Handwriting Analysis

Primary Investigator:

Maria Leyba Mesa

About The Study

Our lab is exploring how handwriting can serve as a window into Parkinson’s disease progression. By collecting handwriting samples across a range of tasks, we’re building an AI model trained first on a control population to learn typical handwriting patterns, then applied to individuals with Parkinson’s to better understand how their condition evolves over time.

Interested in being a participant? Send an Email to: mvl16@uakron.edu

Journal Articles

Coming Soon…

Conferences and Poster Presentations

Conference Papers

Leyba-Mesa MV, Barkana BD. A Multimodal Deep Network for Parkinson’s Disease Assessment from Handwriting Kinematics and Visual Task Traces. 4th International Conference on Artificial Intelligence, Blockchain, and Internet of Things, Central Michigan University (CMU), USA, on September 05 – 06, 2026.

Leyba-Mesa MV, Barkana BD. Compact ResNet18 with Test-Time Adaptation: Balancing Accuracy and Latency for Parkinson’s Disease Screening. In2026 12th International Conference on Control, Decision and Information Technologies (CoDIT) 2026 Jul 13 (pp. 349-353). IEEE.

Poster Presentations

Maria V. Leyba Mesa, Buket D. Barkana, PhD, AI-Driven Remote Monitoring of Parkinson’s Disease Through Spatiotemporal Handwriting Analysis. UA Biomedical Engineering Research Day, March 6, 2026

Supporting Researchers

Undergraduate Students: Elijah Ray and Connor Allen