5 papers
AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
Anton Smerdov, Evgeny Burnaev, Andrey Somov +1
The emerging progress of eSports lacks the tools for ensuring high-quality analytics and training in Pro and amateur eSports teams. We report on an Artificial Intelligence (AI) ena…
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine Learning
Anton Smerdov, Andrey Somov, Evgeny Burnaev +2
Current research in eSports lacks the tools for proper game practising and performance analytics. The majority of prior work relied only on in-game data for advising the players on…
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset
Anton Smerdov, Bo Zhou, Paul Lukowicz +1
Proper training and analytics in eSports require accurately collected and annotated data. Most eSports research focuses exclusively on in-game data analysis, and there is a lack of…
Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario
Anton Smerdov, Anastasia Kiskun, Rostislav Shaniiazov +2
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 - a…
eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart Chair
Anton Smerdov, Evgeny Burnaev, Andrey Somov
Today's competition between the professional eSports teams is so strong that in-depth analysis of players' performance literally crucial for creating a powerful team. There are two…