Cognitive Fingerprinting of Attention-Deficit/Hyperactivity Disorder Subtypes via Artificial Intelligence-Driven Virtual Reality

Abstract

Background:

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurodevelopmental disorders, defined by persistent patterns of inattention, hyperactivity, and/or impulsivity that impair academic, social, and occupational functioning across the lifespan. Affecting approximately 5% of children and adolescents worldwide, ADHD frequently persists into adulthood, contributing to long-term psychosocial difficulties.

Objective:

To outline the limitations of current ADHD diagnostic approaches and highlight how immersive virtual reality (VR) may strengthen ecological relevance, subtype differentiation, and contextual sensitivity.

Methods:

We reviewed the shortcomings of existing diagnostic tools, including their restricted ecological validity and limited ability to capture real-world attentional demands. We then examined immersive VR as a platform capable of standardized, realistic testing environments and simultaneous acquisition of multimodal behavioral and physiological data.

Results:

Evidence suggests that VR-based assessments can enhance the precision of ADHD subtype profiling, support individualized behavioral characterization, and overcome several constraints of traditional diagnostic methods. Common VR paradigms and prior examples of VR-based diagnostic platforms are summarized.

Conclusion:

Immersive VR offers a promising approach for advancing ADHD assessment by improving ecological validity, enabling objective multimodal measurement, and supporting more personalized subtype differentiation. Further research may refine its integration into clinical workflows.