Does feedback based on FES-evoked nociceptive withdrawal reflex condition event-related desynchronization? An exploratory study with brain-computer interfaces.

Introduction.Event-related desynchronization (ERD) is used in brain-computer interfaces (BCI) to detect the user's motor intention (MI) and convert it into a command for an actuator to provide sensory feedback or mobility, for example by means of functional electrical stimulation (FES). Recent studies have proposed to evoke the nociceptive withdrawal reflex (NWR) using FES, in order to evoke synergistic movements of the lower limb and to facilitate the gait rehabilitation of stroke patients. The use of NWR to provide sensorimotor feedback in ERD-based BCI is novel; thererfore, the conditioning effect that nociceptive stimuli might have on MI is still unknown.Objetive.To assess the ERD produced during the MI after FES-evoked NWR, in order to evaluate if nociceptive stimuli condition subsequent ERDs.Methods. Data from 528 electroencephalography trials of 8 healthy volunteers were recorded and analyzed. Volunteers used an ERD-based BCI, which provided two types of feedback: intrisic by the FES-evoked NWR and extrinsic by virtual reality. The electromyogram of the tibialis anterior muscle was also recorded. The main outcome variables were the normalized root mean square of the evoked electromyogram (RMSnorm), the average electroencephalogram amplitude at the ERD frequency during MI (A¯MI) and the percentage decrease ofA¯MIrelative to rest (ERD%) at the first MI subsequent to the activation of the BCI.Results.No evidence of changes of theRMSnormon both theA¯MI(p = 0.663) and theERD%(p = 0.252) of the subsequent MI was detected. A main effect of the type of feedback was found in the subsequentA¯MI(p < 0.001), with intrinsic feedback resulting in a largerA¯MI.Conclusions.No evidence of ERD conditioning was observed using BCI feedback based on FES-evoked NWR .Significance.FES-evoked NWR could constitute a potential feedback modality in an ERD-based BCI to facilitate motor recovery of stroke people.

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

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.

M-wave elimination from surface electromyogram of electrically stimulated muscles using singular value decomposition: preliminary results.

The goal of this preliminary study was to investigate the feasibility of using singular value decomposition (SVD) to eliminate the M-wave from the surface electromyogram (EMG) of an electrically stimulated paretic muscle in order to extract the volitional response. An SVD-based algorithm combining the subspaces method and a subsequent filtering is presented. It was evaluated with EMG signals registered from surface of electrically stimulated muscles with simulated paresis and its performance was compared with a conventional fixed filter. The filtering strategy proposed showed a good performance in static conditions where there were no traces of the M-wave. In dynamic conditions, the SVD-based algorithm was robust but with some remaining M-wave traces. It would be as a consequence of modifications in the data matrix and, therefore, in the subspaces generator columns and the singular values. In general, the fixed filter was very sensitive to input signal disturbances. In all of these conditions there was a greater power reduction for the SVD-based filter than for the fixed filter.

BiosStep-assisted walking in spinal cord-injured patients: an evaluation report.

BiosStep is a functional neuromuscular stimulation system designed to assist the gait of people with central nervous system injuries. It stimulates the quadriceps during the stance phase and the nerves in the popliteal space to produce the swing phase of the gait cycle. The gait obtained with BiosStep was assessed using kinematic analysis and it was compared with nondisabled gait. Moreover, the evolution of the physiological cost of walking using BiosStep was evaluated and compared with the gait obtained with mechanical orthoses. The kinematic analysis of the three lower limb joints showed that the angular excursion morphologies of BiosStep-assisted gait were similar to those obtained in healthy gait, but with minor amplitudes. The physiological cost indexes for the BiosStep-assisted gait were higher than those computed for the mechanical-orthoses-assisted gait. Results show the necessity to continue improving the strategies to obtain more functional movements and enhance the training of patients.