Handwriting Task

Handwriting analysis is emerging as a powerful tool for diagnosing and monitoring neurological conditions, particularly neurodegenerative diseases like Parkinson's and Alzheimer's, and developmental disorders like dysgraphia. Current research focuses on developing objective, quantitative metrics from handwriting data—analyzing speed, pressure, and spatial characteristics—often employing machine learning algorithms like various classifiers and deep learning models for accurate classification and prediction of disease states or severity. These advancements offer the potential for non-invasive, cost-effective, and early detection of neurological disorders, improving diagnosis and potentially facilitating personalized treatment strategies.