Please use this identifier to cite or link to this item: https://zone.biblio.laurentian.ca/handle/10219/4081
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dc.contributor.authorKlaassen, Stefan-
dc.date.accessioned2023-09-22T20:05:59Z-
dc.date.available2023-09-22T20:05:59Z-
dc.date.issued2022-01-06-
dc.identifier.urihttps://zone.biblio.laurentian.ca/handle/10219/4081-
dc.description.abstractThe purpose of this paper was to determine the level of engagement with a specific stimuli while playing video games. The modern video game industry has a large and wide audience and is therefore becoming more popular and accessible to the public. The interactions and rewards offered in video games are a key to keep player engagement high. Understanding the player’s brain and how it reacts to different type of stimuli would help to continue improving games and advance the industry into a new era. Although studying human engagement had started many years ago, the application of measuring it in video game players has only been applied more recently and is still an evolving field of research. This thesis will be taking an objective approach by measuring engagement through electroencephalogram (EEG) readings and seeing if it will help improve current dynamic difficulty adjustment (DDA) systems for video games leading to more engaging and entertaining games. Although statistically significant findings were not found in this experiment, the technique for future experiments were laid out in the form of classifiers comparison and program layouts.en_US
dc.language.isoenen_US
dc.subjectEEG,en_US
dc.subjectDDA,en_US
dc.subjectvideo games,en_US
dc.subjectengagement,en_US
dc.subjectflowen_US
dc.subjectBCIen_US
dc.subjectHCIen_US
dc.subjectbehavioral sciencesen_US
dc.subjectUnityen_US
dc.subjectPythonen_US
dc.subjectC#en_US
dc.titleBiocybernetic closed-loop system to improve engagement in video games using electroencephalographyen_US
dc.typeThesisen_US
dc.description.degreeMasters degree in Computational Scienceen_US
dc.publisher.grantorLaurentian University of Sudburyen_US
Appears in Collections:Computational Sciences - Master's theses

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