Open AccessAttention Deficit Hyperactivity Disorder (Adhd) Detection Methods
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1050.0782s519
Subject(s) - attention deficit hyperactivity disorder , feature (linguistics) , attention deficit , psychology , attention deficit disorder , artificial intelligence , computer science , machine learning , clinical psychology , psychiatry , linguistics , philosophy
Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common mental-health disorders, affecting around 5%-10% of school-age children. This paper details about various methodologies for detecting and diagnosing the ADHD disease in patients using different soft computing and deep learning techniques. The limitations of advantages of each ADHD method were discussed in detail with its corresponding simulation results. The feature extraction method and its training with classification procedure for each conventional ADHD method were illustrated in detail.