Author:
Merzon Liya,Pettersson Kati,Aronen Eeva T.,Huhdanpää Hanna,Seesjärvi Erik,Henriksson Linda,MacInnes W. Joseph,Mannerkoski Minna,Macaluso Emiliano,Salmi Juha
Abstract
AbstractEye movements and other rich data obtained in virtual reality (VR) environments resembling situations where symptoms are manifested could help in the objective detection of various symptoms in clinical conditions. In the present study, 37 children with attention deficit hyperactivity disorder and 36 typically developing controls (9–13 y.o) played a lifelike prospective memory game using head-mounted display with inbuilt 90 Hz eye tracker. Eye movement patterns had prominent group differences, but they were dispersed across the full performance time rather than associated with specific events or stimulus features. A support vector machine classifier trained on eye movement data showed excellent discrimination ability with 0.92 area under curve, which was significantly higher than for task performance measures or for eye movements obtained in a visual search task. We demonstrated that a naturalistic VR task combined with eye tracking allows accurate prediction of attention deficits, paving the way for precision diagnostics.
Funder
Suomen Kulttuurirahasto
Psychiatry Research Foundation, Finland
Instrumentariumin Tiedesäätiö
Academy of Finland
Publisher
Springer Science and Business Media LLC
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