Development of an algorithm for automating gaze data analysis gathered while using upper limb prostheses

Studying gaze behavior (where someone looks) is an emerging area of research particularly in the domain of behavioral psychology. Gaze behavior can, for instance, indicate the amount of attention paid in certain tasks and whether the performance is natural or not. Also, it can indicate the level of competence and experience of the user. Therefore, it has the potential to be used as an evaluative tool in upper limb prosthetic field. In order to obtain informative results from gaze data, the visual scene need to be divided into areas of interests (AOIs) and the time of gaze fixation (eye fixation) has to be calculated. This process is usually completed manually by a rater, who goes through the gaze trial frame by frame, to report at which AOI the gaze is fixated at each frame. Therefore, this process is extremely tedious and is highly subjective, and thus prone to unsystematic error. The aim of this paper is to report the development of an automated algorithm which used to analyze gaze data and obtain an initial indication of its validity and reliability.