Dynamic handwriting analysis for the assessment of neurodegenerative diseases: a pattern recognition perspective.

Neurodegenerative diseases, as for instance Alzheimer's Disease (AD) and Parkinson's Disease (PD), affect the peripheral nervous system, where nerve cells send the messages that control muscles in order to allow movements. Sick neurons cannot control muscles properly. Handwriting involves cognitive planning, coordination and execution abilities. Significant changes in the handwriting performance are a prominent feature of AD and PD. This work addresses the most relevant results obtained in the field of on-line (dynamic) analysis of handwritten trials by AD and PD patients. The survey is made from a pattern recognition point of view, so that different phases are described. Data acquisition deal not only with the device, but also with the handwriting task. Feature extraction can deal with function and parameter features. The classification problem is also discussed along with results already obtained. The paper also highlights the most profitable research direction.