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Updated: Jan 10, 2026

Author Spotlight: Using Motor Imagery Brain-Computer Interface to Improve Motor and Cognitive Function in Stroke Patients
Published on: September 1, 2023
The Enhancement Efficacy of Motor Imagery Based on Gait Phase Encoding Sequential Electrical Stimulation in Stroke
Abstract:
Motor imagery-based brain-computer interface (MI-BCI) has been widely used to promote stroke rehabilitation. However, the conventional lower limb MI paradigm can only induce weak brain activation in stroke patients and cannot effectively guide patients to generate pronounced features during MI tasks, limiting the widespread application of MI-BCI. In this study, we applied a novel walking MI paradigm based on gait phase encoding sequential sensory threshold electrical stimulation (SES-MI) in stroke patients, and systematically explored the efficacy of SES-MI in enhancing brain response patterns and improving classification accuracy, compared with the MI paradigm only with text cues (Non-MI) and with invariable electrical stimulation (IES-MI). Thirteen stroke patients were recruited for this experiment. Event-related spectral perturbation (ERSP) was utilized to supply details about the event-related desynchronization (ERD) phenomenon. Brain activation region, intensity and functional connectivity were compared among the three paradigms. SES-MI induced stronger and wider-area ERD activation than Non-MI and IES-MI. In the somatosensory cortex, the ERD amplitudes of SES-MI increased by a maximum of 115% in contrast to Non-MI. The enhancement of activation in bilateral sensorimotor cortex and prefrontal cortex was observed in SES-MI. The increased brain excitability only occurred in the alpha frequency band. Compared with Non-MI, decreased functional connectivity between different brain regions was found in SES-MI and IES-MI, especially in SES-MI. In the alpha+beta bands, the 2-class classification accuracy for SES-MI vs. SES-Idle (81.30%) was significantly improved compared with the other two paradigms. This work demonstrates that SES-MI is a more efficient paradigm for the modulation of the brain activation patterns, having the potential to promote the development of MI-BCI in stroke lower limb rehabilitation.
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