Project OverviewNeurEYE is an interdisciplinary venture aimed at developing and clinically validating an automated system for assessing functional limitations in people with neurological conditions (Parkinson's disease, multiple sclerosis, Alzheimer's, stroke, cerebral palsy, etc.).
The system relies on multi-modal data collected through inertial, audio-video, depth, and wearable sensors while users perform Activities of Daily Living (ADLs).
The ultimate goal is to provide comprehensive clinical reports that support healthcare professionals in diagnosis, treatment and rehabilitation.PhD FocusThe PhD will design, implement and validate algorithmic solutions to automatically evaluate functional limitations, ensuring objective clinical validity and eliminating evaluator bias.
The research will explore state-of-the-art deep learning architectures, generative models and multimodal integration under scarce data constraints, with an emphasis on methods that can be transferred to real clinical settings.Research TasksStudy, implement and improve robust deep-learning architectures for behavior analysis using RGB-D images and biometric sensors (accelerometer bracelets).
Develop methods to extract quality parameters from monitored users during ADLs and relate them to neurological condition and disease evolution.Create and maintain image and multimodal databases for the target environments.Evaluate algorithmic proposals on the available databases.Integrate and assess the developed systems within clinical validation tools.Generate demonstrators to facilitate technology