Towards multi-modal stress response modelling in competitive league of legends

Research output: Chapter in Book/Report/Conference proceedingChapterScientificpeer-review

Abstract

With the constant rise in popularity of competitive video gaming (also known as Esports), Esports analytics has been a field of growing scientific interest in the recent years. Studies discussing player behaviour, skill learning and team performance have been conducted through Multiplayer Online Battle Arena games such as League of Legends. In this paper, we propose a multi-modal approach towards stress response modeling in competitive LoL games. We collect wearable physiological sensor data, mouse keyboard logs and in-game data in order to study the relationship between player stress responses and in-game behaviour. We discuss the design criteria and propose future studies using the collected dataset.
Original languageEnglish
Title of host publicationIEEE Conference on Computatonal Intelligence and Games, CIG
PublisherIEEE Computer Society
ISBN (Print)9781728118840
DOIs
Publication statusPublished - 1 Aug 2019
Event2019 IEEE Conference on Games - London, United Kingdom
Duration: 20 Aug 201923 Aug 2019
http://ieee-cog.org/2019/

Publication series

NameIEEE Conference on Computatonal Intelligence and Games, CIG
Volume2019-August

Conference

Conference2019 IEEE Conference on Games
Abbreviated titleCoG
CountryUnited Kingdom
CityLondon
Period20/08/1923/08/19
Internet address

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Keywords

  • Competitive video games
  • Esports
  • League of Legends
  • Multi-modal
  • Player modelling
  • Player physiology
  • Player stress response

Cite this

Blom, P. M., Bakkes, S., & Spronck, P. (2019). Towards multi-modal stress response modelling in competitive league of legends. In IEEE Conference on Computatonal Intelligence and Games, CIG (IEEE Conference on Computatonal Intelligence and Games, CIG; Vol. 2019-August). IEEE Computer Society. https://doi.org/10.1109/CIG.2019.8848004