Novel method for lower limb rehabilitation based on brain-computer interface and transcutaneous spinal cord electrical stimulation

Ninenko, Ivan; Alisa, Kokorina; Egorov, Maxim; Gupta, Ayush; Mudalige, Nipun Dhananjaya Weerakkodi; Tsetserukou, Dzmitry; Lebedev, Mikhail

doi:10.1109/cnn56452.2022.9912550

Cited by 1 publication

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“…So, Delijorge et al (2020) proposed using the P300-based BCI to control a hand exoskeleton, which allows users to control all exoskeleton fingers with high accuracy, while MI-based paradigms are limited in their ability to provide fine movements of finger control. Several studies have proposed combining exoskeletons, virtual reality, and electrical stimulation to restore both upper limb ( Bulanov et al, 2021 ; Hernandez-Rojas et al, 2022 ) and lower limb ( Ninenko et al, 2022 ) mobility in individuals with paralysis, using the P300-BCI to control the robotic-manipulator and electrical stimulation.…”

Section: Introductionmentioning

confidence: 99%

Beyond passive observation: feedback anticipation and observation activate the mirror system in virtual finger movement control via P300-BCI

Syrov

Yakovlev

Miroshnikov

et al. 2023

Front. Hum. Neurosci.

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Action observation (AO) is widely used as a post-stroke therapy to activate sensorimotor circuits through the mirror neuron system. However, passive observation is often considered to be less effective and less interactive than goal-directed movement observation, leading to the suggestion that observation of goal-directed actions may have stronger therapeutic potential, as goal-directed AO has been shown to activate mechanisms for monitoring action errors. Some studies have also suggested the use of AO as a form of Brain–computer interface (BCI) feedback. In this study, we investigated the potential for observation of virtual hand movements within a P300-based BCI as a feedback system to activate the mirror neuron system. We also explored the role of feedback anticipation and estimation mechanisms during movement observation. Twenty healthy subjects participated in the study. We analyzed event-related desynchronization and synchronization (ERD/S) of sensorimotor EEG rhythms and Error-related potentials (ErrPs) during observation of virtual hand finger flexion presented as feedback in the P300-BCI loop and compared the dynamics of ERD/S and ErrPs during observation of correct feedback and errors. We also analyzed these EEG markers during passive AO under two conditions: when subjects anticipated the action demonstration and when the action was unexpected. A pre-action mu-ERD was found both before passive AO and during action anticipation within the BCI loop. Furthermore, a significant increase in beta-ERS was found during AO within incorrect BCI feedback trials. We suggest that the BCI feedback may exaggerate the passive-AO effect, as it engages feedback anticipation and estimation mechanisms as well as movement error monitoring simultaneously. The results of this study provide insights into the potential of P300-BCI with AO-feedback as a tool for neurorehabilitation.

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