CogniMeter: EEG-based Emotion, Mental Workload and Stress Visual Monitoring

• Published in: 2015 International Conference on Cyberworlds (CW) pp. 153 - 160
• Main Authors: Xiyuan Hou, Yisi Liu, Sourina, Olga, Mueller-Wittig, Wolfgang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.10.2015
• Subjects: Biomedical monitoring; EEG; Electroencephalography; Emotion recognition; emotions; Feature extraction; mental workload; Monitoring; Real-time systems; Stress; visual interface
• DOI: 10.1109/CW.2015.58

Real-time EEG (Electroencephalogram)-based user's emotion, mental workload and stress monitoring is a new direction in research and development of human-machine interfaces. It has attracted recently more attention from the research community and industry as wireless portable EEG devices became easily available on the market. EEG-based technology has been applied in anesthesiology, psychology, serious games or even in marketing. In this work, we describe available real-time algorithms of emotion recognition, mental workload, and stress recognition from EEG and propose a novel interface Cogni Meter for the user's mental state visual monitoring. The system can be used in real time to assess human current emotions, levels of mental workload and stress. Currently, it is applied to monitor the user's emotional state, mental workload and stress in simulation scenarios or used as a tool to assess the subject's mental state in human factor study experiments.