An Approach to Measure and Improve the Cognitive Capability of ADHD Affected Children Through EEG Signals

Abstract

Attention Deficit Hyperactivity disorder (ADHD) is a common mental disorder that begins in childhood and can continue through adolescence and adulthood. It makes it hard for a child to focus and pay attention. The present work is mainly designed to predict the probable region of brain that shows abnormality due to ADHD syndrome. EEG data of non – ADHD and ADHD study participants of age group 4-17 years has been collected following a protocol which contains 4 events. Eyes close, Eyes open, Visual Cue and Motor activity. Single map analysis and Frequency map analysis is performed. Comparative analysis is carried out between the non – ADHD and ADHD paricipants.3-D plotting of the EEG signals is performed for ease of visualization. Neural network algorithm is used to distinguish between non – ADHD and ADHD participants for the same task performed. Higher power and higher standard deviation is found in the ADHD patients when eyes closed, eyes open and in motor activity, which is an indication of hyper active nature. However, in the non – ADHD participants, all the parameters show significantly lower values. The proposed work can be used for assessment of learning capability of ADHD affected children and based on which, new methodology or techniques of teaching can be adopted to enhance their learning capability.