EEG(brain-wave) for gaming using Emotiv Insight

Abstract

Technology has improved people's quality of life since the use of modern tools allows industrialists to produce better and higher quality products. Nowadays, several AI algorithms such as machine learning or deep learning are being applied as a tool to solve problems or to make predictions in many different areas.

Using Artificial Intelligence, control mechanisms for video gaming through Brain-Computer Interfacing (BCI) are becoming more feasible. It is amazing if people can control their game characters using only their brain without having to use controllers, keyboards, or any other external devices.

This paper explores the design, implementation and testing of the BCI-compatible game for children with mobility difficulties, especially children with no functional movement of their hands. A series of mini-games, including "flappy bird", "sunny land" and "dash run", have been developed for PC or mobile (android/iOS) by using Unity Engine.

The purpose of this research is to explore ways to use electroencephalography(EEG) brain signals to control the game by using the Emotiv Insight headset. Cortex models are used in Python to read, analyze real-time EEG data, then to extract mental commands and translate them into game commands in C Sharp (C#). EmotivBCI application is being utilized to train mental commands such as PUSH, PULL, LEFT, RIGHT, etc.