학술논문

Assessing Player Profiles of Achievement, Affiliation, and Power Motivation Using Electroencephalography
Document Type
Periodical
Source
IEEE Transactions on Systems, Man, and Cybernetics: Systems IEEE Trans. Syst. Man Cybern, Syst. Systems, Man, and Cybernetics: Systems, IEEE Transactions on. 52(6):3648-3658 Jun, 2022
Subject
Signal Processing and Analysis
Robotics and Control Systems
Power, Energy and Industry Applications
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Electroencephalography
Games
Psychology
Task analysis
Brain modeling
Particle measurements
Labeling
Computer game
electroencephalography (EEG)
player motivation
Language
ISSN
2168-2216
2168-2232
Abstract
Individual differences in motivation can explain why people act differently in the same situation, and which aspects of a game people with different motive profiles may find most engaging. However, identifying a player’s motive profile from data available during gameplay remains an open research question. Besides a range of subjective and objective techniques for identifying player motivation, electroencephalography (EEG) technology could offer an automatic, objective technique for identifying the profile that best describes a given player. This article proposes a framework to measure player profiles of achievement, affiliation, and power motivation using EEG signals during their engagement within a game. First, an abstract mini-game is proposed to evaluate a player’s motivation. In the mini-game, each human player interacts with four nonplayer characters to gain fortune or friendship through an individual play phase and a social network phase. The game is used within an experimental scenario to collect players’ actions and EEG signals. In addition, data from a psychological test are used to establish ground truth. We propose three subject labeling schemes using the output of the psychological test. Based on a player’s motive profile, behavioral indicators and EEG data analysis indicate that assessing a player’s motive profile is more robust from EEG signals than from behavioral data.