Files and links (1)
Published, Version of Record (VoR)CC BY V4.0, Open
Journal article
Single-Trial Recognition of Video Gamer's Expertise from Brain Haemodynamic and Facial Emotion Responses
Brain sciences, v 11(1), pp 1-20
01 Jan 2021
PMID: 33466787
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
With an increase in consumer demand of video gaming entertainment, the game industry is exploring novel ways of game interaction such as providing direct interfaces between the game and the gamers' cognitive or affective responses. In this work, gamer's brain activity has been imaged using functional near infrared spectroscopy (fNIRS) whilst they watch video of a video game (League of Legends) they play. A video of the face of the participants is also recorded for each of a total of 15 trials where a trial is defined as watching a gameplay video. From the data collected, i.e., gamer's fNIRS data in combination with emotional state estimation from gamer's facial expressions, the expertise level of the gamers has been decoded per trial in a multi-modal framework comprising of unsupervised deep feature learning and classification by state-of-the-art models. The best tri-class classification accuracy is obtained using a cascade of random convolutional kernel transform (ROCKET) feature extraction method and deep classifier at 91.44%. This is the first work that aims at decoding expertise level of gamers using non-restrictive and portable technologies for brain imaging, and emotional state recognition derived from gamers' facial expressions. This work has profound implications for novel designs of future human interactions with video games and brain-controlled games.
Metrics
Details
- Title
- Single-Trial Recognition of Video Gamer's Expertise from Brain Haemodynamic and Facial Emotion Responses
- Creators
- Ana R. Andreu-Perez - University of GranadaMehrin Kiani - University of EssexJavier Andreu-Perez - University of EssexPratusha Reddy - Drexel UniversityJaime Andreu-Abela - University of GranadaMaria Pinto - University of GranadaKurtulus Izzetoglu - Drexel University
- Publication Details
- Brain sciences, v 11(1), pp 1-20
- Publisher
- Mdpi
- Number of pages
- 20
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000609861000001
- Scopus ID
- 2-s2.0-85099341054
- Other Identifier
- 991019168338504721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Neurosciences