Date of Award

Fall 11-11-2010

Degree Type


Degree Name

Doctor of Philosophy (PhD)


Computer Science

First Advisor

Dr. Michael Weeks

Second Advisor

Dr. Saeid Belkasim

Third Advisor

Dr. Xiaolin Hu

Fourth Advisor

Dr. Xiaochun He


Today the effective use of computers (e.g. those with Internet browsers and graphical interfaces) involves the use of some sort of cursor control like what a mouse provides. However, a standard mouse is not always the best option for all users. There are currently many devices available to provide alternative computer access. These devices may be divided into categories: brain-computer interfaces (BCI), mouth-based controls, camera-based controls, and head-tilt controls. There is no single solution as each device and application has to be tailored to each user's unique preferences and abilities. Furthermore, each device category has certain strengths and weaknesses that need to be considered when making an effective match between a user and a device. One problem that remains is that these alternative input devices do not perform as well when compared to standard mouse devices. To help with this, assistive user interface techniques can be employed. While research shows that these techniques help, most require that modifications be made to the user interfaces or that a user's intended target be known beforehand by the host computer. In this research, a novel target-agnostic assistive user interface algorithm intended to improve usage performance for both head-operated and standard mouse devices is designed, implemented (as a mouse device driver and in host computer software) and experimentally evaluated. In addition, a new wireless head-operated input device requiring no special host computer hardware, is designed, built and evaluated. It was found that the Virtual Dynamic Tunnel algorithm improved performance for a standard mouse in straight tunnel trials and that nearly 60% of users would be willing to use the head-tilt mouse as a hands-free option for cursor control.