Abstract
Quantitative and reliable data are required in the patient rehabilitation process to conduct evaluation and set treatment goals. Different data sensors have been used by researchers in the hand motion analysis with limitations in detail and accuracy. This paper introduces our research in development of a virtual environment for hand motion analysis to evaluate patient’s hand movements. Using uncontacted motion sensors in the developed virtual environment, data for the hand rehabilitation can be accurately obtained. Unity 3D and Leap Motion sensor are used as tools for real-time data capturing of hand movements, which provides graphical information for hand fingers’ positions, angles, grab strength, and gesture types. The designed tool is adaptable to different rehabilitations and user needs.
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