Dyslexia is a neurodevelopmental reading disability estimated to affect 5–10% of the population. While there is yet no full understanding of the cause of dyslexia, or agreement on its precise definition, it is certain that many individuals suffer persistent problems in learning to read for no apparent reason. Although it is generally agreed that early intervention is the best form of support for children with dyslexia, there is still a lack of efficient and objective means to help identify those at risk during the early years of school. Here we show that it is possible to identify 9–10 year old individuals at risk of persistent reading difficulties by using eye tracking during reading to probe the processes that underlie reading ability. In contrast to current screening methods, which rely on oral or written tests, eye tracking does not depend on the subject to produce some overt verbal response and thus provides a natural means to objectively assess the reading process as it unfolds in real-time. Our study is based on a sample of 97 high-risk subjects with early identified word decoding difficulties and a control group of 88 low-risk subjects. These subjects were selected from a larger population of 2165 school children attending second grade. Using predictive modeling and statistical resampling techniques, we develop classification models from eye tracking records less than one minute in duration and show that the models are able to differentiate high-risk subjects from low-risk subjects with high accuracy. Although dyslexia is fundamentally a language-based learning disability, our results suggest that eye movements in reading can be highly predictive of individual reading ability and that eye tracking can be an efficient means to identify children at risk of long-term reading difficulties.
Background: Visual and oculomotor problems are very common in Parkinson’s disease (PD) and by using eye-tracking such problems could be characterized in more detail. However, eye-tracking is not part of the routine clinical investigation of parkinsonism. Objective: To evaluate gaze stability and pupil size in stable light conditions, as well as eye movements during sustained fixation in a population of PD patients and healthy controls (HC). Methods: In total, 50 PD patients (66% males) with unilateral to mild-to-moderate disease (Hoehn & Yahr 1– 3, Schwab and England 70– 90% ) and 43 HC (37% males) were included in the study. Eye movements were recorded with Tobii Pro Spectrum, a screen-based eye tracker with a sampling rate of 1200 Hz. Logistic regression analysis was applied to investigate the strength of association of eye-movement measures with diagnosis. Results: Median pupil size (OR 0.811; 95% CI 0.666– 0.987; p = 0.037) and longest fixation period (OR 0.798; 95% CI 0.691-0.921; p = 0.002), were the eye-movement parameters that were independently associated with diagnosis, after adjustment for sex (OR 4.35; 95% CI 1.516– 12.483; p = 0.006) and visuospatial/executive score in Montreal Cognitive Assessment (OR 0.422; 95% CI 0.233– 0.764; p = 0.004). The area under the ROC curve was determined to 0.817; 95% (CI) 0.732– 0.901. Conclusion: Eye-tracking based measurements of gaze fixation and pupil reaction may be useful biomarkers of PD diagnosis. However, larger studies of eye-tracking parameters integrated into the screening of patients with suspected PD are necessary, to further investigate and confirm their diagnostic value.
The use of eye tracking to assess reading fluency has been proposed as a novel and efficient screening method for identifying school children with atypical reading development or risk of dyslexia. Currently, however, little is known about the relationship between the predictive outcomes produced by eye tracking screening systems and specialist cognitive assessments. Here we investigate this relationship in the context of a neuropsychological case study involving eight subjects (9–10 years) who were identified as being at risk of dyslexia by an eye tracking screening system. We analyze to what extent these subjects displayed cognitive limitations when assessed with a neuropsychological test battery, and to what extent cognitive difficulties were limited to reading and decoding, or whether they extended to other domains as well. As a group, the subjects performed on average significantly worse in reading and decoding than in other cognitive domains. Five subjects performed more than 1.25 standard deviations below the mean for age. In line with empirical evidence, co-occurring difficulties in the attention domain were also observed in a few struggling readers. Overall, the results support the view that eye tracking can be a useful tool to assess and monitor children’s reading development during the early school years.
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