Affective Multimodal Counter-Strike video game dataset (AMuCS) - Public

This dataset consists of data collected from 245 participants. It was recorded at four large LAN events in Switzerland which took place between October 2020 and April 2022. Physiological and behavioural data was recorded from groups of 2 or 4 participants playing a round of team deathmatch in the game CounterStrike: Global Offensive. The gameplay was then continuously self-annotated according to either valence or arousal. *** To gain access to this dataset please follow this procedure: 1. request access using the corresponding button; 2. you need a switch-edu account to register, anyone is entitled to create such an account; 3. download, sign and attach the EULA to the request form; 4. we will then accept your demand upon verification. ***

    Organizational unit
    SIMS - Social Intelligence and Multi-Sensing
    Type
    Dataset
    DOI
    10.26037/yareta:gvvoc4wfsfhupm4ygge26wupnm
    Referenced by the following DOI
    • 10.36227/techrxiv.170630398.84528625/v1
    Keywords
    multimodal, affective computing, video game, physiological signals, electrodermal activity, multiplayer, arousal, valence, ECG, EDA, eyetracking, gameplay
Publication date21/11/2022
Retention date
accessLevelClosedAccess levelClosed
SensitivityOrange
duaSignedContract on the use of data
Signed
Contributors
  • Fanourakis, Marios Aristogenis
  • Chanel, Guillaume orcid
Files
3926 Files (954.2 GB)
1
0
  • Quality (0 Reviews)
  • Usefulness (0 Reviews)

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