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A software tool has been developed to support the objective diagnosis of patients with Parkinson's Disease (PD). Patients completed hand exercises using a personal computer mouse and data has been gathered for further studies. We have analyzed different parameters and suggest using a particular parameter vector containing median and standard deviation values for tracking the daily changes in PD patients' status. Using the classification abilities of self-organizing feature maps (SOFM) we were able to provide support for the diagnostic process.