Handwriting as a Tool for Monitoring the Progression of Neurodegenerative Diseases
摘要
As the global population ages, neurodegenerative diseases like Alzheimer (AD) and Parkinson (PD) are increasing, necessitating better remote monitoring methods. Here we explore quantitative analysis of handwriting skills as a tool for predicting cognitive impairment and thus, monitoring the degeneration of the disease. A novel probabilistic model using bump functions was developed to analyze handwriting’s spatial organization, capturing their complexity and variability. The key findings are that AD subjects tend to organize the same dictated text into more rows than PD, and the rows’ average tilt and height are predictive of cognitive functions. This approach offers a non-invasive, accessible, and effective solution for monitoring of neurodegenerative diseases.