Artificial intelligence based game design and analysis of brain signals
In an era of rapid technological evolution, industries that utilize technology continue to innovate in order to gain a competitive edge. This gaming industry has seen significant development in recent years, with eSports becoming a global phenomenon, and a rise in the availability of novel input dev...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/165866 |
| _version_ | 1811689679233220608 |
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| author | Pang, Kelvin Jun Wei |
| author2 | Smitha Kavallur Pisharath Gopi |
| author_facet | Smitha Kavallur Pisharath Gopi Pang, Kelvin Jun Wei |
| author_sort | Pang, Kelvin Jun Wei |
| collection | NTU |
| description | In an era of rapid technological evolution, industries that utilize technology continue to innovate in order to gain a competitive edge. This gaming industry has seen significant development in recent years, with eSports becoming a global phenomenon, and a rise in the availability of novel input devices that offer unique user experiences.
This project involves the development of an infinite runner Unity 3D game and an Emotiv EPOC+ EEG headset to evaluate the credibility of the provided Emotiv Suite. By using the relatively low-cost portable EEG acquisition device, the project aims to explore on the potential of Brain-Computer Interface (BCI) devices as game controls and provide insights for further research into this field. Additionally, this study seeks to clarify the over reliance on the Emotiv Suite by game development firms, and whether it may lead them in the wrong direction.
This report presents the results of an experiment designed to evaluate the use of an EEG headset in a game designed to evoke emotions in players. Three participants played the developed game while wearing the EEG headset and their emotional responses were measured using both a self-reported Player’s Rating survey and the EEG data. The results showed that the game was not perceived as difficult by the participants and that there was a high level of engagement and immersion in the game. The analysis of the EEG data showed the evoked emotions varied little among the participants and that the game had a significant impact on their stress and relaxation levels. The report concludes by discussing the limitations of the experiment and suggesting future research directions in the field of EEG-base gaming. |
| first_indexed | 2024-10-01T05:51:56Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/165866 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:51:56Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1658662023-04-21T15:39:26Z Artificial intelligence based game design and analysis of brain signals Pang, Kelvin Jun Wei Smitha Kavallur Pisharath Gopi School of Computer Science and Engineering smitha@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Medicine::Biosensors Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics In an era of rapid technological evolution, industries that utilize technology continue to innovate in order to gain a competitive edge. This gaming industry has seen significant development in recent years, with eSports becoming a global phenomenon, and a rise in the availability of novel input devices that offer unique user experiences. This project involves the development of an infinite runner Unity 3D game and an Emotiv EPOC+ EEG headset to evaluate the credibility of the provided Emotiv Suite. By using the relatively low-cost portable EEG acquisition device, the project aims to explore on the potential of Brain-Computer Interface (BCI) devices as game controls and provide insights for further research into this field. Additionally, this study seeks to clarify the over reliance on the Emotiv Suite by game development firms, and whether it may lead them in the wrong direction. This report presents the results of an experiment designed to evaluate the use of an EEG headset in a game designed to evoke emotions in players. Three participants played the developed game while wearing the EEG headset and their emotional responses were measured using both a self-reported Player’s Rating survey and the EEG data. The results showed that the game was not perceived as difficult by the participants and that there was a high level of engagement and immersion in the game. The analysis of the EEG data showed the evoked emotions varied little among the participants and that the game had a significant impact on their stress and relaxation levels. The report concludes by discussing the limitations of the experiment and suggesting future research directions in the field of EEG-base gaming. Bachelor of Engineering (Computer Engineering) 2023-04-16T03:51:40Z 2023-04-16T03:51:40Z 2023 Final Year Project (FYP) Pang, K. J. W. (2023). Artificial intelligence based game design and analysis of brain signals. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/165866 https://hdl.handle.net/10356/165866 en SCSE22-0361 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Medicine::Biosensors Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics Pang, Kelvin Jun Wei Artificial intelligence based game design and analysis of brain signals |
| title | Artificial intelligence based game design and analysis of brain signals |
| title_full | Artificial intelligence based game design and analysis of brain signals |
| title_fullStr | Artificial intelligence based game design and analysis of brain signals |
| title_full_unstemmed | Artificial intelligence based game design and analysis of brain signals |
| title_short | Artificial intelligence based game design and analysis of brain signals |
| title_sort | artificial intelligence based game design and analysis of brain signals |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Medicine::Biosensors Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics |
| url | https://hdl.handle.net/10356/165866 |
| work_keys_str_mv | AT pangkelvinjunwei artificialintelligencebasedgamedesignandanalysisofbrainsignals |