Objective: Independent of conventional neurofeedback training, in this study, we propose a tactile sensation assisted motor imagery training (SA-MI Training) approach to improve the performance of MI-based BCI.
Methods: Twenty-six subjects were recruited and randomly divided into a Training-Group and a Control-Group. All subjects were required to perform three blocks of MI tasks. In the Training-Group, during the second block (SA-MI Training block), tactile stimulation was applied to the left or right wrist while the subjects were performing the left or right-hand MI task, while during the first block (Pre-Training block) and the third block (Post-Training block), subjects performed pure MI tasks without the tactile sensation assistance. In contrast, in the Control-Group, subjects performed the left and right-hand MI tasks in all three blocks.
Results: The performance of the Post-Training block (83.2 ± 11.4%) was significantly (p = 0.0014) higher than that of the Pre-Training block (73.2 ± 16.3%). By contrast, in the Control-Group, no significant difference was found among the three blocks. Moreover, after the SA-MI Training, the motor-related cortex activation (i.e., ERD/ERS) and the R coefficient in the alpha-beta band were enhanced, while no training effect was found in the Control-Group.
Conclusion: The proposed SA-MI Training approach can significantly improve the performance of MI, which provides a novel training framework for MI-based BCI.
Significance: It may be especially beneficial to those who are with difficulty in convention neurofeedback training or performing pure MI mental tasks to gain BCI control.
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http://dx.doi.org/10.1109/TBME.2022.3201241 | DOI Listing |
IEEE Trans Neural Syst Rehabil Eng
November 2023
Objective: In this study, we propose a tactile-assisted calibration method for a motor imagery (MI) based Brain-Computer Interface (BCI) system.
Method: In the proposed calibration, tactile stimulation was applied to the hand wrist to assist the subjects in the MI task, which is named SA-MI task. Then, classifier training in the SA-MI Calibration was performed using the SA-MI data, while the Conventional Calibration employed the MI data.
IEEE Trans Biomed Eng
February 2023
Objective: Independent of conventional neurofeedback training, in this study, we propose a tactile sensation assisted motor imagery training (SA-MI Training) approach to improve the performance of MI-based BCI.
Methods: Twenty-six subjects were recruited and randomly divided into a Training-Group and a Control-Group. All subjects were required to perform three blocks of MI tasks.
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