Automated Analysis of Spontaneous Facial Expression Variability in Neurocognitive Disorders During Naturalistic Conversation
These findings suggest that automated facial expression analysis can detect meaningful patterns of emotional variability across neurodegenerative conditions, potentially aiding in diagnostic differentiation. Future research should address current limitations through larger sample sizes, manual validation, and longitudinal designs to track changes over time.
Authors
- Erin Marsh
- Francesca Dino (ORCID: https://orcid.org/0009-0008-9279-5141)
- Peter Pressman (ORCID: https://orcid.org/0000-0003-1760-1286)
- Elliott D. Ross
- Sofia S Messersmith
- Mohammad Mahoor
Institutions
- University of Denver (US)
- Oklahoma City University (US)
- Alzheimer’s Disease Neuroimaging Initiative (US)
- University of Colorado Anschutz Medical Campus (US)
- University of Oklahoma (US)
- University of Colorado Denver (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70857_104472
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00