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How Free-Viewing Eye Movements Can Be Used to Detect the Presence of Visual Field Defects in Glaucoma Patients

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Purpose: There is a need for more intuitive perimetric screening methods, which can also be performed by elderly people and children currently unable to perform standard automated perimetry (SAP). Ideally,… Click to show full abstract

Purpose: There is a need for more intuitive perimetric screening methods, which can also be performed by elderly people and children currently unable to perform standard automated perimetry (SAP). Ideally, these methods should also be easier to administer, such that they may be used outside of a regular clinical environment. We evaluated the suitability of various methodological and analytical approaches for detecting and localizing VFD in glaucoma patients, based on eye movement recordings. Methods: The present study consisted of two experiments. In experiment 1, we collected data from 20 glaucoma patients and 20 age-matched controls, who monocularly viewed 28 1-min video clips while their eyes were being tracked. In experiment 2, we re-analyzed a published dataset, that contained data of 44 glaucoma patients and 32 age-matched controls who had binocularly viewed three longer-duration (3, 5, and 7 min) video clips. For both experiments, we first examined if the two groups differed in the basic properties of their fixations and saccades. In addition, we computed the viewing priority (VP) of each participant. Following a previously reported approach, for each participant, we mapped their fixation locations and used kernel Principal Component Analysis (kPCA) to distinguish patients from controls. Finally, we attempted to reconstruct the location of a patient's VFD by mapping the relative fixation frequency and the VP across their visual field. Results: We found direction dependent saccade amplitudes in glaucoma patients that often differed from those of the controls. Moreover, the kPCA indicated that the fixation maps of the two groups separated into two clusters based on the first two principal components. On average, glaucoma patients had a significantly lower VP than the controls, with this decrease depending on the specific video viewed. Conclusions: It is possible to detect the presence of VFD in glaucoma patients based on their gaze behavior made during video viewing. While this corroborates earlier conclusions, we show that it requires participants to view the videos monocularly. Nevertheless, we could not reconstruct the VFD with any of the evaluated methods, possibly due to compensatory eye movements made by the glaucoma patients.

Keywords: eye movements; detect presence; visual field; glaucoma; glaucoma patients

Journal Title: Frontiers in Medicine
Year Published: 2021

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