Understanding cyber athletes behaviour through a smart chair: Cs:go and monolith team scenario

Anton Smerdov, Anastasia Kiskun, Rostislav Shaniiazov, Andrey Somov, Evgeny Burnaev

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    7 Citations (Scopus)

    Abstract

    eSports is the rapidly developing multidisciplinary domain. However, research and experimentation in eSports are in the infancy. In this work, we propose a smart chair platform-An unobtrusive approach to the collection of data on the eSports athletes and data further processing with machine learning methods. The use case scenario involves three groups of players: cyber athletes (Monolith team), semi-professional players and newbies all playing CS:GO discipline. In particular, we collect data from the accelerometer and gyroscope integrated in the chair and apply machine learning algorithms for the data analysis. Our results demonstrate that the professional athletes can be identified by their behaviour on the chair while playing the game.

    Original languageEnglish
    Title of host publicationIEEE 5th World Forum on Internet of Things, WF-IoT 2019 - Conference Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages973-978
    Number of pages6
    ISBN (Electronic)9781538649800
    DOIs
    Publication statusPublished - Apr 2019
    Event5th IEEE World Forum on Internet of Things, WF-IoT 2019 - Limerick, Ireland
    Duration: 15 Apr 201918 Apr 2019

    Publication series

    NameIEEE 5th World Forum on Internet of Things, WF-IoT 2019 - Conference Proceedings

    Conference

    Conference5th IEEE World Forum on Internet of Things, WF-IoT 2019
    Country/TerritoryIreland
    CityLimerick
    Period15/04/1918/04/19

    Keywords

    • eSports
    • machine learning
    • smart sensing

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