Evaluating sub-types of attention deficit hyperactivity disorder with nonlinear analysis of eeg

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders of childhood. ADHD is categorized into three groups according to clinical symptoms: predominantly inattentive subtype (ADHD-I), predominantly hyperactive-impulsive subtype (ADHD-HI) and combined subtype that combines features of both the other types (ADHD-C). A total of 40 children; 14 control group, and 26 ADHD group (9 with ADHD-DE, 6 with ADHD-HI and 11 with ADHD-C type) were included in the study. This study investigates the nonlinear features of EEG signals regarding ADHD subtypes while performing an auditory oddball task. Lempel-Ziv Complexity (LZC) values of control group were significantly higher than all ADHD subtypes. Fractal dimension (FD) measures showed there was a significant difference between the control group and ADHD-C and ADHD-I groups, but no significant difference was observed with the ADHD-HI group. FD and LZC values did not differ significantly in ADHD subtypes. The results show that EEG complexity is reduced in ADHD. ADHD subtypes did not differ significantly from another in EEG nonlinear analysis during an executive task that supports the subtypes are variants of the same condition. © 2021 IEEE.