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http://dx.doi.org/10.1016/j.net.2018.11.009

A novel qEEG measure of teamwork for human error analysis: An EEG hyperscanning study  

Cha, Kab-Mun (Korea Atomic Energy Research Institute)
Lee, Hyun-Chul (Korea Atomic Energy Research Institute)
Publication Information
Nuclear Engineering and Technology / v.51, no.3, 2019 , pp. 683-691 More about this Journal
Abstract
In this paper, we propose a novel method to quantify the neural synchronization between subjects in the collaborative process through electroencephalogram (EEG) hyperscanning. We hypothesized that the neural synchronization in EEGs will increase when the communication of the operators is smooth and the teamwork is better. We quantified the EEG signal for multiple subjects using a representative EEG quantification method, and studied the changes in brain activity occurring during collaboration. The proposed method quantifies neural synchronization between subjects through bispectral analysis. We found that phase synchronization between EEGs of multi subjects increased significantly during the periods of collaborative work. Traditional methods for a human error analysis used a retrospective analysis, and most of them were analyzed for an unspecified majority. However, the proposed method is able to perform the real-time monitoring of human error and can directly analyze and evaluate specific groups.
Keywords
Human error; EEG; Hyperscanning; Bispectral analysis;
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1 L. Astolfi, J. Toppi, F. Fallani, G. Vecchiato, S. Salinari, D. Mattia, F. Cincotti, F. Babiloni, Neuroelectrical hyperscanning measures simultaneous brain activity in humans, Brain Topogr. 23 (3) (2010) 243-256.   DOI
2 S. Johansen, "Estimation and hypothesis testing of cointegration vectors in Gaussian vector autoregressive models", Econometrica, Journal of the Econometric Society 59 (6) (1991) 1551-1580.   DOI
3 C.W.J. Granger, Investigating causal relations by econometric models and cross-spectral methods, Econometrica: Journal of the Econometric Society (1969c) 424-438.
4 L.A. Baccala, K. Sameshima, Partial directed coherence: a new concept in neural structure determination, Biol. Cybern. 84 (6) (2001) 463-474.   DOI
5 K. Hirose, 2011 Fukushima Dai-ichi nuclear power plant accident: summary of regional radioactive deposition monitoring results, J. Environ. Radioact. 111 (2012) 13-17.   DOI
6 P. Le Bot, Human reliability data, human error and accident modelsdillustration through the Three Mile Island accident analysis", Reliab. Eng. Syst. Saf. 83 (2) (2004) 153-167.   DOI
7 T.I. Jang, et al., State of the art report for the development of countermeasures against human errors caused by individual factors in Npps, KAERI/AR 959 (2012).
8 H.C. Lee, et al., Development of Human Error Countermeasures for Nuclear Safety, 4163, KAERI/RR, 2016.
9 J.W. Senders, N.P. Moray, Human Error: Cause, Prediction, and Reduction, 25, Lawrence Erlbaum Associates, 1991. ISBN 0-89859-598-3.
10 A.D. Swain, H.E. Guttmann, Handbook of Human-reliability Analysis with Emphasis on Nuclear Power Plant Applications. Final Report, Sandia National Labs., Albuquerque, NM (USA), 1983.
11 J. Toppi, G. Borghini, M. Petti, E.J. He, G.V. De, B. He, L. Astolfi, F. Babiloni, Investigating cooperative behavior in ecological settings: an EEG hyperscanning study, PloS One 11 (4) (2016).
12 A.P. Burgess, On the interpretation of synchronization in EEG hyperscanning studies: a cautionary note, Front. Hum. Neurosci. 7 (2013) 881.   DOI
13 F. Babiloni, L. Astolfi, Social neuroscience and hyperscanning techniques: past, present and future, Neurosci. Biobehav. Rev. 44 (2014) 76-93.   DOI
14 G. Dumas, J. Nadel, R. Soussignan, J. Martinerie, L. Garnero, Inter-brain synchronization during social interaction, PloS One 5 (8) (2010) e12166.   DOI
15 P.R. Montague, G.S. Berns, J.D. Cohen, S.M. McClure, G. Pagnoni, M. Dhamala, M.C. Wiest, I. Karpov, R.D. King, M. Apple, R.E. Fisher, Hyperscanning: simultaneous fMRI during linked social interactions, Neuroimage 16 (2002) 1159-1164.   DOI
16 H. Tang, X. Mai, S. Wang, C. Zhu, F. Krueger, C. Liu, Interpersonal brain synchronization in the right temporo-parietal junction during face-to-face economic exchange, Soc. Cognit. Affect Neurosci. 11 (1) (2015) 23-32.   DOI
17 D.V. Fallani, et al., "Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements", PloS One 5 (12) (2010) e14187.   DOI
18 C.E. Shannon, W. Weaver, The Mathematical Theory of Information, 1949.
19 T. Schreiber, Measuring information transfer, Phys. Rev. Lett. 85 (2) (2000) 461-464.   DOI
20 D. Marinazzo, O. Gosseries, M. Boly, D. Ledoux, M. Rosanova, M. Massimini, Q. Noirhomme, S. Laureys, Directed information transfer in scalp electroencephalographic recordings: insights on disorders of consciousness, Clin. EEG Neurosci. 45 (1) (2014) 33-39.   DOI
21 C.L. Nikias, M.R. Raghuveer, Bispectrum estimation: a digital signal processing framework, Proc. IEEE 75 (7) (1987) 869-897.
22 J.W. Johansen, P.S. Sebel, Development and clinical application of electroencephalographic bispectrum monitoring, Anesthesiology 93 (5) (2000) 1336-1344.   DOI
23 J.C. Sigl, N.G. Chamoun, An introduction to bispectral analysis for the electroencephalogram, J. Clin. Monit. 10 (6) (1994) 392-404.   DOI
24 S. Hagihira, M. Takashina, T. Mori, T. Mashimo, I. Yoshiya, Practical issues in bispectral analysis of electroencephalographic signals, Anesth. Analg. 93 (4) (2001) 966-970.   DOI
25 G. Tononi, O. Sporns, Measuring information integration, BMC Neurosci. 4 (31) (2003).
26 G. Tononi, An information integration theory consciousness, BMC Neurosci. 5 (1) (2004).