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Meta-Analysis
. 2022 Jan;53(1):79-90.
doi: 10.1177/15500594211009065. Epub 2021 Apr 29.

Efficacy of Brain-Computer Interface and the Impact of Its Design Characteristics on Poststroke Upper-limb Rehabilitation: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Affiliations

Affiliations

  • 1 Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
  • 2 54759Agency for Science Technology and Research, Institute for Infocomm Research, Singapore, Singapore.
  • 3 School of Computer Science and Engineering, Nanyang Technological University, Singapore.
Meta-Analysis

Efficacy of Brain-Computer Interface and the Impact of Its Design Characteristics on Poststroke Upper-limb Rehabilitation: A Systematic Review and Meta-analysis of Randomized Controlled Trials

Salem Mansour et al. Clin EEG Neurosci. 2022 Jan.
. 2022 Jan;53(1):79-90.
doi: 10.1177/15500594211009065. Epub 2021 Apr 29.

Affiliations

  • 1 Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
  • 2 54759Agency for Science Technology and Research, Institute for Infocomm Research, Singapore, Singapore.
  • 3 School of Computer Science and Engineering, Nanyang Technological University, Singapore.

Abstract

Background. A number of recent randomized controlled trials reported the efficacy of brain-computer interface (BCI) for upper-limb stroke rehabilitation compared with other therapies. Despite the encouraging results reported, there is a significant variance in the reported outcomes. This paper aims to investigate the effectiveness of different BCI designs on poststroke upper-limb rehabilitation. Methods. The effect sizes of pooled and individual studies were assessed by computing Hedge's g values with a 95% confidence interval. Subgroup analyses were also performed to examine the impact of different BCI designs on the treatment effect. Results. The study included 12 clinical trials involving 298 patients. The analysis showed that the BCI yielded significant superior short-term and long-term efficacy in improving the upper-limb motor function compared to the control therapies (Hedge's g = 0.73 and 0.33, respectively). Based on our subgroup analyses, the BCI studies that used the intention of movement had a higher effect size compared to those used motor imagery (Hedge's g = 1.21 and 0.55, respectively). The BCI studies using band power features had a significantly higher effect size than those using filter bank common spatial patterns features (Hedge's g = 1.25 and - 0.23, respectively). Finally, the studies that used functional electrical stimulation as the BCI feedback had the highest effect size compared to other devices (Hedge's g = 1.2). Conclusion. This meta-analysis confirmed the effectiveness of BCI for upper-limb rehabilitation. Our findings support the use of band power features, the intention of movement, and the functional electrical stimulation in future BCI designs for poststroke upper-limb rehabilitation.

Keywords: brain–computer interface; mental tasks; meta-analysis; randomized clinical trials; stroke rehabilitation.

PubMed Disclaimer

Conflict of interest statement

Declaration of Conflicting Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.

Figure 1.

Components of brain–computer interface commonly…

Figure 1.

Components of brain–computer interface commonly used for upper-limb stroke rehabilitation.

Figure 1.
Components of brain–computer interface commonly used for upper-limb stroke rehabilitation.
Figure 2.

Figure 2.

Preferred reporting items for systematic…

Figure 2.

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flowchart illustrating the process…

Figure 2.
Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flowchart illustrating the process for the selection of the included studies in this meta-analysis.
Figure 3.

Figure 3.

Evaluating effects of brain–computer interface,…

Figure 3.

Evaluating effects of brain–computer interface, compared to control interventions, in improving upper-limb motor…

Figure 3.
Evaluating effects of brain–computer interface, compared to control interventions, in improving upper-limb motor functions after stroke: (A) assessed immediately after finishing the intervention and (B) assessed in the follow-up session a number of weeks after finishing the intervention.
Figure 4.

Figure 4.

(A) A subgroup meta-analysis comparing…

Figure 4.

(A) A subgroup meta-analysis comparing the efficacy of brain–computer interface in improving upper-limb…

Figure 4.
(A) A subgroup meta-analysis comparing the efficacy of brain–computer interface in improving upper-limb motor functions, between 2 different phases of stroke. (B) A subgroup meta-analysis comparing the efficacy of brain–computer interfaces with different mental practices on poststroke upper-limb motor recovery; (ie, motor imagery vs intention of movement).
Figure 5.

Figure 5.

A subgroup meta-analysis comparing the…

Figure 5.

A subgroup meta-analysis comparing the efficacy of brain–computer interface, grouped based on different…

Figure 5.
A subgroup meta-analysis comparing the efficacy of brain–computer interface, grouped based on different classification features, on poststroke upper-limb motor recovery.
Figure 6.

Figure 6.

A subgroup meta-analysis comparing the…

Figure 6.

A subgroup meta-analysis comparing the efficacy of brain–computer interface, grouped based on different…

Figure 6.
A subgroup meta-analysis comparing the efficacy of brain–computer interface, grouped based on different types of feedbacks, on poststroke upper-limb recovery.

References

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