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Using brain-computer-interface for robot arm control

Sebastian-Daniel Rosca, +1 more
- Vol. 121, pp 08006
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TLDR
The model and simulate the entire system functioning, both the robotic arm control and the brain signals processing are developed, to achieve a brain-computer system that controls a robotic arm that can replace a human arm.
Abstract
In this paper, we analyze the principles of brain computer interface that convert the electrical activity of the human brain into commands for a computer of any embedded device. For this reason, we present the existing devices and applications from the area of brain-computer interfaces with advantages and disadvantages. Further, we propose a solution for brain control of a robotic arm. We develop the model and simulate the entire system functioning, both the robotic arm control and the brain signals processing. The final purpose of our research is to achieve a brain-computer system that controls a robotic arm that can replace a human arm.

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Citations
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References
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Journal ArticleDOI

Brain Computer Interfaces, a Review

TL;DR: The state-of-the-art of BCIs are reviewed, looking at the different steps that form a standard BCI: signal acquisition, preprocessing or signal enhancement, feature extraction, classification and the control interface.
Journal ArticleDOI

P300 brain computer interface: current challenges and emerging trends

TL;DR: It is concluded that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.
Journal ArticleDOI

Robust classification of EEG signal for brain-computer interface

TL;DR: High accuracy, fast learning, and online performance make this P300 speller a potential communication tool for severely disabled individuals, who have lost all other means of communication and are otherwise cut off from the world, provided their disability does not interfere with the performance of the speller.
Journal ArticleDOI

A brain-computer interface based attention training program for treating attention deficit hyperactivity disorder.

TL;DR: Investigation of a new more intensive BCI-based attention training game system on 20 unmedicated ADHD children with significant inattentive symptoms found that the change in the EEG based BCI ADHD severity measure correlated with the change ADHD Rating Scale scores.
Journal ArticleDOI

A Synergetic Brain-Machine Interfacing Paradigm for Multi-DOF Robot Control

TL;DR: The user needs to only think about the end-point movement of the robot arm, which allows simultaneous multijoints control by BMI, and the support vector machine-based decoder designed in this paper is adaptive to the changing mental state of the user.
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