SEPARATING PARKINSONIAN PATIENTS FROM NORMAL PERSONS USING HANDWRITING FEATURES

Parkinson's disease (PD) is a widespread progressive neural degenerative disease. Patients encounter problems in carrying out ordinary voluntary movements such as gaiting and writing. Effects of tremor, rigidity, and bradykinesia are seen in writing. Since the diagnosis of PD is based on the presence of cardinal symptoms, therefore voluntary movements like writing could be helpful as an indicator in this process. Handwriting analysis can be a suitable method to separate patients from normal individuals. We recorded handwriting data from 17 normal and 13 PD subjects, and then used mathematical analysis in order to extract proper features. At the end of the study, we used these selected features in a classifier. We achieved 93.89% accuracy in the test phase. Hence, this tool may be aid in the diagnosing of both PD and suspected PD individuals in the early stages of the disease.