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