A gesture recognition device with visual feedback based on capacitive proximity sensing

In this thesis, a novel gesture recognition device - called Rainbowfish - with visual feedback is presented. Rainbowfish is able to recognize objects like a human hand with its sensors. A software running on the computer evaluates the provided sensor data and triggers lighting animations on Rainbowfish's surface. This visual feedback facilitates a closer interaction between the device and the user if no additional feedback like a graphical user interface is provided. An evaluation shows that the system can raise the usability of gesture recognition applications based on capacitive proximity sensors. Especially in cases when the user experiences usage problems, the feedback, as the defining factor, decreases the estrangement between the user and the device. The user study reveals that the visual feedback has a positive impact on a user's intrinsic motivation, encouraging the user to keep on using the application.