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Neurological Measurement of Human Trust in Automation Using Electroencephalogram
International Journal of Fuzzy Logic and Intelligent Systems 2020;20(4):261-271
Published online December 25, 2020
© 2020 Korean Institute of Intelligent Systems.

Seeung Oh1, Younho Seong2, Sun Yi3, and Sangsung Park4

1Department of Applied Engineering Technology at North Carolina Agricultural and Technical State University, Greensboro, USA
2Industrial and systems engineering with North Carolina A&T State University, Greensboro, NC, USA.Greensboro, NC, USA
3Mechanical Engineering at North Carolina A&T State University, USA
4CheongJu University, Cheongju, Korea
Correspondence to: Seeung Oh (soh1@ncat.edu)
Received September 10, 2020; Revised December 2, 2020; Accepted December 8, 2020.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
In modern society, automation is sufficiently complex to conduct advanced tasks. The role of the human operator in controlling a complex automation is crucial for avoiding failures, reducing risk, and preventing unpredictable situations. Measuring the level of trust of human operators is vital in predicting their acceptance and reliance on automation. In this study, an electroencephalogram (EEG) is used to identify specific brainwaves under trusted and mistrusted cases of automation. A power spectrum analysis was used for a brainwave analysis. The results indicate that the power of the alpha and beta waves is stronger for a trusted situation, whereas the power of gamma waves was stronger for a mistrusted situation. When the level of human trust in automation increases, the use of automatic control increases. Therefore, the findings of this research will contribute to utilizing a neurological technology to measure the level of trust of the human operator, which can affect the decision-making and the overall performance of automation used in industries.
Keywords : Trust, Mistrust, Automation, Electroencephalogram (EEG), Power spectrum