Neurological Measurement of Human Trust in Automation Using Electroencephalogram

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.