Attention deficit hyperactivity disorder (Adhd) detection methods

Abstract

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.