Title: A systematic analysis of intelligent control for robotic arms using non-invasive EEG signals: a comprehensive review

Authors: D. Senthil Vadivelan; Prabhu Sethuramalingam; M. Uma

Addresses: Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India ' Department of Mechanical Engineering, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India ' Department of Computational Intelligence, SRM Institute of Science and Technology, Kattankulathur, Chennai, 603203, India

Abstract: The brain-computer interface (BCI) technology has evolved into a powerful tool for human-machine interaction, particularly benefiting those with physical limitations. This review focuses on the significance of non-invasive electroencephalography (EEG) signals in BCI applications, emphasising their role in controlling assistive robotic arms. The manuscript explores established techniques for processing electrophysiological data, feature extraction, and the use of classification algorithms. Also, discuss diverse BCI hardware for comprehensive brain signal acquisition analysis. The paper addresses challenges in BCI assistive robotic arm control applications and suggests potential solutions, serving as a valuable resource for researchers. Furthermore, it identifies research gaps, helping to understand and resolve emerging issues in BCI technology and assistive robotic arm control.

Keywords: BCI; brain-computer interface; EEG signal; robot arm control; feature extraction; machine learning.

DOI: 10.1504/IJSISE.2024.146213

International Journal of Signal and Imaging Systems Engineering, 2024 Vol.13 No.4, pp.218 - 243

Received: 31 Jan 2024
Accepted: 19 May 2024
Published online: 12 May 2025 *

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