TY - JOUR AU - Wang, Felix AU - Wolf, Julian AU - Farshad, Mazda AU - Meboldt, Mirko AU - Lohmeyer, Quentin PY - 2021/05/19 Y2 - 2024/03/29 TI - Object-gaze distance: Quantifying near-peripheral gaze behavior in real-world applications JF - Journal of Eye Movement Research JA - JEMR VL - 14 IS - 1 SE - Articles DO - 10.16910/jemr.14.1.5 UR - https://bop.unibe.ch/JEMR/article/view/JEMR.14.1.5 SP - AB - <p>Eye tracking (ET) has shown to reveal the wearer’s cognitive processes using the measurement of the central point of foveal vision. However, traditional ET evaluation methods have not been able to take into account the wearers’ use of the peripheral field of vision. We propose an algorithmic enhancement to a state-of-the-art ET analysis method, the Object-Gaze Distance (OGD), which additionally allows the quantification of near-peripheral gaze behavior in complex real-world environments. The algorithm uses machine learning for area of interest (AOI) detection and computes the minimal 2D Euclidean pixel distance to the gaze point, creating a continuous gaze-based time-series. Based on an evaluation of two AOIs in a real surgical procedure, the results show that a considerable increase of interpretable fixation data from 23.8 % to 78.3 % of AOI <em>screw</em> and from 4.5 % to 67.2 % of AOI <em>screwdriver </em>was achieved, when incorporating the near-peripheral field of vision. Additionally, the evaluation of a <em>multi</em>-OGD time series representation has shown the potential to reveal novel gaze patterns, which may provide a more accurate depiction of human gaze behavior in multi-object environments.</p> ER -