Interacting with multiple game genres using Motion Onset Visual Evoked Potentials

David Marshall; Ryan Beveridge; Shane Wilson; Damien Coyle

doi:10.1109/CGames.2015.7272957

Interacting with multiple game genres using Motion Onset Visual Evoked Potentials

David Marshall, Ryan Beveridge, Shane Wilson, Damien Coyle

Ulster University

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

6 Citations (SciVal)

Abstract

Motion Onset Visually Evoked Potentials (mVEPs) allow users to interact with technology using non-visually fatiguing stimuli in a Brain Computer Interface (BCI). This study employs mVEP in an onscreen controller and evaluates players’ ability to use mVEP for online gameplay with games from three different genres namely action, puzzle and sports. The onscreen controller consists of five mVEP stimuli that are presented as buttons to allow the participant to choose from five different actions in each game. The performance was assessed based on online BCI accuracy and game score for each game. Results indicate that the players could control the games with an average online accuracy of 71% (5 class classification chance accuracy is 20%). The results also suggest that the use of the mVEP controller with a detailed environment and stimulating feedback in the form of an action game helped to attain the highest online accuracy (75%).

Original language	English
Title of host publication	2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)
Place of Publication	U. S. A.
Publisher	IEEE Computational Intelligence Society
Pages	18-27
Number of pages	10
ISBN (Electronic)	9781467379212
DOIs	https://doi.org/10.1109/CGames.2015.7272957
Publication status	Published - 29 Jul 2015
Event	2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES) - Louisville, Kentucky, USA United States Duration: 27 Jul 2015 → 29 Jul 2015

Conference

Conference	2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)
Country/Territory	USA United States
City	Kentucky
Period	27/07/15 → 29/07/15

Keywords

brain-computer interface
EEG
games
motion onset visual evoked potentials

Access to Document

10.1109/CGames.2015.7272957

Cite this

Interacting with multiple game genres using Motion Onset Visual Evoked Potentials. / Marshall, David; Beveridge, Ryan; Wilson, Shane et al.
2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES). U. S. A.: IEEE Computational Intelligence Society, 2015. p. 18-27.

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Marshall, D, Beveridge, R, Wilson, S & Coyle, D 2015, Interacting with multiple game genres using Motion Onset Visual Evoked Potentials. in 2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES). IEEE Computational Intelligence Society, U. S. A., pp. 18-27, 2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES), Kentucky, USA United States, 27/07/15. https://doi.org/10.1109/CGames.2015.7272957

@inproceedings{330bee5b63d24c3695a8f1887cde1c63,

title = "Interacting with multiple game genres using Motion Onset Visual Evoked Potentials",

abstract = "Motion Onset Visually Evoked Potentials (mVEPs) allow users to interact with technology using non-visually fatiguing stimuli in a Brain Computer Interface (BCI). This study employs mVEP in an onscreen controller and evaluates players{\textquoteright} ability to use mVEP for online gameplay with games from three different genres namely action, puzzle and sports. The onscreen controller consists of five mVEP stimuli that are presented as buttons to allow the participant to choose from five different actions in each game. The performance was assessed based on online BCI accuracy and game score for each game. Results indicate that the players could control the games with an average online accuracy of 71% (5 class classification chance accuracy is 20%). The results also suggest that the use of the mVEP controller with a detailed environment and stimulating feedback in the form of an action game helped to attain the highest online accuracy (75%).",

keywords = "brain-computer interface, EEG, games, motion onset visual evoked potentials",

author = "David Marshall and Ryan Beveridge and Shane Wilson and Damien Coyle",

year = "2015",

month = jul,

day = "29",

doi = "10.1109/CGames.2015.7272957",

language = "English",

pages = "18--27",

booktitle = "2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)",

publisher = "IEEE Computational Intelligence Society",

note = "2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES) ; Conference date: 27-07-2015 Through 29-07-2015",

}

TY - GEN

T1 - Interacting with multiple game genres using Motion Onset Visual Evoked Potentials

AU - Marshall, David

AU - Beveridge, Ryan

AU - Wilson, Shane

AU - Coyle, Damien

PY - 2015/7/29

Y1 - 2015/7/29

N2 - Motion Onset Visually Evoked Potentials (mVEPs) allow users to interact with technology using non-visually fatiguing stimuli in a Brain Computer Interface (BCI). This study employs mVEP in an onscreen controller and evaluates players’ ability to use mVEP for online gameplay with games from three different genres namely action, puzzle and sports. The onscreen controller consists of five mVEP stimuli that are presented as buttons to allow the participant to choose from five different actions in each game. The performance was assessed based on online BCI accuracy and game score for each game. Results indicate that the players could control the games with an average online accuracy of 71% (5 class classification chance accuracy is 20%). The results also suggest that the use of the mVEP controller with a detailed environment and stimulating feedback in the form of an action game helped to attain the highest online accuracy (75%).

AB - Motion Onset Visually Evoked Potentials (mVEPs) allow users to interact with technology using non-visually fatiguing stimuli in a Brain Computer Interface (BCI). This study employs mVEP in an onscreen controller and evaluates players’ ability to use mVEP for online gameplay with games from three different genres namely action, puzzle and sports. The onscreen controller consists of five mVEP stimuli that are presented as buttons to allow the participant to choose from five different actions in each game. The performance was assessed based on online BCI accuracy and game score for each game. Results indicate that the players could control the games with an average online accuracy of 71% (5 class classification chance accuracy is 20%). The results also suggest that the use of the mVEP controller with a detailed environment and stimulating feedback in the form of an action game helped to attain the highest online accuracy (75%).

KW - brain-computer interface

KW - EEG

KW - games

KW - motion onset visual evoked potentials

U2 - 10.1109/CGames.2015.7272957

DO - 10.1109/CGames.2015.7272957

M3 - Chapter in a published conference proceeding

SP - 18

EP - 27

BT - 2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)

PB - IEEE Computational Intelligence Society

CY - U. S. A.

T2 - 2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)

Y2 - 27 July 2015 through 29 July 2015

ER -

Interacting with multiple game genres using Motion Onset Visual Evoked Potentials

Abstract

Conference

Keywords

Access to Document

Fingerprint

Cite this