Using Gesture Recognition to Aid People with Motor Impairments (2011)

Undergraduate: Stephanie Zolayvar

Faculty Advisor: Gary Bishop
Department: Computer Science

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In some cases, individuals with motor impairments must use awkward and effort-intensive switch access interfaces in order to interact with computers. Others must engage in difficult and even painful physical therapy in order to improve motor function. In this work, these two issues were addressed through the development of a software system for recognizing user-trained gestures using the Nintendo Wiimote as an input tool. The system was specifically made to be suited for continuous recognition and rapid training of new gestures. This tool was successfully integrated into prototype versions of a switch access application and a physical therapy game.