A Virtual-Reality System Integrated With Neuro-Behavior Sensing for Attention-Deficit/Hyperactivity Disorder Intelligent Assessment

In this study, an immersive VR classroom embedded with sustained and selective attention tasks was developed in which visual, audio, and visual-audio hybrid distractions, were triggered while attention tasks were conducted. A clinical experiment with 37 ADHD and 31 healthy subjects was performed. Data from BRS was compared with VR task performance and analyzed by rank-sum tests and Pearson Correlation. Results showed that 23 features out of total 28 were related to distinguish the ADHD and non-ADHD children. Several features of task performance and neuro-behavioral measurements were also correlated with features of the BRSs. Additionally, the machine learning models incorporating task performance and neuro-behavior were used to classify ADHD and non-ADHD children. The mean accuracy for the repeated cross-validation reached to 83.2%, which demonstrated a great potential for our system to provide more help for clinicians on assessment of ADHD.
Source: IEE Transactions on Neural Systems and Rehabilitation Engineering - Category: Neuroscience Source Type: research