Thesis Project Form

Home-based monitoring systems are increasingly adopted to support long-term rehabilitation and patient follow-up, especially in cognitive and neurorehabilitation contexts. These systems often combine interactive platforms for cognitive training—such as tablet-based applications—with remote data collection and clinician monitoring.
While tablet-based cognitive training enables structured therapeutic exercises, it provides limited information about the physiological state, engagement level, and daily-life context of the patient. Wearable sensors, including smartwatches and pulse oximeters, can complement these systems by continuously collecting physiological and activity-related data in naturalistic home environments.
This thesis aims to evaluate both the technical feasibility and the potential added value of wearable sensor data for into a home-based rehabilitation monitoring system.

The main objective of this thesis is to design and validate an architectural solution for integrating wearable sensors into an existing home monitoring system that includes a tablet-based cognitive training module. More specifically, the activities will include:
Review and selection of wearable sensors relevant for home monitoring scenarios. Design and implementation of the communication interface between wearable devices and the system. Integration of physiological and behavioral metrics into the system’s data infrastructure
Development of a visualization dashboard for monitoring and analyzing the collected data. Evaluation of the usability of the new version of the system

The student will acquire knowledge and skills in:
- signal processing techniques
- management and integration of wearable sensing technologies
- design and development of communication protocols
- mobile and backend software integration
- data analysis and visualization of multimodal datasets