康复学报 (Dec 2023)

Application of Motor Imagery Brain-Computer Interface on Patients with Motor Dysfunction after Stroke

  • JIANG Yongchun,
  • YIN Junxiao,
  • ZHAO Biyi,
  • WANG Siqing,
  • OU Peilin,
  • LI Jiawen,
  • ZHANG Yanni,
  • LIN Qiang

Journal volume & issue
Vol. 33
pp. 562 – 570

Abstract

Read online

Motor imagery brain-computer interface (MI-BCI) technology determines the motor intention by recognizing the electroencephalogram (EEG) signals generated by motor imagery and then realizes the communication and control between the human brain and external devices. MI-BCI technology had achieved a positive effect in the application of motor function rehabilitation of patients after stroke, which has excellent potential for rehabilitating patients with moderate and severe limb motor dysfunctions. This paper summarizes the domestic and international research status evidence (neuroregulatory mechanism, clinical rehabilitation application, existing problems and possible solutions) of MI-BCI technology in motor function rehabilitation after stroke to provide theoretical support for the clinical application of MI-BCI technology and the development of related equipment. The neural regulation mechanisms of MI-BCI technology mainly include the "central-peripheral-central" closed-loop theory [the top-down central stimulation mode of "central-periphery" (motor imagery) and the down-top sensorimotor feedback mode of "peripheral-central" (limb movement driven by external devices)], neurofeedback and Hebb theory. The clinical rehabilitation application mainly focuses on rehabilitating upper/lower limb motor function and the changes in brain functional networks after stroke. However, there are still some problems in applying MI-BCI technology in clinical rehabilitation, such as poor performance, unclear treatment dose, the quality of collected signals needing to be improved, few categories of motor imagery, and long training cycle. The future study is needed to conduct research on MI-BCI technology combined with other central nervous system intervention, improve the rehabilitation effect of MI-BCI technology by increasing the categories of motor imagery modalities, develop MI-BCI training programs for stroke patients in all periods, and provide a reference for limb movement rehabilitation of patients with central nervous system diseases.

Keywords