Objective: Computerized neglect tests could significantly deepen our disorder-specific knowledge by effortlessly providing additional behavioral markers that are hardly or not extractable from existing paper-and-pencil versions. This study investigated how testing format (paper versus digital), and screen size (small, medium, large) affect the Center of cancelation (CoC) in right-hemispheric stroke patients in the Letters and the Bells cancelation task. Our second objective was to determine whether a machine learning approach could reliably classify patients with and without neglect based on their search speed, search distance, and search strategy.
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