International acknowledgement: Luca Carmisciano, student of the Italian national PhD in AI, co-supervised by L'EMbeDS members, receives the Best Paper Award at the 4th IEEE International Conference on ICT Solutions for eHealth in Paris
Luca Carmisciano, a medical resident at the University of Pisa, and a second-year student of the Italian National PhD in AI, co-supervised by members of the L’EMbeDS Department of Excellence (Francesca Chiaromonte and Andrea Vandin) at the Scuola Superiore Sant'Anna, CNR Pisa (Franca Delmastro) and IBM Research Dublin (Tobia Boschi), recieved the Best Paper Award at the 4th IEEE International Conference on ICT Solutions for eHealth held in Paris from 26 to 29 June, 2024.
The conference focused on interdisciplinary solutions for eHealth, a topic of great relevance that is attracting increasing interest from interdisciplinary research groups. In line with the spirit of the conference, this work involved both academic and industrial researchers from medical, computational, and statistical backgrounds.
The paper titled “Investigating Functional Data Analysis for Wearable Physiological Sensor Data in Stress Evaluation”, co-authored by Carmisciano and his co-supervisors, proposes an innovative approach to the analysis of longitudinal medical data collected using wearable devices, advancing the state of the art in the study of the stress level detection.
For the first time, the paper proposes the use of Functional Data Analysis in this research field. As exemplified in the image below, sequences of point observations (numbers) for a patient are transformed into functions, on which generalizations of analysis techniques typical of machine learning and statistical learning are applied. This methodology offers the advantage of more effectively managing temporal dependencies in the data.
The approach has been validated on a famous public dataset of medical data collected through wearable devices regarding stress detection.
One of the slides used by Luca to present his work at the conference
