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

Paris Mavromoustakos Blom; Sander Bakkes; Pieter Spronck

doi:10.1109/CIG.2019.8848004

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

Paris Mavromoustakos Blom, Sander Bakkes, Pieter Spronck

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

168 Downloads (Pure)

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 language	English
Title of host publication	IEEE Conference on Computatonal Intelligence and Games, CIG
Publisher	IEEE Computer Society
ISBN (Print)	9781728118840
DOIs	https://doi.org/10.1109/CIG.2019.8848004
Publication status	Published - 1 Aug 2019
Event	2019 IEEE Conference on Games - London, United Kingdom Duration: 20 Aug 2019 → 23 Aug 2019 http://ieee-cog.org/2019/

Publication series

Name	IEEE Conference on Computatonal Intelligence and Games, CIG
Volume	2019-August

Conference

Conference	2019 IEEE Conference on Games
Abbreviated title	CoG
Country/Territory	United Kingdom
City	London
Period	20/08/19 → 23/08/19
Internet address	http://ieee-cog.org/2019/

Keywords

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

Access to Document

10.1109/CIG.2019.8848004

COG_2019_Esports (2)

Cite this

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title = "Towards multi-modal stress response modelling in competitive league of legends",

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.",

keywords = "Competitive video games, Esports, League of Legends, Multi-modal, Player modelling, Player physiology, Player stress response",

author = "Blom, {Paris Mavromoustakos} and Sander Bakkes and Pieter Spronck",

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doi = "10.1109/CIG.2019.8848004",

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booktitle = "IEEE Conference on Computatonal Intelligence and Games, CIG",

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note = "2019 IEEE Conference on Games, CoG ; Conference date: 20-08-2019 Through 23-08-2019",

url = "http://ieee-cog.org/2019/",

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Blom, PM, 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, 2019 IEEE Conference on Games, London, United Kingdom, 20/08/19. https://doi.org/10.1109/CIG.2019.8848004

Towards multi-modal stress response modelling in competitive league of legends. / Blom, Paris Mavromoustakos; Bakkes, Sander; Spronck, Pieter.
IEEE Conference on Computatonal Intelligence and Games, CIG. IEEE Computer Society, 2019. (IEEE Conference on Computatonal Intelligence and Games, CIG; Vol. 2019-August).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Scientific › peer-review

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T1 - Towards multi-modal stress response modelling in competitive league of legends

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AU - Bakkes, Sander

AU - Spronck, Pieter

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N2 - 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.

AB - 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.

KW - Competitive video games

KW - Esports

KW - League of Legends

KW - Multi-modal

KW - Player modelling

KW - Player physiology

KW - Player stress response

UR - http://www.mendeley.com/research/towards-multimodal-stress-response-modelling-competitive-league-legends

U2 - 10.1109/CIG.2019.8848004

DO - 10.1109/CIG.2019.8848004

M3 - Chapter

SN - 9781728118840

T3 - IEEE Conference on Computatonal Intelligence and Games, CIG

BT - IEEE Conference on Computatonal Intelligence and Games, CIG

PB - IEEE Computer Society

T2 - 2019 IEEE Conference on Games

Y2 - 20 August 2019 through 23 August 2019

ER -

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

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Keywords

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