Mental fatigue assessment using brain computer interface (BCI) game

• Main Author: Muhammad Iman Nur Haqim Sulaiman
• Other Authors: Guan Cuntai
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling; DRNTU::Engineering::Computer science and engineering::Computer applications::Social and behavioral sciences
• Online Access: http://hdl.handle.net/10356/76940
• Institution: Nanyang Technological University

Mental fatigue has been a prevalent factor affecting mental efficiency while performing various cognitive workload tasks. Since mental fatigue does not have a clear-cut definition, symptoms such as drowsiness, stress, forgetfulness and the inability to concentrate were examined to represent levels of mental fatigue. In this project, an OpenSesame application was created with the Muse headband to conduct series of alert and fatigue inducing experiments for model training. Through performing SVM classification technique using Matlab, a stress vs alert score was evaluated to control and assess mental fatigue levels from a simple falling blocks game in Unity. While the Matlab BCI engine was able to stream normalized BCI scores from the Muse, the responses became intermittent after a few minutes of gameplay.