Attention-deficit hyperactivity disorder (ADHD) is one of the most common neuropsychiatric disorders of childhood. Diagnosis of ADHD is based on core symptoms and checklists. However, these are both subjective, which can lead to the problems of overdiagnosis and underdiagnosis. Elevated theta/beta ratio (TBR) of EEG band has been approved by the US Food and Drug Administration as a tool to assist in the diagnosis of ADHD. However, several recent studies have demonstrated that there are no significant differences in TBR between people with and without ADHD. In this study, we attempted to develop a new method for differentiating between male with and without ADHD by analyzing EEG features. Thirty boys with ADHD combined type (aged 8 years 5 months ± 1 year 11 months) and 30 age-matched controls (aged 8 years 5 months ± 1 year 8 months) were enrolled in this study. A classification analysis-based approach comprising training and classification phases was developed for classifying each subject's EEG features as ADHD or non-ADHD. Eight crucial feature descriptors were selected and ranked based on the t test. Compared with TBR in our study, the developed method had a higher area under the curve (87.78%), sensitivity (80.0%), and specificity (80.0%). Our method is more precise than using TBR in the diagnosis of ADHD. This newly developed method is a useful tool in identifying patients with ADHD and might reduce the possibility of overdiagnosis and underdiagnosis.
Keywords: ADHD; feature; male; qEEG; theta/beta ratio.