Sadeghmousavi, Mostafa

AbstractPurpose: Evaluation of an adjustable chin rest apparatus for visual field machine.Methods: The HFA 60‐4 visual field test was performed in the primary position and then repeated in the optimum head turn angle using an adjustable chin rest to maximize a visual field for each subject. The optimum head turn angle was calculated using a 3D face model. A 3D model of the face of the subjects was reconstructed using a single facial photo and a Convolutional Neural Networks (CNN), which is a deep learning algorithm. The angles between visual axis and all points around it on the face surface were calculated and the points on the 3D face model with the angle less than 60 degrees was used to predict the optimal head turn angle. A chin rest apparatus for a visual field system was made by 3D printing. The chin rest apparatus includes a moveable chin rest insert coupled to the base and configured to be adjusted to one of a plurality of head turn angles.Results: Three eyes from three healthy subjects (2 female and 1 male) with the mean age of 27.33, CI: 7.37 were enrolled. The visual field defects cause by the facial contour of the subject was decreased by turning the subject's head relative to a vertical axis away from (nasally) the eye being tested using a visual field system with the adaptive chin rest. The mean threshold of the visual field tests of all eyes in the primary angle and optimized angle was 1496, CI: 380.22 and 1567.67, CI: 295.37 respectively. Mean of the degree of head turn to maximize the visual field for all individuals was 6.67 degrees, CI: 2.88.Conclusions: The described adaptive chin rest can be used to position a subject's head at an optimal head turn angle that minimizes the visual field defects caused by the facial contours and maximizes the measured visual field of the subject. This technology can be used in far peripheral visual field tests for early detection of glaucoma as well as accurate follow up of disease progression.