Tactile Sensation Assisted Motor Imagery Training for Enhanced BCI Performance: A Randomized Controlled Study

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-2 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.

Automated summary

In this study, a tactile sensation assisted motor imagery training method is proposed to improve the performance of MI-based BCI. The training group received training with tactile stimulation, while the control group performed regular tasks. The results showed that the proposed training method significantly improved the performance of motor imagery.