Parkinson’s disease (PD) is a neurodegenerative condition with neuronal cell death in the substantia nigra and striatal dopamine deficiency that produces slowness, stiffness, tremor, shuffling gait and postural instability. More than 1 million people in North America are affected by PD resulting in balance problems and falls. It is observed that postural instability and gait problems become resistant to pharmacologic therapy as the disease progresses. Furthermore, studies suggest that postural sway abnormalities are worsened by levodopa, the mainstay of therapy for PD. This paper presents a classification of postural balance test data using Support Vector Machines (SVM) to identify the effect of medicine (levodopa) as well as dyskinesia. It is demonstrated that SVM is a useful tool and can complement the widely accepted (but very resource intensive) Unified Parkinson’s Disease Rating Scale (UPDRS).

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