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.