Handwriting as an objective tool for Parkinson's disease diagnosis.

To date, clinical assessment remains the gold standard in the diagnosis of Parkinson's disease (PD). We sought to identify simple characteristics of handwriting which could accurately differentiate PD patients from healthy controls. Twenty PD patients and 20 matched controls wrote their name and copied an address on a paper affixed to a digitizer. Mean pressure and mean velocity was measured for the entire task and the spatial and temporal characteristics were measured for each stroke. Results of the MANOVAs for the temporal, spatial, and pressure measures (stroke length, width, and height; mean pressure; mean time per stroke; mean velocity), for both the name writing and address copying tasks, showed significant group effects (F(6,32) = 6.72, p < 0.001; F(6,31) = 14.77, p < 0.001, respectively). A discriminant analysis was performed for the two tasks. One discriminant function was found for the group classification of all participants (Wilks' Lambda = 0.305, p < 0.001). Based on this function, 97.5% of participants were correctly classified (100% of the controls and 95% of PD patients). A Kappa value of 0.947 (p < 0.001) was calculated, demonstrating that the group classification did not occur by chance. In this pilot study we identified two simple short and routine writing tasks which differentiate PD patients from healthy controls. These writing tasks have future potential as cost-effective, fast and reliable biomarkers for PD.