Visual exploration of objects and scenes in patients with age-related macular degeneration

Thibaut, Miguel; Delerue, Céline; Boucart, Muriel; Tran, Thi Ha Chau

doi:10.1016/j.jfo.2015.08.010

Cited by 26 publications

(32 citation statements)

References 23 publications

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“…In scene-categorization tasks, AMD patients demonstrated good performance (above 75%), yet below the performance of healthy participants (Tran, Rambaud, Despretz, & Boucart, 2010). In an object and scene identification task (Thibaut, Delerue, Boucart, & Tran, 2016), AMD patients exhibited reduced performances, as well as an increased number of saccades and shorter fixation duration.…”

Section: Inference From Gaze Datamentioning

confidence: 84%

Predicting artificial visual field losses: A gaze-based inference study

et al. 2019

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Visual field defects are a worldwide concern, and the proportion of the population experiencing vision loss is ever increasing. Macular degeneration and glaucoma are among the four leading causes of permanent vision loss. Identifying and characterizing visual field losses from gaze alone could prove crucial in the future for screening tests, rehabilitation therapies, and monitoring. In this experiment, 54 participants took part in a free-viewing task of visual scenes while experiencing artificial scotomas (central and peripheral) of varying radii in a gaze-contingent paradigm. We studied the importance of a set of gaze features as predictors to best differentiate between artificial scotoma conditions. Linear mixed models were utilized to measure differences between scotoma conditions. Correlation and factorial analyses revealed redundancies in our data. Finally, hidden Markov models and recurrent neural networks were implemented as classifiers in order to measure the predictive usefulness of gaze features. The results show separate saccade direction biases depending on scotoma type. We demonstrate that the saccade relative angle, amplitude, and peak velocity of saccades are the best features on the basis of which to distinguish between artificial scotomas in a free-viewing task. Finally, we discuss the usefulness of our protocol and analyses as a gaze-feature identifier tool that discriminates between artificial scotomas of different types and sizes.

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Section: Inference From Gaze Datamentioning

confidence: 84%

Predicting artificial visual field losses: A gaze-based inference study

et al. 2019

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“…19,36 Yet increased fixation duration is not consistently reported across studies investigating visual search in people with central scotomas, and our study did not find a significant difference in fixation durations between AMD patients and controls. Others 27,37 discuss the increased number of saccades that may be required to attempt to bring a target of interest onto an area of healthy retina. Our results support this idea in part; the visually healthy participants in our study made more saccades per second on average than the patients during their search duration but this was only really apparent after we filtered the data by the quality of the calibration of the eye-tracking experiments.…”

Section: Discussionmentioning

confidence: 99%

“…16,26 More recently, eye movements during a ''real-world'' visual exploration task have been reported to be different in patients with neovascular AMD compared with visually healthy peers. 27 This study, therefore, investigated the primary hypothesis that people with dry AMD perform worse than visually healthy peers on a computer-based surrogate of ''real-world'' search tasks in a prospective case-control study. A secondary aim investigates whether eye movements during the tasks differ in people with dry AMD compared with those without.…”

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confidence: 99%

Searching for Objects in Everyday Scenes: Measuring Performance in People With Dry Age-Related Macular Degeneration

Taylor

Smith

Crabb

2017

Invest. Ophthalmol. Vis. Sci.

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“…In the context of studies with populations suffering from partial loss of vision, such as in age-related macular degeneration (AMD), there is also an unknown degree of error in the calibration. Currently, calibration with AMD patients relies on the assumption that patients use a preferred retinal locus (PRL) (Guez, Le Gargasson, Rigaudiere, & O'Regan, 1993) as an alternative to central fixation during eye-tracker calibration (Seiple, Szlyk, McMahon, Pulido, & Fishman, 2005;Tarita-Nistor, Brent, Steinbach, & González, 2011;Thibaut, Delerue, Boucart, & Tran, 2016). Depending on the size of the scotoma, the use of a PRL will add an absolute error in the gaze estimate (on average around 208, see table 2 in Schuchard, Naseer, de Castro, & Dev, 1999).…”

Section: Discussionmentioning

confidence: 99%

“…Depending on the size of the scotoma, the use of a PRL will add an absolute error in the gaze estimate (on average around 208, see table 2 in Schuchard, Naseer, de Castro, & Dev, 1999). Further, because participants often have multiple PRLs, which might be used interchangeably during calibration and testing (Crossland, Culham, Kabanarou, & Rubin, 2005;Thibaut et al, 2016), the precision in the gaze estimate would be severely compromised. In contrast, the replacement calibration method can be used to better approximate the central gaze position of patients with central visual impairment, maintaining precision in the measurement independent of the position or number of their PRLs.…”

Section: Discussionmentioning

confidence: 99%

A nonvisual eye tracker calibration method for video-based tracking

et al. 2018

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Video-based eye trackers have enabled major advancements in our understanding of eye movements through their ease of use and their non-invasiveness. One necessity to obtain accurate eye recordings using video-based trackers is calibration. The aim of the current study was to determine the feasibility and reliability of alternative calibration methods for scenarios in which the standard visual-calibration is not possible. Fourteen participants were tested using the EyeLink 1000 Plus video-based eye tracker, and each completed the following 5-point calibration methods: 1) standard visual-target calibration, 2) described calibration where participants were provided with verbal instructions about where to direct their eyes (without vision of the screen), 3) proprioceptive calibration where participants were asked to look at their hidden finger, 4) replacement calibration, where the visual calibration was performed by 3 different people; the calibrators were temporary substitutes for the participants. Following calibration, participants performed a simple visually-guided saccade task to 16 randomly presented targets on a grid. We found that precision errors were comparable across the alternative calibration methods. In terms of accuracy, compared to the standard calibration, non-visual calibration methods (described and proprioception) led to significantly larger errors, whilst the replacement calibration method had much smaller errors. In conditions where calibration is not possible, for example when testing blind or visually impaired people who are unable to foveate the calibration targets, we suggest that using a single stand-in to perform the calibration is a simple and easy alternative calibration method, which should only cause a minimal decrease in accuracy.

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Visual exploration of objects and scenes in patients with age-related macular degeneration

Cited by 26 publications

References 23 publications

Predicting artificial visual field losses: A gaze-based inference study

Predicting artificial visual field losses: A gaze-based inference study

Searching for Objects in Everyday Scenes: Measuring Performance in People With Dry Age-Related Macular Degeneration

A nonvisual eye tracker calibration method for video-based tracking

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