Virtual Reality Music-Based Game as a Co-Tool to Diagnose Autism in Young Children

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that impacts various aspects of life, including motor skills, social interactions, and communication, with symptoms that differ widely among individuals. Early diagnosis is critical, especially in young children, as timely intervention can significantly improve outcomes. This paper presents a novel approach utilizing a music-based virtual reality (VR) game to assist therapists in differentiating children with ASD from their typically developing (TD) peers. A classification model was trained using data collected from 21 TD children and 9 children with ASD, focusing on their actions and movements within the game. The model achieved an accuracy of 93% and a sensitivity of 85%, showcasing the potential of VR games in advancing ASD/TD classification and autism screening.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/icrom64545.2024.10903545
Citations
1
Primary Topic
Autism Spectrum Disorder Research
Type
article
Field-Weighted Citation Impact
0.34
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article

Virtual Reality Music-Based Game as a Co-Tool to Diagnose Autism in Young Children

Alireza Taheri, Armin Tandiseh
1 citations
Autism Spectrum Disorder Research
0.34
article

Virtual Reality Music-Based Game as a Co-Tool to Diagnose Autism in Young Children

Alireza Taheri, Armin Tandiseh
article en
1 citations

Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition that impacts various aspects of life, including motor skills, social interactions, and communication, with symptoms that differ widely among individuals. Early diagnosis is critical, especially in young children, as timely intervention can significantly improve outcomes. This paper presents a novel approach utilizing a music-based virtual reality (VR) game to assist therapists in differentiating children with ASD from their typically developing (TD) peers. A classification model was trained using data collected from 21 TD children and 9 children with ASD, focusing on their actions and movements within the game. The model achieved an accuracy of 93% and a sensitivity of 85%, showcasing the potential of VR games in advancing ASD/TD classification and autism screening.

Sharif University of Technology (IR)
Openalex Percentile: Top 37%
Autism Spectrum Disorder Research
0.34
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