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M. MacKeben, D.C. Fletcher; Find And Identify: Efficiency Of Scanning Eye Movements In Low Vision Patients . Invest. Ophthalmol. Vis. Sci. 2006;47(13):3690.
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The ability to find and identify objects is of fundamental importance for solving tasks of daily living in patients with low vision. For this purpose, patients have to change their direction of gaze by scanning eye movements until the image of the object of interest falls on an intact area of the retina.
To quantitatively measure search performance psychophysically and to look for correlations with personal or disease characteristics.
Subjects (Ss) were to find and identify single objects a monitor screen, one per trial. There were 32 loci of appearance, and Ss could make any eye movements needed in order to achieve the goal. Correct identification ended each trial and the response latency was measured. Targets were Landolt rings of a diameter that was double the recognition threshold. –– We present data from 114 consecutive patients referred to our low vision service for rehabilitation with a variety of pathologies. The most frequent diagnosis (76/114) was age–related maculopathy. Ages ranged from 19 to 96 years, and visual acuity in the better eye varied from 20/20 to 20/800 (median = 20/80).
Tests took between 55 and 478 seconds (median duration = 125 s). Response latencies varied between 630 ms and 50110 ms (2/3 s to about 50 s, median shortest latency = 1321 ms). The longest latency could be between 1.4 and 31 times longer than the shortest. Visual acuity did not show an appreciable correlation with the median response latency (r^2 = 0.12) or with the sum of all latencies per patient (r^2 = 0.04). The least efficient scanners took up to 16.7 times longer to solve the 32 tasks than the most efficient scanners (sum of all 32 latencies = 400 s vs. 24 s). Scanning efficiency showed only a negligible correlation with patient age (r^2 = 0.044). However, it showed a strong correlation with maximum reading speed achieved at any letter size (MNread, r^2 = 0.66).
We hypothesize that the large differences in search performance between patients and the high correlation with reading could be due to shared resources like oculomotor skills and strategy or agility of transient focal attention.
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