An EEG-/EOG-Based Hybrid Brain-Computer Interface: Application on Controlling an Integrated Wheelchair Robotic Arm System

Frontiers in Neuroscience

Qiyun Huang¹  Tianyou Yu¹  Zhijun Zhang¹  Yuanqing Li¹  Shenghong He² 

[1] Center for Brain Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China;MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom;

关键词: brain-computer interface (BCI);    hybrid BCI;    electroencephalogram (EEG);    electrooculogram (EOG);    wheelchair;    robotic arm;   

DOI  :  10.3389/fnins.2019.01243

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown