A Real-Time Brainwave Based Neuro-Feedback System for Cognitive Enhancement

Abstract

Brain Computer Interface (BCI) provides a pathway to connect the brain to external devices. Neuro-rehabilitation provides advanced means to assist people with movement disorders such as post-stroke patients and those with lost limbs. While much progress has been made in neuro-rehabilitation as assistive devices, few studies had examined mental rehabilitation assisted by BCI such as memory training using neuroenhancement. It should be noted that many patients with physical disabilities also suffer cognitive difficulties. On the other hand, cognitive decline can also be the result of normal aging without brain injury nor diseases. Here, we propose a novel real-time brainwave BCI platform for enhancing human cognitive by designing and employing a personalized neuro-feedback robot. Short-term memory and attention are among the most important cognitive abilities which manifest in many mental diseases. A social robot is integrated into the BCI system to provide feedback based on individual’s brainwaves and memory performance. As a simple scenario of memory task, real-time EEG signals will be monitored during a visual object memory task. Our novel neuro-feedback system has great potential as a neuro-enhancing device for cognitive rehabilitation.