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Objective.Brain-computer Interfaces (BCI) with functional electrical stimulation (FES) as a feedback device might promote neuroplasticity and hence improve motor function. Novel findings suggested that neuroplasticity could be possible in people with multiple sclerosis (pwMS). This preliminary study explores the effects of using a BCI-FES in therapeutic intervention, as an emerging methodology for gait rehabilitation in pwMS.Approach.People with relapsing-remitting, primary progressive or secondary progressive MS were evaluated with the inclusion criteria to enroll the nine participants required by the statistically computed sample size. Each patient trained with a BCI-FES during 24 sessions distributed in eight weeks. The effects were evaluated on gait speed (Timed 25 Foot Walk), walking ability (12-item Multiple Sclerosis Walking Scale), quality of life measures, the true positive rate as the BCI-FES performance metric and the event-related desynchronization (ERD) onset latency of the sensorimotor rhythms.Main results.Seven patients completed the therapeutic intervention. A statistically and clinically significant post-treatment improvement was observed in gait speed, as a result of a reduction in the time to walk 25 feet (-1.99 s,p= 0.018), and walking ability (-31.25 score points,p= 0.028). The true positive rate showed a statistically significant improvement (+15.87 score points,p= 0.018). An earlier ERD onset latency (-180 ms) after treatment was found.Significance.This is the first study that explored gait rehabilitation using BCI-FES in pwMS. The results showed improvement in gait which might have been promoted by changes in functional brain connections involved in sensorimotor rhythm modulation. Although more studies with a larger sample size and control group are required to validate the efficacy of this approach, these results suggest that BCI-FES technology could have a positive effect on MS gait rehabilitation.

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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.

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Brain computer interfaces (BCI) represent an alternative for patients whose cognitive functions are preserved, but are unable to communicate via conventional means. A commonly used BCI paradigm is based on the detection of event-related potentials, particularly the P300, immersed in the electroencephalogram (EEG). In order to transfer laboratory-tested BCIs into systems that can be used by at homes, it is relevant to investigate if it is possible to select a limited set of EEG channels that work for most subjects and across different sessions without a significant decrease in performance. In this work, two strategies for channel selection for a single-trial P300 brain computer interface were evaluated and compared. The first strategy was tailored specifically for each subject, whereas the second strategy aimed at finding a subject-independent set of channels. In both strategies, genetic algorithms (GAs) and recursive feature elimination algorithms were used. The classification stage was performed using a linear discriminant. A dataset of EEG recordings from 18 healthy subjects was used test the proposed configurations. Performance indexes were calculated to evaluate the system. Results showed that a fixed subset of four subject-independent EEG channels selected using GA provided the best compromise between BCI setup and single-trial system performance.

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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.

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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.

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La señal de electromiografía de músculos sanos es modelada como un proceso aleatorio cuya función de distribución de probabilidades es aproximada por medio de distribuciones Gaussianas o Laplacianas. En este trabajo se estudia el ajuste del EMG del músculo tibial anterior (TA) parético a estas distribuciones y el análisis estadístico de sus estimadores de amplitud, com vistas a la utilización de esta senãl como control de un estimulador eléctrico para corrección de la caída del antepié durante la fase de oscilación (FO) de la marcha hemipléjica. Se estudiarón: el valor cuadrático medio (RMS), valor medio absoluto (VMA), valor medio absoluto de la diferencia (VMAD) y varianza (VAR). Se analizaron 40 registros eletromiográfico del TA obtenidos durante distintas fases de la marcha de 2 músculos con hemiparesia. Se observó que dicha senãl puede ser aproximada, al igual que en músculos sanos, mediante distribuciones Gaussianas o Laplacianas. La distribución Laplaciana es la que mejor ajustó a la señal durante la FO, fase de la marcha con mayor actividad del TAA, lo que supone que el VMA es el mehor estimador de su amplitud. Sin embargo, todos los parámetros analizados puddieron diferenciar estadísticamente da FO del resto de las fases analizadas. La VAR es el estimador que presentó mejor comportamiento dada su menor variabilidad. En conclusión, los algoritmos de detección de cambios en músculos sanos basados en estos estimadores, podrían también aplicarse para el TA parético y utilizar la señal proveniente de ese músculo como control de un estimulador eléctrico funcional.

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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.

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