CogniMeter: EEG-Based Brain States Monitoring

被引:3
作者
Hou, Xiyuan [1 ]
Liu, Yisi [1 ]
Lim, Wei Lun [2 ]
Lan, Zirui [2 ]
Sourina, Olga [1 ]
Mueller-Wittig, Wolfgang [1 ]
Wang, Lipo [2 ]
机构
[1] Nanyang Technol Univ, Fraunhofer IDM, Singapore, Singapore
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore, Singapore
来源
TRANSACTIONS ON COMPUTATIONAL SCIENCE XXVIII: SPECIAL ISSUE ON CYBERWORLDS AND CYBERSECURITY | 2016年 / 9590卷
关键词
Visual interface; EEG; Stress; Mental workload; Emotions; EMOTION; AROUSAL;
D O I
10.1007/978-3-662-53090-0_6
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Electroencephalogram (EEG) techniques are traditionally used in the medical field. Recent research work focuses on applying these techniques to daily life with wireless and relatively low-price EEG devices available in the market. As a result, applications such as neurofeedback training, neuromarketing, emotion, stress, mental workload recognition, etc. using EEG techniques on healthy adults have been developed. Since the EEG measures and records electrical activity in the brain, it is possible for it to reflect a person's brain states. In this paper, we describe a novel brain computer interface called CogniMeter integrated with proposed real-time emotion, mental workload, and stress recognition algorithms. With this system, we can assess human emotions, mental workload, and stress in real time. This work can be applied as a human study tool in many fields. For example, the wellbeing of users within a system or workers in industry can be monitored to improve their protection from overly stressful workload conditions. In research, brain state monitoring can be applied in simulation scenarios during human factor study experiments. In marketing, a person's emotional response toward products or advertisements can be studied using EEG-based brain states monitoring.
引用
收藏
页码:108 / 126
页数:19
相关论文
共 39 条
  • [1] ELAN: A Software Package for Analysis and Visualization of MEG, EEG, and LFP Signals
    Aguera, Pierre-Emmanuel
    Jerbi, Karim
    Caclin, Anne
    Bertrand, Olivier
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2011, 2011
  • [2] [Anonymous], P 2015 10 INT C INF, DOI DOI 10.1109/ICICS.2015.7459815
  • [3] Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness
    Borghini, Gianluca
    Astolfi, Laura
    Vecchiato, Giovanni
    Mattia, Donatella
    Babiloni, Fabio
    [J]. NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS, 2014, 44 : 58 - 75
  • [4] Bradley M. M., 2007, Technical report B-3, V2nd
  • [5] Calibo TK, 2013, IEEE IMTC P, P1471
  • [6] Coan J.A., 2007, HDB EMOTION ELICITAT, V1st, P29
  • [7] EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
    Delorme, A
    Makeig, S
    [J]. JOURNAL OF NEUROSCIENCE METHODS, 2004, 134 (01) : 9 - 21
  • [8] Hart S. G., 1988, HUMAN MENTAL WORKLOA
  • [9] Long-Term Stability of Cardiovascular and Catecholamine Responses to Stress Tests An 18-Year Follow-Up Study
    Hassellund, Skjalg S.
    Flaa, Arnljot
    Sandvik, Leiv
    Kjeldsen, Sverre E.
    Rostrup, Morten
    [J]. HYPERTENSION, 2010, 55 (01) : 131 - 136
  • [10] APPROACH TO AN IRREGULAR TIME-SERIES ON THE BASIS OF THE FRACTAL THEORY
    HIGUCHI, T
    [J]. PHYSICA D-NONLINEAR PHENOMENA, 1988, 31 (02) : 277 - 283