Machine-based classification of ADHD and nonADHD participants using time/frequency features of event-related neuroelectric activity.

Objective: Attention-deficit/hyperactivity disorder (ADHD) is the most frequent diagnosis among children who are referred to psychiatry departments. Although ADHD was discovered at the beginning of the 20th century, its diagnosis is still confronted with many problems.

Method: A novel classification approach that discriminates ADHD and nonADHD groups over the time-frequency domain features of event-related potential (ERP) recordings that are taken during Stroop task is presented.