The primary Human Computer Interfaces (HCI) today are the keyboard and mouse. These interfaces do not facilitate a fluid flow of thought and intent from the operator to the computer. A computer mouse provides only 2 Degrees of Freedom (2DOF). Touch interfaces also provide 2DOF, but with multiple points, making the touch interface far more expressive. The hand has 6 Degrees of Freedom (6DOF)by itself. Combined with the motion of the fingers, the hand has the potential to represent a vast array of differing gestures. Hand gestures must be captured before they can be used as a HCI. Fortunately, advances in device manufacturing now make it possible to build a complete Inertial Measurement Unit (IMU) the size of a fingernail.

This thesis documents the design and development of a glove out tted with six IMUs. The IMUs are used to track the finger and hand positions. The glove employs a controller board for capturing IMU data and interfacing with the host computer. Python™ software on the host computer captures data from the glove. MATLAB™ is used to perform IMU calculations of the incoming data. The calculated data drives a 3D visualization of the glove rendered in Panda3D™. Future work using the glove would include improved IMU algorithms and development of gesture pattern recognition.