Brain-machine interface-based training for improving upper extremity function after stroke: A meta-analysis of randomized controlled trials

Abstract

BackgroundUpper extremity dysfunction after stroke is an urgent clinical problem that greatly affects patients' daily life and reduces their quality of life. As an emerging rehabilitation method, brain-machine interface (BMI)-based training can extract brain signals and provide feedback to form a closed-loop rehabilitation, which is currently being studied for functional restoration after stroke. However, there is no reliable medical evidence to support the effect of BMI-based training on upper extremity function after stroke. This review aimed to evaluate the efficacy and safety of BMI-based training for improving upper extremity function after stroke, as well as potential differences in efficacy of different external devices.MethodsEnglish-language literature published before April 1, 2022, was searched in five electronic databases using search terms including “brain-computer/machine interface”, “stroke” and “upper extremity.” The identified articles were screened, data were extracted, and the methodological quality of the included trials was assessed. Meta-analysis was performed using RevMan 5.4.1 software. The GRADE method was used to assess the quality of the evidence.ResultsA total of 17 studies with 410 post-stroke patients were included. Meta-analysis showed that BMI-based training significantly improved upper extremity motor function [standardized mean difference (SMD) = 0.62; 95% confidence interval (CI) (0.34, 0.90); I2 = 38%; p < 0.0001; n = 385; random-effects model; moderate-quality evidence]. Subgroup meta-analysis indicated that BMI-based training significantly improves upper extremity motor function in both chronic [SMD = 0.68; 95% CI (0.32, 1.03), I2 = 46%; p = 0.0002, random-effects model] and subacute [SMD = 1.11; 95%CI (0.22, 1.99); I2 = 76%; p = 0.01; random-effects model] stroke patients compared with control interventions, and using functional electrical stimulation (FES) [SMD = 1.11; 95% CI (0.67, 1.54); I2 = 11%; p < 0.00001; random-effects model]or visual feedback [SMD = 0.66; 95% CI (0.2, 1.12); I2 = 4%; p = 0.005; random-effects model;] as the feedback devices in BMI training was more effective than using robot. In addition, BMI-based training was more effective in improving patients' activities of daily living (ADL) than control interventions [SMD = 1.12; 95% CI (0.65, 1.60); I2 = 0%; p < 0.00001; n = 80; random-effects model]. There was no statistical difference in the dropout rate and adverse effects between the BMI-based training group and the control group.ConclusionBMI-based training improved upper limb motor function and ADL in post-stroke patients. BMI combined with FES or visual feedback may be a better combination for functional recovery than robot. BMI-based trainings are well-tolerated and associated with mild adverse effects.

Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review

“…The majority turned out to be literatures reviews on Assistive BCI systems. Due to the large quantity of review articles, the authors combined all the review articles' (Cervera et al, 2018 ; Bai et al, 2020 ; Kruse et al, 2020 ; Baniqued et al, 2021 ; Behboodi et al, 2022 ; Mansour et al, 2022 ; Peng et al, 2022 ; Xie et al, 2022 ) studies/reports. The eight literature reviews produced 32 unique research articles that were within the scope of this sub-review, and they are described in Supplementary Table V .…”

“…These studies have small sample sizes, short intervention durations, and interpretation difficulty of results due to many factors (e.g., severity of stroke, acuity of stroke, protocol of the intervention, etc. ), which leads to a lack of evidence in proving the effectiveness of these systems and discourages medical companies and hospitals from using them in their routine treatments (Mcconnell et al, 2017 ; Hu et al, 2022 ; Xie et al, 2022 ).…”

Acupuncture combined with balloon dilation for post-stroke cricopharyngeal achalasia: A meta-analysis of randomized controlled trials

“…After the stroke, the patient's brain structure and connectivity have changed. Related studies have found that, the plasticity of the brain provides a basis for rehabilitation after stroke (Xie et al, 2022 ), as time goes on, the brain tissue has a certain ability to repair itself (Hermann and Chopp, 2012 ). Acupuncture combined with balloon dilatation may promote this compensation and repair mechanism, and reorganize the brain function of stroke patients (Zhang et al, 2021 ), thus improving swallowing function, promoting rapid recovery of patients, and shortening the disease's course.…”

Sensorimotor Rhythm-Based Brain–Computer Interfaces for Motor Tasks Used in Hand Upper Extremity Rehabilitation after Stroke: A Systematic Review

“…They mainly analyzed robot, FES, and visual feedback, and the results indicated that only BCIs triggering the stimulation of FES had a significantly larger effect size on motor function recovery, compared with control interventions. In Xie's meta-analysis [48], they considered BCI combined with FES or visual feedback may be a better combination for functional recovery than a robot.…”