Abstract

Introduction: After a stroke, individuals commonly experience visual problems and impaired cognitive function, which can significantly impact their daily lives. In addition to visual neglect and hemianopia, stroke survivors often have difficulties with visual search tasks. Researchers are increasingly interested in using eye tracking technology to study cognitive processing and determine whether eye tracking metrics can be used to screen and assess cognitive impairment in patients with neurological disorders. As such, assessing these areas and understanding their relationship is crucial for effective stroke rehabilitation. Methods: We enrolled 60 stroke patients in this study and evaluated their eye tracking performance and cognitive function through a series of tests. Subsequently, we divided the subjects into two groups based on their scores on the HK-MoCA test, with scores below 21 out of 30 indicating cognitive impairment. We then compared the eye tracking metrics between the two groups and identified any significant differences that existed. Spearman correlation analysis was conducted to explore the relationship between clinical test scores and eye tracking metrics. Moreover, we employed a Mann-Whitney U test to compare eye tracking metrics between groups with and without cognitive impairment. Results: Our results revealed significant correlations between various eye tracking metrics and cognitive tests (p ≤ 0.001–0.041). Furthermore, the group without cognitive impairment demonstrated higher saccade velocity, gaze path velocity, and shorter time to target than the group with cognitive impairment (p ≤ 0.001–0.040). Receiver operating characteristic curve analyses were performed, and the optimal cut-off values for gaze path velocity and saccade velocity were 329.665 (px/s) (sensitivity = 0.80, specificity = 0.533) and 2.150 (px/ms) (sensitivity = 0.733, specificity = 0.633), respectively. Conclusions: Our findings indicate a significant correlation between eye tracking metrics and cognitive test scores. Furthermore, the group with cognitive impairment exhibited a significant difference in these metrics, and a cut-off value was identified to predict whether a client was experiencing cognitive impairment.

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