A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm

doi:10.1109/JAS.2020.1003336

CASIA OpenIR > 学术期刊 > IEEE/CAA Journal of Automatica Sinica

	A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm
	Arnab Rakshit; Amit Konar; Atulya K. Nagar
发表期刊	IEEE/CAA Journal of Automatica Sinica
ISSN	2329-9266
	2020
卷号	7 期号:5 页码:1344-1360
摘要	Brain-Computer interfacing (BCI) has currently added a new dimension in assistive robotics. Existing brain-computer interfaces designed for position control applications suffer from two fundamental limitations. First, most of the existing schemes employ open-loop control, and thus are unable to track positional errors, resulting in failures in taking necessary online corrective actions. There are examples of a few works dealing with closed-loop electroencephalography (EEG)-based position control. These existing closed-loop brain-induced position control schemes employ a fixed order link selection rule, which often creates a bottleneck preventing time-efficient control. Second, the existing brain-induced position controllers are designed to generate a position response like a traditional first-order system, resulting in a large steady-state error. This paper overcomes the above two limitations by keeping provisions for steady-state visual evoked potential (SSVEP) induced link-selection in an arbitrary order as required for efficient control and generating a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors. Other than the above, the third innovation is to utilize motor imagery and P300 signals to design the hybrid brain-computer interfacing system for the said application with gradually diminishing error-margin using speed reversal at the zero-crossings of positional errors. Experiments undertaken reveal that the steady-state error is reduced to 0.2%. The paper also provides a thorough analysis of the stability of the closed-loop system performance using the Root Locus technique.
关键词	Brain-computer interfacing (BCI) electroencephalography (EEG) Jaco robot arm motor imagery P300 steady-state visually evoked potential (SSVEP)
DOI	10.1109/JAS.2020.1003336
引用统计	被引频次：26[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/43038
专题	学术期刊_IEEE/CAA Journal of Automatica Sinica
推荐引用方式 GB/T 7714	Arnab Rakshit,Amit Konar,Atulya K. Nagar. A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm[J]. IEEE/CAA Journal of Automatica Sinica,2020,7(5):1344-1360.
APA	Arnab Rakshit,Amit Konar,&Atulya K. Nagar.(2020).A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm.IEEE/CAA Journal of Automatica Sinica,7(5),1344-1360.
MLA	Arnab Rakshit,et al."A Hybrid Brain-Computer Interface for Closed-Loop Position Control of a Robot Arm".IEEE/CAA Journal of Automatica Sinica 7.5(2020):1344-1360.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
JAS-2019-0328.pdf（3027KB）	期刊论文	出版稿	开放获取	CC BY-NC-SA	浏览下载