Effects of virtual reality in improving upper extremity function after stroke: A systematic review and meta-analysis of randomized controlled trials

Jin, Minxia; Pei, Junjie; Bai, Zhongfei; Zhang, Jiaqi; He, Ting; Xu, Xiaojing; Zhu, Feifei; Yu, Dan; Zhang, Ziwei

doi:10.1177/02692155211066534

Cited by 22 publications

(22 citation statements)

References 73 publications

(177 reference statements)

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“…Our findings clearly demonstrate that BMI-based training shows greater SMD compared to widely used treatments such as CIMT [SMD = 0.557; 95% CI (0.301, 0.813); p < 0.001] (Etoom et al, 2016 ), mirror therapy [SMD = 0.51; 95% CI (0.29, 0.73); p < 0.00001] (Zeng et al, 2018 ), motor imagery [SMD = 0.36; 95% CI (0.16, 0.55); p = 0.0004] (Guerra et al, 2017 ), supporting its clinical application. Furthermore, it has comparable or significant efficacy compared to other novel rehabilitation techniques such as robot-assisted therapy [SMD = 0.25; 95% CI (0.11, 0.38); p = 0.000] (Wu et al, 2021 ), and virtual reality-based therapy [SMD = 0.42; 95% CI (0.17, 0.67); p = 0.00] (Jin et al, 2022 ). The main source of heterogeneity in this meta-analysis was Wu et al ( 2019 ), which investigated the clinical efficacy of BMI-baesd training and changes in functional brain networks.…”

Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

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

et al. 2022

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“…Otherwise, the fixed-effects model was selected. 16 The level of the meta-analysis was set at α = 0.05. If there was significant clinical heterogeneity, methods such as subgroup analysis or sensitivity analysis were used to treat it, otherwise only descriptive analysis was performed.…”

Section: Methodsmentioning

confidence: 99%

Effects of dual-task training on gait and balance in stroke patients: A meta-analysis

Zhang

Shi

et al. 2022

Clin Rehabil

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Objective To assess the effects of dual-task training on gait and balance in stroke patients. Data sources: A systematic review of PubMed, Web of Science, Embase and Cochrane Library from their inception through 20 August 2021. Review methods The bibliography was screened to identify randomized controlled trials that applied dual-task training to rehabilitation function training in stroke patients. Two reviewers independently screened references, selected relevant studies, extracted data and assessed risk of bias using the Cochrane tool of bias. The primary outcome was the gait and balance parameters. Results A total of 1992 studies were identified and 15 randomized controlled trials were finally included (512 individuals) were analyzed. A meta-analysis was performed and a beneficial effect on rehabilitation training was found. Compared to patients who received conventional rehabilitation therapy, those who received dual-task training showed greater improvement in step length (MD = 3.46, 95% CI [1.01, 5.92], P = 0.006), cadence (MD = 4.92, 95% CI [3.10, 6.74], P < 0.001) and berg balance scale score (MD = 3.10, 95% CI [0.11, 6.09], P = 0.040). There were no differences in the improvements in gait speed (MD = 2.89, 95% CI [ − 2.02, 7.80], P = 0.250) and timed up and go test (MD = −2.62, 95% CI [ − 7.94, 2.71], P = 0.340) between dual-task and control groups. Conclusion Dual-task training is an effective training for rehabilitation of stroke patients in step length and cadence, however, the superiority of dual-task training for improving balance function needs further discussion.

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“…Virtual reality (VR) has been defined as “the computer-generated simulation of a three-dimensional image or environment that can be interacted with in a seemingly real or physical way by a person using special electronic equipment, such as a helmet with a screen inside or gloves fitted with sensors” ( 54 ). Active ingredients that likely play a role are immersive vs. non-immersive VR experience ( 55 ); the therapeutic content of the exercise, i.e., being specifically designed for neurorehabilitation purposes ( 56 ); the type of feedback being provided (explicit and/or implicit feedback) ( 57 ); and the integration of multisensory stimuli (visual, auditory, haptic) ( 15 ).…”

Section: Interventions Providing Feedback and Multisensory Stimulatio...mentioning

confidence: 99%

Time to reconcile research findings and clinical practice on upper limb neurorehabilitation

et al. 2022

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The problemIn the field of upper limb neurorehabilitation, the translation from research findings to clinical practice remains troublesome. Patients are not receiving treatments based on the best available evidence. There are certainly multiple reasons to account for this issue, including the power of habit over innovation, subjective beliefs over objective results. We need to take a step forward, by looking at most important results from randomized controlled trials, and then identify key active ingredients that determined the success of interventions. On the other hand, we need to recognize those specific categories of patients having the greatest benefit from each intervention, and why. The aim is to reach the ability to design a neurorehabilitation program based on motor learning principles with established clinical efficacy and tailored for specific patient's needs.Proposed solutionsThe objective of the present manuscript is to facilitate the translation of research findings to clinical practice. Starting from a literature review of selected neurorehabilitation approaches, for each intervention the following elements were highlighted: definition of active ingredients; identification of underlying motor learning principles and neural mechanisms of recovery; inferences from research findings; and recommendations for clinical practice. Furthermore, we included a dedicated chapter on the importance of a comprehensive assessment (objective impairments and patient's perspective) to design personalized and effective neurorehabilitation interventions.ConclusionsIt's time to reconcile research findings with clinical practice. Evidence from literature is consistently showing that neurological patients improve upper limb function, when core strategies based on motor learning principles are applied. To this end, practical take-home messages in the concluding section are provided, focusing on the importance of graded task practice, high number of repetitions, interventions tailored to patient's goals and expectations, solutions to increase and distribute therapy beyond the formal patient-therapist session, and how to integrate different interventions to maximize upper limb motor outcomes. We hope that this manuscript will serve as starting point to fill the gap between theory and practice in upper limb neurorehabilitation, and as a practical tool to leverage the positive impact of clinicians on patients' recovery.

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Effects of virtual reality in improving upper extremity function after stroke: A systematic review and meta-analysis of randomized controlled trials

Cited by 22 publications

References 73 publications

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

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

Effects of dual-task training on gait and balance in stroke patients: A meta-analysis

Time to reconcile research findings and clinical practice on upper limb neurorehabilitation

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