Operators’ Emotion Recognition During a Teleoperation Task

Teleoperation systems have been widely used in a large number of fields where the environment is hostile for human. Due to the complexities of the tasks and environments, humans are often still considered a liability to the system. Human performances, major concerns in the teleoperation, not only are affected by HMI, but also interact with human emotion states. This study was to evaluate the emotion states of operators during the teleoperation task. Three tasks were carried out based on the simulated teleoperation system to evaluate the effects of the factors from HMI on subjects’ emotion. Human emotion states were recognized via a Random Forest model based on EEG signals. The results showed the background interference and target movement adversely influenced emotion states.