A Two-stage model for inference of target identity during 2D cursor control from natural gaze trajectories

We describe a two stage hidden Markov model based algorithm for inferring target identity in a 2D cursor control task where subjects are instructed to use a joystick to steer a cursor towards a target while avoiding obstacles. The first stage of the model converts a regularly sampled gaze trajectory into a sequence of fixations. The second stage then makes a determination of the end target in the cursor control task based on this sequence of fixations. In contrast to prior work, this two stage model allows for more accurate modelling of the natural eye gaze behavior of subjects, which in turn leads to increased accuracy and speed of target identification. This work demonstrates the importance of accurate gaze modelling, and paves the way for more natural and reliable hybrid Brain Computer Interfaces.