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

Rakshit, Arnab and Konar, Amit and Nagar, Atulya K. (2020) A Hybrid Brain-Computer Interface for Closed- Loop Position Control of a Robot Arm. IEEE/CAA Journal of Automatica Sinica. ISSN 2329-9266 (Accepted for Publication)

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Brain-Computer Interfacing 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 the positional errors, resulting in failures in taking necessary online corrective actions. There are traces of one or fewer works dealing with closed-loop EEG-based position control. The existing closed-loop brain-induced position control schemes employ a fixed order link selection rule, which often creates a bottleneck for time-efficient control. Second, the existing brain-induced position controllers are designed to generate the 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 induced) link-selection in an arbitrary order as required for efficient control and also to generate a second-order response of the position-control system with gradually diminishing overshoots/undershoots to reduce steady-state errors. Besides the above, the third novelty 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 by 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 stability of the closed-loop system performance using Root Locus technique.

Item Type: Article
Additional Information and Comments: This paper has been accepted for publication in the Journal of Automatica Sinica. When published, the final version will be available from http://www.ieee-jas.org/
Keywords: BCI; EEG; SSVEP; Motor Imagery; P300, Jaco Robot Arm.
Faculty / Department: Faculty of Science > Mathematics and Computer Science
Depositing User: Atulya Nagar
Date Deposited: 13 Jul 2020 15:56
Last Modified: 13 Jul 2020 15:56
URI: https://hira.hope.ac.uk/id/eprint/3101

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