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

Abstract

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.

Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis

“…A total of 1015 records were screened, of which the full texts of 80 were assessed for eligibility. Finally, 33 studies were included in the current systematic review [6, 7, 15-17, 26, 35, 37, 46, 47, 49-71], of which 18 studies were of single-group design [26,37,[56][57][58][59][60][61][62][63][64][65][66][67][68][69][70][71], and 15 studies were of controlled-trial design [6, 7, 15-17, 35, 46, 47, 49-55]. In the current review, only studies with a controlled-trial design were included in our metaanalysis, and those with single-group designs were only included in our qualitative description.…”

“…In particular, the average duration since stroke onset indicated that the subjects were at chronic stages, and so improvements in motor function were less likely to be caused by spontaneous recovery. In those single-group studies in which statistical analysis had not been performed, most likely due to the small sample size, descriptive statistics indicated that the majority of subjects benefited from the BCI treatment [26,37,58,60,62,65,69]. However, Buch et al [56] found that six out of eight subjects could volitionally control the BCI system via the ERD of the mu rhythm, whereas there was no significant improvement in residual finger extension, as measured by the Medical Research Council Scale, after 13 to 22 training sessions.…”

Brain-Computer Interface Robotics for Hand Rehabilitation After Stroke: A Systematic Review

“…A final list with 30 studies was identified as eligible for qualitative review. Among the 30 studies, 11 [60][61][62][63][64][65][66][67][68][69][70] were involved in testing the BCI-hand robot system on chronic and subacute stroke patients ( [60,65] are RCTs) while the rest involved testing on healthy participants [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89].…”

“…One study [60] reported a 3-armed RCT with control groups as device-only and SAT while another study [65] was a multi-centre RCT with sham as the control group. Five studies were uncontrolledwhere the aims were either to study classification accuracies during sessions [61], to monitor clinical outcomes improvement from Day 0 until the end of the programme [62,70] or both [64,67]. Two studies [68,69] For the studies that had a clinical testing component, a methodological quality assessment by the PEDro Scale was performed.…”

“…Another study[63] compared the classification accuracies of healthy and hemiplegic stroke patients against two BCI classifiers while the remaining study[66] compared classification accuracies from stroke patients who receive congruent or incongruent visual and kinaesthetic feedback.Most of the studies adopted FMMA, ARAT and GS measurements to assess clinical outcomes. Six studies[60,62,64,65,68,70] reported patient improvement in these measures when subjected to BCI-hand robot interventions; in contrast with their respective controls or as recorded through time in the programme. For Ang et al[60], FMMA Distal scores were reported in weeks 3, 6, 12 and 24 and the BCI-device group (N=6) yielded the highest improvement in scores across all time points as compared to the device only (N=8) and SAT (N=7) groups.…”