Literature DB >> 33913351

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 Mansour1, Kai Keng Ang2,3, Krishnan P S Nair3, Kok Soon Phua2, Mahnaz Arvaneh1.   

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.

Entities:  

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

Year:  2021        PMID: 33913351     DOI: 10.1177/15500594211009065

Source DB:  PubMed          Journal:  Clin EEG Neurosci        ISSN: 1550-0594            Impact factor:   1.843


  3 in total

Review 1.  Toward an Adapted Neurofeedback for Post-stroke Motor Rehabilitation: State of the Art and Perspectives.

Authors:  Salomé Le Franc; Gabriela Herrera Altamira; Maud Guillen; Simon Butet; Stéphanie Fleck; Anatole Lécuyer; Laurent Bougrain; Isabelle Bonan
Journal:  Front Hum Neurosci       Date:  2022-07-14       Impact factor: 3.473

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

Authors:  Yu-Lei Xie; Yu-Xuan Yang; Hong Jiang; Xing-Yu Duan; Li-Jing Gu; Wu Qing; Bo Zhang; Yin-Xu Wang
Journal:  Front Neurosci       Date:  2022-08-03       Impact factor: 5.152

3.  Exploring the ability of stroke survivors in using the contralesional hemisphere to control a brain-computer interface.

Authors:  Salem Mansour; Joshua Giles; Kai Keng Ang; Krishnan P S Nair; Kok Soon Phua; Mahnaz Arvaneh
Journal:  Sci Rep       Date:  2022-09-28       Impact factor: 4.996

  3 in total

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