Joint analysis of spatial and gaze trajectories for the early diagnosis of Alzheimer’s disease – ACTSOMA
Alzheimer’s disease (AD) is the most common major neurodegenerative dementia type. Current state-of-the-art diagnostic measures of AD are invasive (cerebro-spinal fluid analysis), expensive (neuroimaging) and time-consuming (neuropsychological assessment). By contrast, AD cognitive fingerprints based on gaze behavior and spatial abilities are widely overlooked, and yet inexpensive, non-invasive, and easy to implement. In this project we first propose to jointly record the eye movements and spatial trajectories of controls and patients at different clinical stages performing well-established navigation tasks . Then, we will jointly analyse these trajectories using statistical modelling and machine learning to capture reliable fingerprints for the different stages of AD. This work will help the neurologists to predict, detect and quantify the disease, which will improve the quality of care of patients.
Project coordination
Antoine COUTROT (UMR 5205 - LABORATOIRE D'INFORMATIQUE EN IMAGE ET SYSTEMES D'INFORMATION)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partner
University of East Anglia, Norwich Medical School
CRNL Centre de Recherche en Neurosciences de Lyon
LIRIS UMR 5205 - LABORATOIRE D'INFORMATIQUE EN IMAGE ET SYSTEMES D'INFORMATION
Help of the ANR 297,949 euros
Beginning and duration of the scientific project:
January 2024
- 42 Months