Visual pursuit is a key marker of residual consciousness in patients with disorders of consciousness (DOC). Currently, its assessment relies on subjective clinical decisions. In this study, we explore the variability of such clinical assessments, and present an easy-to-use device composed of cameras and video processing algorithms that could help the clinician to improve the detection of visual pursuit in a clinical context. Visual pursuit was assessed by an experienced research neuropsychologist on 31 patients with DOC and on 23 healthy subjects, while the device was used to simultaneously record videos of both one eye and the mirror. These videos were then scored by three researchers: the experienced research neuropsychologist who did the clinical assessment, another experienced research neuropsychologist, and a neurologist. For each video, a consensus was decided between the three persons, and used as the gold standard of the presence or absence of visual pursuit. Almost 10% of the patients were misclassified at the bedside according to their consensus. An automatic classifier analyzed eye and mirror trajectories, and was able to identify patients and healthy subjects with visual pursuit, in total agreement with the consensus on video. In conclusion, our device can be used easily in patients with DOC while respecting the current guidelines of visual pursuit assessment. Our results suggest that our material and our classification method can identify patients with visual pursuit, as well as the three researchers based on video recordings can.
Keywords: Automatic detection; Behavioral assessment; Disorders of consciousness; Minimally conscious state; Visual pursuit.