Neurophysiological Characterization of ADHD in Children Using EEG Signals: A Machine Learning Approach to Executive Function Networks

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder whose clinical assessment relies mainly on behavioral and neuropsychological evaluation. This study evaluates a subject-wise machine learning framework for distinguishing children with ADHD from healthy controls using multichannel EEG-derived features. The public dataset comprised 121 participants (61 ADHD and 60 controls), with 19-channel EEG recordings sampled at 128 Hz. Signals were segmented into 4-s…

via https://pubmed.ncbi.nlm.nih.gov/42740304/?utm_source=Other&utm_medium=rss&utm_campaign=None&utm_content=1lqZ3NPYysePVKsoyz66mDSgu4veDGJwnUBS47TBQPoOuNZY5J&fc=None&ff=20260924011006&v=2.20.1


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