VR-Based ADHD Diagnosis Using AI and Questionnaire Data
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Solution Overview
Problem
Current ADHD diagnosis methods for children and adolescents are inefficient due to social indifference, lack of awareness, and the time-consuming nature of traditional testing, leading to delayed or improper recognition of symptoms, and variability in classification depending on clinicians.
Innovation Solution
A method and system utilizing virtual reality and artificial intelligence to diagnose ADHD, which includes loading questionnaire data, training AI using supervised and unsupervised learning, storing measurement data from VR interactions, and classifying ADHD types based on digitized evaluation factors from VR games like automobile assembly and baseball hitter games.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional testing and questionnaire methods are used for ADHD diagnosis, then clinicians can evaluate patients, but the process takes a long time and reduces productivity
Solution Approach 1:
The patent replaces the manual clinical assessment process with an automated VR-based testing system. The system uses virtual reality environments to objectively measure ADHD symptoms through standardized tasks, eliminating the time-consuming nature of traditional clinician-administered questionnaires and observations while maintaining diagnostic accuracy.
Solution Approach 2:
The patent transforms subjective clinical evaluations into objective quantitative measurements by tracking VR interaction parameters such as response time, task completion accuracy, and behavioral patterns in virtual environments. This parameter transformation enables automated analysis and significantly reduces diagnosis time.
2Reliability
If traditional clinical diagnosis methods are used, then patients can receive treatment, but classification varies depending on the clinician
Solution Approach 1:
The patent implements a standardized VR-based assessment platform that can be uniformly applied across different clinical settings and by different clinicians. The system uses consistent algorithms and measurement protocols to classify ADHD symptoms, ensuring that the same patient would receive the same diagnosis regardless of which clinician administers the test, thereby eliminating inter-rater variability.
3Measurement precision
If more clinicians visit psychiatric departments for ADHD diagnosis, then better recognition of symptoms can be achieved, but the departments are already overloaded
Solution Approach 1:
The patent implements preliminary automated screening and assessment through VR tasks that can be completed before clinician consultation. The system pre-evaluates patients using objective measures of attention, impulse control, and hyperactivity, allowing clinicians to focus their expertise on cases that require nuanced judgment rather than spending time on routine assessments.
Data Source
AI summary
The present invention relates to a attention deficit hyperactivity disorder psychological test diagnosis method based on virtual reality and artificial intelligence, and a system for implementing same, the method comprising the steps of: loading a plurality of pieces of personal questionnaire data; training AI on the basis of the personal questionnaire data; storing measurement data acquired when a person to be tested uses VR content for diagnosis; classifying attention deficit hyperactivity disorder (ADHD) classes by using the AI on the basis of the measurement data.