Document Type



Doctor of Philosophy (PhD)


Electrical Engineering

First Advisor's Name

Armando Barreto

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Gualberto Cremades

Third Advisor's Name

Ophelia Weeks

Fourth Advisor's Name

Jean Andrian

Fifth Advisor's Name

Malek Adjouadi

Date of Defense



This research pursued the conceptualization and real-time verification of a system that allows a computer user to control the cursor of a computer interface without using his/her hands. The target user groups for this system are individuals who are unable to use their hands due to spinal dysfunction or other afflictions, and individuals who must use their hands for higher priority tasks while still requiring interaction with a computer.

The system receives two forms of input from the user: Electromyogram (EMG) signals from muscles in the face and point-of-gaze coordinates produced by an Eye Gaze Tracking (EGT) system. In order to produce reliable cursor control from the two forms of user input, the development of this EMG/EGT system addressed three key requirements: an algorithm was created to accurately translate EMG signals due to facial movements into cursor actions, a separate algorithm was created that recognized an eye gaze fixation and provided an estimate of the associated eye gaze position, and an information fusion protocol was devised to efficiently integrate the outputs of these algorithms.





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