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Article Dans Une Revue IEEE Transactions on Medical Robotics and Bionics Année : 2019

Augmenting Motor Imagery Learning for Brain–Computer Interfacing Using Electrical Stimulation as Feedback

Résumé

Brain-computer Interfaces (BCI) and Functional electrical stimulation (FES) contribute significantly to induce cortical learning and to elicit peripheral neuronal activation processes and thus, are highly effective to promote motor recovery. This study aims at understanding the effect of FES as a neural feedback and its influence on the learning process for motor imagery tasks while comparing its performance with a classical visual feedback protocol. The participants were randomly separated into two groups: one group was provided with visual feedback (VIS) while the other received electrical stimulation (FES) as feedback. Both groups performed various motor imagery tasks while feedback was provided in form of a bi-directional bar for VIS group and targeted electrical stimulation on the upper and lower limbs for FES group. The results shown in this paper suggest that the FES based feedback is more intuitive to the participants, hence, the superior results as compared to the visual feedback. The results suggest that the convergence of BCI with FES modality could improve the learning of the patients both in terms of accuracy and speed and provide a practical solution to the BCI learning process in rehabilitation.

Dates et versions

hal-02401304 , version 1 (09-12-2019)

Identifiants

Citer

Saugat Bhattacharyya, Maureen Clerc, Mitsuhiro Hayashibe. Augmenting Motor Imagery Learning for Brain–Computer Interfacing Using Electrical Stimulation as Feedback. IEEE Transactions on Medical Robotics and Bionics, 2019, 1 (4), pp.247-255. ⟨10.1109/TMRB.2019.2949854⟩. ⟨hal-02401304⟩
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