Abstract

Attention deficit hyperactivity disorder (ADHD), i.e., children’s hyperactivity, is a common neurodevelopmental disorder in childhood. ADHD is mainly characterized by having difficulty in staying focused, behavioral impulsivity and hyperactivity, and is often accompanied by conduct disorders, learning disabilities or learning difficulties. Traditional therapies generally rely on doctors and parents who can observe and assess patients’ behavior through behavioral scales; however, these therapies are time consuming and ineffective in quantifying behavior. Basing on virtual reality technology, this study integrated multiple sensor technologies, such as eye movement sensors and EEG sensors, and developed an assessment and diagnosis system for ADHD. This system constructed a virtual classroom environment and integrated some tasks, such as audio test, Continuous Performance Task (CPT) and Wisconsin Card Sorting Test (WCST), to judge the subject’s sustained attention, abstract reasoning ability and cognitive ability. Distraction elements were also added to the experiment by analyzing the attention shift of the test taker to diagnose ADHD. Physiological data, such as head movements, eyes movements, and EEG, were used to supplement test results to assess the subject’s sustained attention and attention shift.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.