Parkinson's disease is a prevalent and debilitating neurological disorder, where the severity of motor symptoms are frequently monitored using clinical tests that include a hand pronation and supination task. Objective quantification of motor symptoms in persons with Parkinson's disease and detection of dopamine-induced dyskinesias during treatment is important for the management of the most common symptoms in persons with Parkinson's disease. Thus, the development of a neuromechanical model of rhythmic hand pronation and supination may further our understanding of the mechanisms underlying motor symptoms during rhythmic upper extremity tasks in persons with Parkinson's disease. The aim of this study was to create a model for a rhythmic hand pronation and supination task. This was done to create a simulation of a popular diagnostic task used in determining the severity of motor impairments in persons with Parkinson's disease. It is imperative to understand the neural dynamics as well as the physiological constraints placed on a system such as this in both the creation of a usable model as well as understanding the neuromechanical interactions occurring during this diagnostic task. This model of either normal or slowed, clinical behavior, can then serve as a springboard for the creation of models that characterize disordered motor movement and perhaps even the creation of models that could be incorporated into the diagnostic process.