A Study on Implicit Learning EEG using Sample Entropy to Further Development for ADHD Therapy

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) is a neurological disorder that affects many people in the world. Many researchers had speculated that behavior therapy could be used to treat people with ADHD. One of the promising behavioral therapy to help patients train their brains to focus, impulse control and executive functions is neurofeedback therapy. Using neurofeedback, therapists can learn how to influence patients’ brain activity by adjusting the training regimen according to the feedback brainwave. According to past research, it was speculated that implicit learning and children with ADHD could have an atypical relationship. The aim of this paper is to analyze brainwave, electroencephalogram signal (EEG), of healthy people while they perform cognitive tasks to identify when a patient achieves an implicit learning event. Once the event is temporally identified, a pattern in the brainwave could be extracted which can potentially help in designing the neurofeedback treatment to help people with ADHD by training the brain to regular evoking the implicit learning brain state.