-invasive sensors and systems for biomedical applications, innovative sensor principles, and the modeling of bioelectrical signals. He has actively participated in numerous national and international research projects (over 20 projects) and collaborated extensively with universities, research institutes, and companies across the globe. Currently, he is coordinating the Horizon Europe project TOLIFE as the coordinator.