Original Research ARTICLE
An EEG-/EOG-based Hybrid Brain-computer Interface: Application on Controlling an Integrated Wheelchair Robotic Arm System
- 1South China University of Technology, China
- 2University of Oxford, United Kingdom
Most existing brain-computer Interfaces (BCIs) are designed to control a single assistive device, such as a wheelchair, a robotic arm or a prosthetic limb. However, many daily tasks require combined functions which can only be realized by integrating multiple robotic devices. Such integration raises the requirement of the control accuracy and is more challenging to achieve a reliable control compared with the single device case. In this study, we propose a novel hybrid BCI with high accuracy based on electroencephalogram (EEG) and electrooculogram (EOG) to control an integrated wheelchair robotic arm system. The user turns the wheelchair left/right by performing left/right hand motor imagery (MI), and generates other commands for the wheelchair and the robotic arm by performing eye blinks and eyebrow raising movements. Twenty-two subjects participated in a MI training session and five of them completed a mobile self-drinking experiment, which was designed purposely with high accuracy requirements. The results demonstrated that the proposed hBCI could provide satisfied control accuracy for a system that consists of multiple robotic devices, and showed the potential of BCI-controlled systems to be applied in complex daily tasks.
Keywords: brain-computer interface (BCI), hybrid BCI, electroencephalogram (EEG), electrooculogram (EOG), Wheelchair, robotic arm
Received: 09 Mar 2019;
Accepted: 04 Nov 2019.
Copyright: © 2019 Li, Huang, Zhang, Yu and He. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Prof. Yuanqing Li, South China University of Technology, Guangzhou, China, firstname.lastname@example.org