Neurorehabilitation therapy of patients with severe stroke based on functional electrical stimulation commanded by a brain computer interface

Abstract

Introduction: Brain computer interface is an emerging technology to treat the sequelae of stroke. The purpose of this study was to explore the motor imagery related desynchronization of sensorimotor rhythms of stroke patients and to assess the efficacy of an upper limb neurorehabilitation therapy based on functional electrical stimulation controlled by a brain computer interface.

Methods: Eight severe chronic stroke patients were recruited. The study consisted of two stages: screening and therapy. During screening, the ability of patients to desynchronize the contralateral oscillatory sensorimotor rhythms by motor imagery of the most affected hand was assessed. In the second stage, a therapeutic intervention was performed. It involved 20 sessions where an electrical stimulator was activated when the patient's cerebral activity related to motor imagery was detected. The upper limb was assessed, before and after the intervention, by the Fugl-Meyer score (primary outcome). Spasticity, motor activity, range of movement and quality of life were also evaluated (secondary outcomes).

Results: Desynchronization was identified in all screened patients. Significant post-treatment improvement (p < 0.05) was detected in the primary outcome measure and in the majority of secondary outcome scores.

Conclusions: The results suggest that the proposed therapy could be beneficial in the neurorehabilitation of stroke individuals.

Keywords: Brain computer interface; EMOTIV Epoc+; functional electrical stimulation; motor imagery; rehabilitation; stroke; therapy.

Figure 1.

(a) Position of electrodes with gGAMMAcap®, (b) EEG derivations, and (c) picture of a patient during motor imagination trials.

Figure 2.

Components of the Emotiv_BCI-FES Systems employed in the therapy: the headset for EEG signal acquisition; the processing engines where the BCI and interface software run; the microprocessor-based module with the hardware adapter, and the FES device. The movement assisted by FES gives the patient proprioceptive and visual feedback.

Figure 3.

Topographic maps during imagery motor tasks of the paretic upper limbs for the selected f_ERD for each of the eight patients. The color scale of $r^2$ for each map is shown at the right of the map.

Figure 4.

A patient using the Emotiv_BCI-FES System. The different elements of the system are visible in the picture: the headset for EEG signal acquisition; the computer where the software for the BCI and the interface run; the FES device and the electrical stimulation electrodes placed on the extensors of the wrist.

Figure 5.

mFMA and active RoM measures for each patient (n = 8). The asterisk indicates a statistically significant change (p < 0.05).

Figure 6.

Scores obtained in QM mMAL, AU mMAL and VAS measures for each patient (n = 8). The asterisk indicates a statistically significant change (p < 0.05).

Figure 7.

Scores obtained in mAsh measures for each patient (n = 8). The asterisk indicates a statistically significant change (p < 0.05).