Brain-computer games interfacing with motion-onset visual evoked potentials

Abstract

A brain-computer interface (BCI) measures brain activity and translates this activity into commands for a program to execute. BCIs enable movement-free communication and interaction with technologies. This thesis evaluates the effectiveness and limitations of motion-onset visual evoked potentials (mVEP) based BCI as a control method for brain-computer games interaction. MVEP incorporates neural activity from the dorsal pathway of the visual system which allows more elegant visual stimuli than other types of VEP and has yet to be used in computer games.

This thesis investigates if mVEP can be used as a control method in multiple computer games, what genre of game is best for interaction with mVEP and can we correct problems with existing VEP BCI computer games? Before conducting experiments involving games of different genres an evaluation of the present state-of-the-art BCI games was carried out in an extensive literature survey on BCI games categorised by genre. The literature survey shows that ‘action’ is the most popular genre in BCI games (49% of BCI games) and provides both games developers and BCI experts a set of design and development guidelines for BCI games.

The conclusions of the survey led to the development of three BCI games of different genres namely action, puzzle and sports. The testing of different BCI games using a single paradigm enables thorough assessment of mVEP as a control method. Five mVEP stimuli are presented as buttons to allow the subject to choose from five possible actions in each game. The performance was assessed based on offline and online BCI accuracy and game score. The results indicate that players could control the games with reasonable online accuracy (66% average for 5 class classification, with an average training accuracy of 74%).

The next study intended on improving the initial study’s results by adding the mVEP to an onscreen HUD (Heads up Display), training in the same game environment as the participants are tested within and adding a questionnaire. Results indicate that the players could control the games with an average online accuracy of 71%, a significant improvement from the previous study. After further analysis of recorded data the ideal setup for mVEP games is defined with key specifications indicating between three and four channels is most economical setup without influencing accuracy whilst averaging over three trials (minimises latency in communication). Finally, through the evaluation of a range of the games related surveys, we found that players enjoyed the mVEP puzzle game most, rating it both the most enjoyable and appropriate game with mVEP control. Overall this thesis shows that mVEP can be used in multiple games genres with good accuracy and provides players with an entertaining and novel control method for computer games

Date of Award	Mar 2016
Original language	English
Sponsors	Department for Employment and Learning
Supervisor	Damien Coyle (Supervisor) & Shane Wilson (Supervisor)