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Shared Three-Dimensional Robotic Arm Control Based on Asynchronous BCI and Computer Vision.
- Source :
-
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society [IEEE Trans Neural Syst Rehabil Eng] 2023; Vol. 31, pp. 3163-3175. Date of Electronic Publication: 2023 Aug 07. - Publication Year :
- 2023
-
Abstract
- Objective: A brain-computer interface (BCI) can be used to translate neuronal activity into commands to control external devices. However, using noninvasive BCI to control a robotic arm for movements in three-dimensional (3D) environments and accomplish complicated daily tasks, such as grasping and drinking, remains a challenge.<br />Approach: In this study, a shared robotic arm control system based on hybrid asynchronous BCI and computer vision was presented. The BCI model, which combines steady-state visual evoked potentials (SSVEPs) and blink-related electrooculography (EOG) signals, allows users to freely choose from fifteen commands in an asynchronous mode corresponding to robot actions in a 3D workspace and reach targets with a wide movement range, while computer vision can identify objects and assist a robotic arm in completing more precise tasks, such as grasping a target automatically.<br />Results: Ten subjects participated in the experiments and achieved an average accuracy of more than 92% and a high trajectory efficiency for robot movement. All subjects were able to perform the reach-grasp-drink tasks successfully using the proposed shared control method, with fewer error commands and shorter completion time than with direct BCI control.<br />Significance: Our results demonstrated the feasibility and efficiency of generating practical multidimensional control of an intuitive robotic arm by merging hybrid asynchronous BCI and computer vision-based recognition.
Details
- Language :
- English
- ISSN :
- 1558-0210
- Volume :
- 31
- Database :
- MEDLINE
- Journal :
- IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
- Publication Type :
- Academic Journal
- Accession number :
- 37498753
- Full Text :
- https://doi.org/10.1109/TNSRE.2023.3299350