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Robot control with multitasking of brain-computer interface

Yajun Zhou, Zilin Lu, Yuanqing Li

Year
2022
Citations
4

Abstract

Brain-computer interfaces (BCI) have been extensively researched to assist people with motor paralysis in controlling external devices such as a robotic limb. However, most BCI systems required participants to focus on a single task, limiting their ability to generate other mental or physical activities. Therefore, people's performance of the BCI-based robotic control in multitasking was discussed, as eight healthy subjects performed motor-related tasks of motor imagery and two-handed balancing ball movement, while simultaneously performing visuospatial attention to asynchronously trigger “drinking” actions of a humanoid robot arm with accuracies of 90% and 87.5%, respectively. The online results indicate that the BCI-based robot control system developed for multi-task conditions has a high potential for human augmentation.

Keywords

Human multitaskingComputer scienceBrain–computer interfaceHuman–computer interactionControl (management)RobotRobot controlInterface (matter)Mobile robotOperating system

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