Functional electrical stimulation therapy controlled by a P300-based brain-computer interface, as a therapeutic alternative for upper limb motor function recovery in chronic post-stroke patients. A non-randomized pilot study.

Introduction: Up to 80% of post-stroke patients present upper-limb motor impairment (ULMI), causing functional limitations in daily activities and loss of independence. UMLI is seldom fully recovered after stroke when using conventional therapeutic approaches. Functional Electrical Stimulation Therapy (FEST) controlled by Brain-Computer Interface (BCI) is an alternative that may induce neuroplastic changes, even in chronic post-stroke patients. The purpose of this work was to evaluate the effects of a P300-based BCI-controlled FEST intervention, for ULMI recovery of chronic post-stroke patients. Methods: A non-randomized pilot study was conducted, including 14 patients divided into 2 groups: BCI-FEST, and Conventional Therapy. Assessments of Upper limb functionality with Action Research Arm Test (ARAT), performance impairment with Fugl-Meyer assessment (FMA), Functional Independence Measure (FIM) and spasticity through Modified Ashworth Scale (MAS) were performed at baseline and after carrying out 20 therapy sessions, and the obtained scores compared using Chi square and Mann-Whitney U statistical tests (𝛼 = 0.05). Results: After training, we found statistically significant differences between groups for FMA (p = 0.012), ARAT (p < 0.001), and FIM (p = 0.025) scales. Discussion: It has been shown that FEST controlled by a P300-based BCI, may be more effective than conventional therapy to improve ULMI after stroke, regardless of chronicity. Conclusion: The results of the proposed BCI-FEST intervention are promising, even for the most chronic post-stroke patients often relegated from novel interventions, whose expected recovery with conventional therapy is very low. It is necessary to carry out a randomized controlled trial in the future with a larger sample of patients.

Education Level Modulates the Presence of Poststroke Depression and Anxiety, But It Depends on Age.

ABSTRACT: Depression and anxiety are common complications after stroke and little is known about the modulatory roles of education and age. Our study aimed to evaluate the modulatory effects of education level on anxiety and depression after stroke and their effect on each age group. Adults with first stroke took part in this cross-sectional observational clinical study. We used the following instruments: Hospital Anxiety and Depression Scale (HADS), Montreal Cognitive Scale, Pittsburgh Sleep Quality Index, Barthel index, and Functional Independence Measure. There were 89 patients. The mean (SD) age was 58.01 (13) years, mean (SD) years of education was 9.91 (5.22), 55.1% presented depression symptoms and 47.2% anxiety symptoms, 56.2% were young adults and 43.8% were older adults. We identified a negative association between education and anxiety score ( r = -0. 269, p = 0.011) and depression score ( r = -0.252, p = 0.017). In the linear regression analysis, we found that education is negatively associated with HADS, but this influence was more consistent in young adults. In conclusion, a higher education level reduces the risk of depression and anxiety, but their effect is less consistent in older adults.

Brain-Computer Interface Coupled to a Robotic Hand Orthosis for Stroke Patients' Neurorehabilitation: A Crossover Feasibility Study.

Brain-Computer Interfaces (BCI) coupled to robotic assistive devices have shown promise for the rehabilitation of stroke patients. However, little has been reported that compares the clinical and physiological effects of a BCI intervention for upper limb stroke rehabilitation with those of conventional therapy. This study assesses the feasibility of an intervention with a BCI based on electroencephalography (EEG) coupled to a robotic hand orthosis for upper limb stroke rehabilitation and compares its outcomes to conventional therapy. Seven subacute and three chronic stroke patients (M = 59.9 ± 12.8) with severe upper limb impairment were recruited in a crossover feasibility study to receive 1 month of BCI therapy and 1 month of conventional therapy in random order. The outcome measures were comprised of: Fugl-Meyer Assessment of the Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), motor evoked potentials elicited by transcranial magnetic stimulation (TMS), hand dynamometry, and EEG. Additionally, BCI performance and user experience were measured. All measurements were acquired before and after each intervention. FMA-UE and ARAT after BCI (23.1 ± 16; 8.4 ± 10) and after conventional therapy (21.9 ± 15; 8.7 ± 11) were significantly higher (p < 0.017) compared to baseline (17.5 ± 15; 4.3 ± 6) but were similar between therapies (p > 0.017). Via TMS, corticospinal tract integrity could be assessed in the affected hemisphere of three patients at baseline, in five after BCI, and four after conventional therapy. While no significant difference (p > 0.05) was found in patients' affected hand strength, it was higher after the BCI therapy. EEG cortical activations were significantly higher over motor and non-motor regions after both therapies (p < 0.017). System performance increased across BCI sessions, from 54 (50, 70%) to 72% (56, 83%). Patients reported moderate mental workloads and excellent usability with the BCI. Outcome measurements implied that a BCI intervention using a robotic hand orthosis as feedback has the potential to elicit neuroplasticity-related mechanisms, similar to those observed during conventional therapy, even in a group of severely impaired stroke patients. Therefore, the proposed BCI system could be a suitable therapy option and will be further assessed in clinical trials.

Prognosis of stroke upper limb recovery with physiological variables using regression tree ensembles.

Objective.This study assesses upper limb recovery prognosis after stroke with solely physiological information, which can provide an objective estimation of recovery.Approach.Clinical recovery was forecasted using EEG-derived Event-Related Desynchronization/Synchronization and coherence, in addition to Transcranial Magnetic Stimulation elicited motor-evoked potentials and upper limb grip and pinch strength. A Regression Tree Ensemble predicted clinical recovery of a stroke database (n= 10) measured after a two-month intervention with the Fugl-Meyer Assessment for the Upper Extremity (FMA-UE) and the Action Research Arm Test (ARAT).Main results.There were no significant differences between predicted and actual outcomes with FMA-UE (p= 0.29) and ARAT (p= 0.5). Median prediction error for FMA-UE and ARAT were of 0.3 (IQR = 6.2) and 3.4 (IQR = 9.4) points, respectively. Predictions with the most pronounced errors were due to an underestimation of high upper limb recovery. The best features for FMA-UE prediction included mostly beta activity over the sensorimotor cortex. Best ARAT prediction features were cortical beta activity, corticospinal tract integrity of the unaffected hemisphere, and upper limb strength.Significance.Results highlighted the importance of measuring cortical activity related to motor control processes, the unaffected hemisphere's integrity, and upper limb strength for prognosis. It was also implied that stroke upper limb recovery prediction is feasible using solely physiological variables with a Regression Tree Ensemble, which can also be used to analyze physiological relationships with recovery.

Longitudinal Analysis of Stroke Patients' Brain Rhythms during an Intervention with a Brain-Computer Interface.

Stroke is a leading cause of motor disability worldwide. Upper limb rehabilitation is particularly challenging since approximately 35% of patients recover significant hand function after 6 months of the stroke's onset. Therefore, new therapies, especially those based on brain-computer interfaces (BCI) and robotic assistive devices, are currently under research. Electroencephalography (EEG) acquired brain rhythms in alpha and beta bands, during motor tasks, such as motor imagery/intention (MI), could provide insight of motor-related neural plasticity occurring during a BCI intervention. Hence, a longitudinal analysis of subacute stroke patients' brain rhythms during a BCI coupled to robotic device intervention was performed in this study. Data of 9 stroke patients were acquired across 12 sessions of the BCI intervention. Alpha and beta event-related desynchronization/synchronization (ERD/ERS) trends across sessions and their association with time since stroke onset and clinical upper extremity recovery were analyzed, using correlation and linear stepwise regression, respectively. More EEG channels presented significant ERD/ERS trends across sessions related with time since stroke onset, in beta, compared to alpha. Linear models implied a moderate relationship between alpha rhythms in frontal, temporal, and parietal areas with upper limb motor recovery and suggested a strong association between beta activity in frontal, central, and parietal regions with upper limb motor recovery. Higher association of beta with both time since stroke onset and upper limb motor recovery could be explained by beta relation with closed-loop communication between the sensorimotor cortex and the paralyzed upper limb, and alpha being probably more associated with motor learning mechanisms. The association between upper limb motor recovery and beta activations reinforces the hypothesis that broader regions of the cortex activate during movement tasks as a compensatory mechanism in stroke patients with severe motor impairment. Therefore, EEG across BCI interventions could provide valuable information for prognosis and BCI cortical activity targets.

[Familiarization to treadmill walking in unimpaired Parkinson's disease patients]. / Familiarización de la marcha en banda sinfin de individuos con enfermedad de Parkinson.

Familiarization to treadmill walking in unimpaired Parkinson's disease (PD) patients is assessed, across multiple treadmill walking sessions. Thirteen PD subjects were enrolled into the study (Eight were in a moderate stage of the disease, and 5 in an advanced stage). PD subjects attended a progressive program consisting of 12 sessions of 20 min. Walking speed, cadence, step length and coefficient of variation were assessed. ANOVA test were used to evaluate progression of disease and time influence over familiarization. PD Subjects baseline characteristics did not differ significantly between both groups and typical dependencies over progression of disease and velocity were found for cadence, step length and coefficient of variation. However, we showed that some PD subjects may require longer familiarization times and that familiarization is an adaptation process which involves parameters as velocity, cadence and gait stability. A better definition of familiarization to treadmill is needed since some parameters such as step length does not change significantly while others such as cadence, coefficient of variation and intraclass correlation coefficient does. Therefore familiarization to treadmill walking should remain on measures of velocity, cadence, reliability and variability. However, a bigger sample size is needed in order to improve the results of the present study.

Evidence-based design and development of a VR-based treadmill system for gait research and rehabilitation of patients with Parkinson's disease.

Virtual reality (VR) in neurorehabilitation allows to reduce patient's risk and allows him to learn on a faster way. Up to now VR has been used in patients with Parkinson disease (PD) as a research tool and none of the developed systems are used in clinical practice. The goal of this project is to develop a VR-based system for gait therapy, and gait research of patients with PD designed based on published evidence. The developed system uses a digital camera to measure spatiotemporal gait parameters. The software was developed in C#, using Open-Source libraries that facilitates VR programming. The system has potential uses in clinical and research settings.