ArticleTranslational vision science & technology2022
Developing a Screening Tool for Areas of Abnormal Central Vision Using Visual Stimuli With Natural Scene Statistics.
Article in Translational vision science & technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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3 authors at 2 institutions in 1 country.
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Abstract
purposePrevious studies show that some visual field (VF) defects are detectable from visual search behavior; for example, when watching video. Here, we developed and tested a VF testing approach that measures the number of fixations to find targets on a background with spatial frequency content similar to natural scenes.
methodsTwenty-one older controls and 20 people with glaucoma participated. Participants searched for a Gabor (6 c/°) that appeared in one of 25 possible locations within a 15° (visual angle) 1/f noise background (RMS contrast: 0.20). Procedure performance was assessed by calculating sensitivity and specificity for different combinations of control performance limits (p = 95%, 98%, 99%), number of target locations with fixations outside control performance limits (k = 0 to 25) and number of repeated target presentations (n = 1 to 20).
resultsControls made a median of two to three fixations (twenty-fifth to seventy-fifth percentile: two to four) to locate the target depending on location. A VF was flagged "abnormal" when the number of fixations was greater than the p = 99% for k = 3 or more locations with n = 2 repeated presentations, giving 85% sensitivity and 95.2% specificity. The median test time for controls was 85.71 (twenty-fifth to seventy-fifth percentile: 66.49-113.53) seconds.
conclusionOur prototype test demonstrated effective and efficient screening of abnormal areas in central vision. TRANSLATIONAL RELEVANCE: Visual search behavior can be used to detect central vision loss and may produce results that relate well to performance in natural visual environments.
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