A Real-World Neuroimaging System to Evaluate Stress
While the laboratory setting offers researchers a great deal of experimental control, this environment also limits how generalizable the results are to the real world. This is particularly true when studying the multifaceted phenomenon of stress, which often relies on personal experience, a dimension that is difficult to reproduce in the laboratory setting. This paper describes a novel, multi-aspect real-world integrated neuroimaging system (MARIN) optimized to study physiological phenomena in the real-world and particularly suited to the study of stress. This system integrates neurological data from a gel-free, wireless EEG device with physiological data from wireless cardiac and skin conductance sensors, as well as self-reports of activity and stress. Coordination of the system is managed through an Android handheld mobile device that also logs salient events and presents inventories for subjective reports of stress. The integration of these components creates a rich, multimodal dataset with minimal interference to the user’s daily life, and these data will guide the further understanding of neurological mechanisms of stress.
Keywordswireless electroencephalography skin conductance response electrodermal activation heart-rate variability wearability
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- 1.Lamond, N., Dawson, D., Roach, G.D.: Fatigue assessment in the field: validation of a hand-held electronic psychomotor vigilance task. Aviat Space Environ. Med. 76, 486–489 (2005)Google Scholar
- 4.Selye, H.: The stress of life. McGraw-Hill (1956)Google Scholar
- 12.Staal, M.A.: Stress, cognition, and human performance: A literature review and conceptual framework (2004)Google Scholar
- 14.Dawson, M.E., Schell, A.M., Filion, D.L.: The electrodermal system. In: Cacioppo, J.T., Tassinary, L.G., Berntson, G.G. (eds.) Handbook of Psychophysiology, 3rd edn., pp. 159–181. Cambridge University Press, New York (2007)Google Scholar
- 18.Hosseini, S.A., Khalilzadeh, M.A.: Emotional stress recognition system using EEG and psychophysiological signals: Using new labelling process of EEG signals in emotional stress state. In: 2010 International Conference on Biomedical Engineering and Computer Science (ICBECS), pp. 1–6 (2010)Google Scholar
- 19.Hamid, N.H.A., Sulaiman, N., Aris, S.A.M., Murat, Z.H., Taib, M.N.: Evaluation of human stress using EEG Power Spectrum. In: 2010 6th International Colloquium on Signal Processing and Its Applications (CSPA), pp. 1–4 (2010)Google Scholar
- 20.Sulaiman, N., Taib, M.N., Lias, S., Murat, Z.H., Aris, S.A.M., Mustafa, M., Rashid, N.A.: Development of EEG-based stress index. In: 2012 International Conference on Biomedical Engineering (ICoBE), pp. 461–466 (2012)Google Scholar
- 24.Gramann, K., Gwin, J.T., Ferris, D.P., Oie, K., Jung, T.-P., Lin, C.-T., Liao, L.-D., Makeig, S.: Cognition in action: imaging brain/body dynamics in mobile humans. Rev. Neurosci. 22, 593–608 (2011)Google Scholar
- 27.Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research. In: Hancock, P.A., Meshkati, N. (eds.) Advances in Psychology, pp. 139–183. North-Holland (1988)Google Scholar