Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2018
Abstract
In this research, we will analyze EEG signals to obtain neural correlate classifications of user experience by applying predictive analytics. Boredom, flow, and anxiety are three states experienced by users interacting with a computer-based system. A within-subjects experiment was used to collect EEG data for these three states and a baseline. We will apply predictive analytics including linear regression, support vector machine, and neural networks to analyze and classify the EEG data for these three states of user experience.
Keywords
neural correlates, electroencephalogram, predictive analytics, linear regression, support vector machine, neural networks.
Discipline
Graphics and Human Computer Interfaces | Systems Architecture
Research Areas
Information Systems and Management
Areas of Excellence
Digital transformation
Publication
Thirteenth Annual Midwest Association for Information Systems Conference (MWAIS 2018), St. Louis, Missouri, May 17-18, 2018
City or Country
St. Louis, Missouri
Citation
MALLAPRAGADA, Chandana; NAH, Fiona Fui-Hoon; SIAU, Keng; CHEN, Langtao; and YELAMANCHILI, Tejaswini.
Neural correlates of states of user experience in gaming using EEG and predictive analytics. (2018). Thirteenth Annual Midwest Association for Information Systems Conference (MWAIS 2018), St. Louis, Missouri, May 17-18, 2018.
Available at: https://ink.library.smu.edu.sg/sis_research/9527
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.