Brain–Computer Interface Training Based on Brain Activity Can Induce Motor Recovery in Patients With Stroke: A Meta-Analysis

Abstract

Background Brain–computer interface (BCI) is a procedure involving brain activity in which neural status is provided to the participants for self-regulation. The current review aims to evaluate the effect sizes of clinical studies investigating the use of BCI-based rehabilitation interventions in restoring upper extremity function and effective methods to detect brain activity for motor recovery. Methods A computerized search of MEDLINE, CENTRAL, Web of Science, and PEDro was performed to identify relevant articles. We selected clinical trials that used BCI-based training for post-stroke patients and provided motor assessment scores before and after the intervention. The pooled standardized mean differences of BCI-based training were calculated using the random-effects model. Results We initially identified 655 potentially relevant articles; finally, 16 articles fulfilled the inclusion criteria, involving 382 participants. A significant effect of neurofeedback intervention for the paretic upper limb was observed (standardized mean difference = .48, [.16-.80], P = .006). However, the effect estimates were moderately heterogeneous among the studies ( I2 = 45%, P = .03). Subgroup analysis of the method of measurement of brain activity indicated the effectiveness of the algorithm focusing on sensorimotor rhythm. Conclusion This meta-analysis suggested that BCI-based training was superior to conventional interventions for motor recovery of the upper limbs in patients with stroke. However, the results are not conclusive because of a high risk of bias and a large degree of heterogeneity due to the differences in the BCI interventions and the participants; therefore, further studies involving larger cohorts are required to confirm these results.

Modulating Frustration and Agency Using Fabricated Input for Motor Imagery BCIs in Stroke Rehabilitation

“…Several studies have shown that these control signals can be detected from single-trial EEG in able-bodied and stroke individuals with input recognition rates roughly around 70-80%, but with higher input recognition rates for able-bodied individuals compared to stroke patients [20], [21]. BCIcontrolled rehabilitation robots and electrical stimulation can effectively improve motor function in stroke patients [2], [4], [22], [23]. However, the experiments have often been performed under controlled conditions with BCI experienced researchers.…”

Sensorimotor Rhythm-Brain Computer Interface With Audio-Cue, Motor Observation and Multisensory Feedback for Upper-Limb Stroke Rehabilitation: A Controlled Study

“…BCI training added to conventional therapy may enhance motor functioning of the upper extremity and brain function recovery in patients after a stroke ( Kruse et al, 2020 ). Compared to conventional interventions, we suggest BCI-based training for motor recovery of the upper limbs in patients with stroke ( Nojima et al, 2021 ).…”

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

“…However, the controversy surrounding the effectiveness of BMI-based training for post-stroke upper extremity dysfunction persists due to the different types of experimental clinical studies and the wide variation in the quality of the literature. In recent years, although some meta-analyses have investigated the effect of BMI-based training on upper limb motor function after stroke (Cervera et al, 2018 ; Bai et al, 2020 ; Yang W. et al, 2021 ; Mansour et al, 2022 ; Nojima et al, 2022 ), there are limitations such as the small sample size included in the study and the failure to provide a level of evidence. In addition, we found data extraction errors in a study analyzing the efficacy of BMI in different stroke stages (Yang W. et al, 2021 ).…”