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Ewa Niechwiej-Szwedo, Dave Gonzalez; Fixation stability during the performance of a high-precision manipulation task. Journal of Vision 2016;16(12):119. doi: 10.1167/16.12.119.
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Numerous studies have shown a stereotypical hand-eye temporal coordination pattern during the performance of reaching and grasping movements. Typically the eyes fixate on the object prior to the initiation of hand movement, which provides high acuity information about the object, such as its shape, orientation or material properties. The information extracted while fixating on the object is important for programming grip aperture and grasp forces, contributing to efficient execution of manipulation tasks. However, every attempt at steady fixation consists of small involuntary eye movements: microsaccades, ocular drift, and tremor. Fixation stability, quantified using bivariate contour elliptical area (BCEA), is reduced during monocular compared to binocular viewing during a visual fixation task (Gonzalez et al 2012). Since grasping is also disrupted during monocular viewing, in this study we examined fixation stability during the performance of a high-precision manual task. Fifteen visually-normal adults grasped a small bead, and placed it on a vertical needle while their eye movements were recorded binocularly. BCEA was calculated for fixations on the bead and the needle, in each viewing condition. In contrast to the hypothesis, fixation stability was significantly better with the dominant eye when fixating on the bead during monocular viewing while there was no difference between the binocular and non-dominant eye viewing conditions. A correlation analysis between BCEA and the performance of grasping and placement tasks showed that better fixation stability was associated with a significantly shorter duration of the grasping and placement actions during monocular viewing. These results indicate that fixation stability contributes to the performance of high-precision manipulation tasks when binocular vision is removed.
Meeting abstract presented at VSS 2016
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