Parkinson's disease is a common neurodegenerative disorder that impairs motor skills. This project aims to develop a novel diagnostic test for early detection of Parkinson's disease by analyzing a subject’s upper extremity motor control with an artificial neural network classifier. Upper extremity motion from both Parkinson’s disease patients and healthy controls will be measured with a field deployable inertial measurement unit during various motor control tasks. An artificial neural network will be trained to classify (diagnose) the subjects as healthy or Parkinson’s disease.