Eye gaze tracking is increasingly popular due to improved technology and availability. However, in assistive device control, eye gaze tracking is often limited to discrete control inputs. In this paper, we present a method for collecting both reactionary and control eye gaze signals to build an individualized characterization for eye gaze interface use. Results from a study conducted with motor-impaired participants are presented, offering insights into maximizing the potential of eye gaze for assistive device control. These findings can inform the development of continuous control paradigms using eye gaze.