ADHD Detection Using fMRI and EEG

Attention Deficit Hyperactivity Disorder (ADHD) is a disease which occurs during childhood. Hyperactivity, frequent forgetfulness, impulsivity, risky behaviors are major symptoms of ADHD. It starts from childhood and will have more impact in future. Spotting ADHD in later stage cause major issues to the person to survive in the society and it will be difficult in preventing to make them cure. So, early spotting of ADHD can make awareness among them to go for the treatment from initial stage to make necessary steps to overcome it. The proposed model at first explores the research on Electro Encephalogram (EEG) and Functional Magnetic Resonance Imaging (fMRI) in identifying ADHD. Secondly, it explores different techniques to detect the psychiatric disease i.e., ADHD. Convolutional neural network (CNN) has been used to detect ADHD using fMRI and Random Forest for EEG. The proposed system is a hybrid model (FMRI AND EEG) for detecting the ADHD.