Objective: Few studies have investigated the assessment and functional impact of egocentric and allocentric neglect among stroke patients. This pilot study aimed to determine (1) whether allocentric and egocentric neglect could be dissociated among a sample of stroke patients using eye tracking; (2) the specific patterns of attention associated with each subtype; and (3) the nature of the relationship between neglect subtype and functional outcome. Method: Twenty acute stroke patients were administered neuropsychological assessment batteries, a pencil-and-paper Apples Test to measure neglect subtype, and an adaptation of the Apples Test with an eye tracking measure. To test clinical discriminability, twenty age- and education-matched control participants were administered the eye tracking measure of neglect. Results: The eye tracking measure identified a greater number of individuals as having egocentric and/or allocentric neglect than the pencil-and-paper Apples Test. Classification of neglect subtype based on eye tracking performance was a significant predictor of functional outcome beyond that accounted for by the neuropsychological test performance and Apples Test neglect classification. Preliminary evidence suggests that patients with no neglect symptoms had superior functional outcomes compared with patients with neglect. Patients with combined egocentric and allocentric neglect had poorer functional outcomes than those with either subtype. Functional outcomes of patients with either allocentric or egocentric neglect did not differ significantly. The applications of our findings, to improve neglect detection, are discussed. Conclusion: Results highlight the potential clinical utility of eye tracking for the assessment and identification of neglect subtype among stroke patients to predict functional outcomes. (JINS, 2019, 25, 479–489)

Analysis of eye movements is essential for investigating vestibular disturbances. Video-oculography, although expensive, is a valuable and sensitive tool that allows accurate estimation of eye movements. We describe a simple and inexpensive method of recording as well as analysing eye movements using a commercially available miniature digital video surveillance camera and an MP4 digital media recorder.