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Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors
EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672363/ https://www.ncbi.nlm.nih.gov/pubmed/26690500 http://dx.doi.org/10.1155/2015/653639 |
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author | Belkacem, Abdelkader Nasreddine Saetia, Supat Zintus-art, Kalanyu Shin, Duk Kambara, Hiroyuki Yoshimura, Natsue Berrached, Nasreddine Koike, Yasuharu |
author_facet | Belkacem, Abdelkader Nasreddine Saetia, Supat Zintus-art, Kalanyu Shin, Duk Kambara, Hiroyuki Yoshimura, Natsue Berrached, Nasreddine Koike, Yasuharu |
author_sort | Belkacem, Abdelkader Nasreddine |
collection | PubMed |
description | EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control. |
format | Online Article Text |
id | pubmed-4672363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-46723632015-12-20 Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors Belkacem, Abdelkader Nasreddine Saetia, Supat Zintus-art, Kalanyu Shin, Duk Kambara, Hiroyuki Yoshimura, Natsue Berrached, Nasreddine Koike, Yasuharu Comput Intell Neurosci Research Article EEG-controlled gaming applications range widely from strictly medical to completely nonmedical applications. Games can provide not only entertainment but also strong motivation for practicing, thereby achieving better control with rehabilitation system. In this paper we present real-time control of video game with eye movements for asynchronous and noninvasive communication system using two temporal EEG sensors. We used wavelets to detect the instance of eye movement and time-series characteristics to distinguish between six classes of eye movement. A control interface was developed to test the proposed algorithm in real-time experiments with opened and closed eyes. Using visual feedback, a mean classification accuracy of 77.3% was obtained for control with six commands. And a mean classification accuracy of 80.2% was obtained using auditory feedback for control with five commands. The algorithm was then applied for controlling direction and speed of character movement in two-dimensional video game. Results showed that the proposed algorithm had an efficient response speed and timing with a bit rate of 30 bits/min, demonstrating its efficacy and robustness in real-time control. Hindawi Publishing Corporation 2015 2015-11-15 /pmc/articles/PMC4672363/ /pubmed/26690500 http://dx.doi.org/10.1155/2015/653639 Text en Copyright © 2015 Abdelkader Nasreddine Belkacem et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Belkacem, Abdelkader Nasreddine Saetia, Supat Zintus-art, Kalanyu Shin, Duk Kambara, Hiroyuki Yoshimura, Natsue Berrached, Nasreddine Koike, Yasuharu Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title | Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title_full | Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title_fullStr | Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title_full_unstemmed | Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title_short | Real-Time Control of a Video Game Using Eye Movements and Two Temporal EEG Sensors |
title_sort | real-time control of a video game using eye movements and two temporal eeg sensors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4672363/ https://www.ncbi.nlm.nih.gov/pubmed/26690500 http://dx.doi.org/10.1155/2015/653639 |
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