Carl A. Nelson
Date of this Version
Craig, T. L. Interacting with the Human Eye: Gaze Vector Shape Based Recognition and the Design of an Improved Episcleral Venomanometer.
The sense of sight is one of the main outlets to how we interact with the world. Using eye tracking methods, this sensory input channel may also be used as an output channel to provide commands for robots to follow. These gaze-commanded robots could then be used to assist severely mobility-limited individuals in the home or similar environments. This thesis explores the use of visually drawn shapes as the input for robot commands. These commands were recorded using low-cost gaze tracking hardware (Gazepoint GP3 Eye Tracker). The data were then processed using a custom algorithm in MATLAB to detect commands to be passed to two different mobile robots. The ability to use stochastic analysis for path prediction is also explored. Using the techniques and procedures given in this paper, people with limited mobility will be able to input shape commands to have robots react as personal assistants. This research is extensible to gaze-based human-machine interfaces in general for a variety of applications.
In order to better under understand the eye, improvements and retro-fitting of an episcleral venomanometer were conducted. A portable video enabled venomanometer was created to observe vein occlusion and its correlating pressure. This was then improved upon through design iteration. The current issue with measuring is receiving accurate and precise readings of eye parameters due to variations in user technique. Designing improved medical devices for collection of information on ocular health and function will provide better understanding of related medical conditions, including but not limited to, glaucomatous damage.
Advisor: Carl Nelson