Detecting Outlier Behavior of Game Player Players Using Multimodal Physiology Data
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kang, Shinjin | - |
dc.contributor.author | Park, Taiwoo | - |
dc.date.available | 2021-03-17T07:45:58Z | - |
dc.date.created | 2020-07-06 | - |
dc.date.issued | 2020-03 | - |
dc.identifier.issn | 1079-8587 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/12410 | - |
dc.description.abstract | This paper describes an outlier detection system based on a multimodal physiology data clustering algorithm in a PC gaming environment. The goal of this system is to provide information on a game player's abnormal behavior with a bio-signal analysis. Using this information, the game platform can easily identify players with abnormal behavior in specific events. To do this, we propose a mouse device that measures the wearer's skin conductivity, temperature, and motion. We also suggest a Dynamic Time Warping (DTW) based clustering algorithm. The developed system examines the biometric information of 50 players in a bullet dodge game. This paper confirms that a mouse coupled with a physiology multimodal system is useful for detecting outlier behavior of game players in a non-intrusive way. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | TSI PRESS | - |
dc.subject | BRAIN-COMPUTER INTERFACE | - |
dc.title | Detecting Outlier Behavior of Game Player Players Using Multimodal Physiology Data | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Shinjin | - |
dc.identifier.doi | 10.31209/2019.100000141 | - |
dc.identifier.scopusid | 2-s2.0-85079834153 | - |
dc.identifier.wosid | 000516553300020 | - |
dc.identifier.bibliographicCitation | INTELLIGENT AUTOMATION AND SOFT COMPUTING, v.26, no.1, pp.205 - 214 | - |
dc.relation.isPartOf | INTELLIGENT AUTOMATION AND SOFT COMPUTING | - |
dc.citation.title | INTELLIGENT AUTOMATION AND SOFT COMPUTING | - |
dc.citation.volume | 26 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 205 | - |
dc.citation.endPage | 214 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Automation & Control Systems | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Automation & Control Systems | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.subject.keywordPlus | BRAIN-COMPUTER INTERFACE | - |
dc.subject.keywordAuthor | Physiology multimodal system | - |
dc.subject.keywordAuthor | Game behavior analysis | - |
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