No Cover Image

Journal article 222 views 19 downloads

Eye movement behavior in a real-world virtual reality task reveals ADHD in children

Liya Merzon, Kati Pettersson, Eeva T. Aronen, Hanna Huhdanpää, Erik Seesjärvi, Linda Henriksson, Joe MacInnes Orcid Logo, Minna Mannerkoski, Emiliano Macaluso, Juha Salmi

Scientific Reports, Volume: 12, Issue: 1

Swansea University Author: Joe MacInnes Orcid Logo

  • 63400.pdf

    PDF | Version of Record

    Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

    Download (1.36MB)

Abstract

Eye 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...

Full description

Published in: Scientific Reports
ISSN: 2045-2322
Published: Springer Science and Business Media LLC
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa63400
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: Eye 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.
College: Faculty of Science and Engineering
Issue: 1