ArticleFrontiers in human neuroscience2026
Bimanual attempts improving EEG-based hand movement decoding in stroke patients with hemiplegia.
Article in Frontiers in human neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Brain-computer interfaces (BCIs) based on electroencephalography (EEG) signals have been applied to improve active hand motor function rehabilitation of stroke patients. Besides, the bilateral arm rehabilitation training can effectively promote the recovery of the unilateral affected hand. However, existing studies on BCIs for stroke patients mainly focus on decoding the unilateral affected hand without effectively utilizing the unaffected hand. Objective: In this paper, we studied the neural signatures and decoding of bimanual and unimanual motor attempts of hemiplegic stroke patients from EEG signals to explore the neural signature differences between bimanual and unimanual movements of patients and whether the differences can improve movement decoding accuracy. Methods: We designed the experimental paradigm of unimanual and bimanual opening and closing motor attempts. Furthermore, we compared the neural signature differences using movement-related cortical potential (MRCP) and event-related desynchronization (ERD). Results: Experimental results from hemiplegic stroke patients indicated that greater MRCP activation was found during bimanual movements than unimanual movements. Although the event-related spectral perturbation (ERSP) varied among patients, it mainly appeared in the [8-30] Hz frequency band, and the ERD activation of bimanual movements was greater than that of unimanual movements in specific frequency bands and brain regions for each patient. The average decoding accuracy of bimanual movements was higher than that of unimanual movements by 4% to 12%. Discussion: This work can potentially advance BCI-based active rehabilitation of hand motor function of stroke patients.
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