Dan Li, Ruoyu Li, Yunping Song, Wenting Qin, Guangli Sun, Yunxi Liu, Yunjun Bao, Lingyu Liu, Lingjing Jin
{"title":"基于脑机接口的训练对脑卒中后上肢康复的影响：荟萃分析。","authors":"Dan Li, Ruoyu Li, Yunping Song, Wenting Qin, Guangli Sun, Yunxi Liu, Yunjun Bao, Lingyu Liu, Lingjing Jin","doi":"10.1186/s12984-025-01588-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Previous research has used the brain-computer interface (BCI) to promote upper-limb motor rehabilitation. However, the results of these studies were variable, leaving efficacy unclear.</p><p><strong>Objectives: </strong>This review aims to evaluate the effects of BCI-based training on post-stroke upper-limb rehabilitation and identify potential factors that may affect the outcome.</p><p><strong>Design: </strong>A meta-analysis including all available randomized-controlled clinical trials (RCTs) that reported the efficacy of BCI-based training on upper-limb motor rehabilitation after stroke.</p><p><strong>Data sources and methods: </strong>We searched PubMed, Cochrane Library, and Web of Science before September 15, 2024, for relevant studies. The primary efficacy outcome was the Fugl-Meyer Assessment-Upper extremity (FMA-UE). RevMan 5.4.1 with a random effect model was used for data synthesis and analysis. Mean difference (MD) and 95% confidence interval (95%CI) were calculated.</p><p><strong>Results: </strong>Twenty-one RCTs (n = 886 patients) were reviewed in the meta-analysis. Compared with control, BCI-based training exerted significant effects on FMA-UE (MD = 3.69, 95%CI 2.41-4.96, P < 0.00001, moderate-quality evidence), Wolf Motor Function Test (WMFT) (MD = 5.00, 95%CI 2.14-7.86, P = 0.0006, low-quality evidence), and Action Research Arm Test (ARAT) (MD = 2.04, 95%CI 0.25-3.82, P = 0.03, high-quality evidence). Additionally, BCI-based training was effective on FMA-UE for both subacute (MD = 4.24, 95%CI 1.81-6.67, P = 0.0006) and chronic patients (MD = 2.63, 95%CI 1.50-3.76, P < 0.00001). BCI combined with functional electrical stimulation (FES) (MD = 4.37, 95%CI 3.09-5.65, P < 0.00001), robots (MD = 2.87, 95%CI 0.69-5.04, P = 0.010), and visual feedback (MD = 4.46, 95%CI 0.24-8.68, P = 0.04) exhibited significant effects on FMA-UE. BCI combined with FES significantly improved FMA-UE for both subacute (MD = 5.31, 95%CI 2.58-8.03, P = 0.0001) and chronic patients (MD = 3.71, 95%CI 2.44-4.98, P < 0.00001), and BCI combined with robots was effective for chronic patients (MD = 1.60, 95%CI 0.15-3.05, P = 0.03). Better results may be achieved with daily training sessions ranging from 20 to 90 min, conducted 2-5 sessions per week for 3-4 weeks.</p><p><strong>Conclusions: </strong>BCI-based training may be a reliable rehabilitation program to improve upper-limb motor impairment and function.</p><p><strong>Trial registration: </strong>PROSPERO registration ID: CRD42022383390.</p>","PeriodicalId":16384,"journal":{"name":"Journal of NeuroEngineering and Rehabilitation","volume":"22 1","pages":"44"},"PeriodicalIF":5.2000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874405/pdf/","citationCount":"0","resultStr":"{\"title\":\"Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis.\",\"authors\":\"Dan Li, Ruoyu Li, Yunping Song, Wenting Qin, Guangli Sun, Yunxi Liu, Yunjun Bao, Lingyu Liu, Lingjing Jin\",\"doi\":\"10.1186/s12984-025-01588-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Previous research has used the brain-computer interface (BCI) to promote upper-limb motor rehabilitation. However, the results of these studies were variable, leaving efficacy unclear.</p><p><strong>Objectives: </strong>This review aims to evaluate the effects of BCI-based training on post-stroke upper-limb rehabilitation and identify potential factors that may affect the outcome.</p><p><strong>Design: </strong>A meta-analysis including all available randomized-controlled clinical trials (RCTs) that reported the efficacy of BCI-based training on upper-limb motor rehabilitation after stroke.</p><p><strong>Data sources and methods: </strong>We searched PubMed, Cochrane Library, and Web of Science before September 15, 2024, for relevant studies. The primary efficacy outcome was the Fugl-Meyer Assessment-Upper extremity (FMA-UE). RevMan 5.4.1 with a random effect model was used for data synthesis and analysis. Mean difference (MD) and 95% confidence interval (95%CI) were calculated.</p><p><strong>Results: </strong>Twenty-one RCTs (n = 886 patients) were reviewed in the meta-analysis. Compared with control, BCI-based training exerted significant effects on FMA-UE (MD = 3.69, 95%CI 2.41-4.96, P < 0.00001, moderate-quality evidence), Wolf Motor Function Test (WMFT) (MD = 5.00, 95%CI 2.14-7.86, P = 0.0006, low-quality evidence), and Action Research Arm Test (ARAT) (MD = 2.04, 95%CI 0.25-3.82, P = 0.03, high-quality evidence). Additionally, BCI-based training was effective on FMA-UE for both subacute (MD = 4.24, 95%CI 1.81-6.67, P = 0.0006) and chronic patients (MD = 2.63, 95%CI 1.50-3.76, P < 0.00001). BCI combined with functional electrical stimulation (FES) (MD = 4.37, 95%CI 3.09-5.65, P < 0.00001), robots (MD = 2.87, 95%CI 0.69-5.04, P = 0.010), and visual feedback (MD = 4.46, 95%CI 0.24-8.68, P = 0.04) exhibited significant effects on FMA-UE. BCI combined with FES significantly improved FMA-UE for both subacute (MD = 5.31, 95%CI 2.58-8.03, P = 0.0001) and chronic patients (MD = 3.71, 95%CI 2.44-4.98, P < 0.00001), and BCI combined with robots was effective for chronic patients (MD = 1.60, 95%CI 0.15-3.05, P = 0.03). Better results may be achieved with daily training sessions ranging from 20 to 90 min, conducted 2-5 sessions per week for 3-4 weeks.</p><p><strong>Conclusions: </strong>BCI-based training may be a reliable rehabilitation program to improve upper-limb motor impairment and function.</p><p><strong>Trial registration: </strong>PROSPERO registration ID: CRD42022383390.</p>\",\"PeriodicalId\":16384,\"journal\":{\"name\":\"Journal of NeuroEngineering and Rehabilitation\",\"volume\":\"22 1\",\"pages\":\"44\"},\"PeriodicalIF\":5.2000,\"publicationDate\":\"2025-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11874405/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of NeuroEngineering and Rehabilitation\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1186/s12984-025-01588-x\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of NeuroEngineering and Rehabilitation","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1186/s12984-025-01588-x","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
Effects of brain-computer interface based training on post-stroke upper-limb rehabilitation: a meta-analysis.
Background: Previous research has used the brain-computer interface (BCI) to promote upper-limb motor rehabilitation. However, the results of these studies were variable, leaving efficacy unclear.
Objectives: This review aims to evaluate the effects of BCI-based training on post-stroke upper-limb rehabilitation and identify potential factors that may affect the outcome.
Design: A meta-analysis including all available randomized-controlled clinical trials (RCTs) that reported the efficacy of BCI-based training on upper-limb motor rehabilitation after stroke.
Data sources and methods: We searched PubMed, Cochrane Library, and Web of Science before September 15, 2024, for relevant studies. The primary efficacy outcome was the Fugl-Meyer Assessment-Upper extremity (FMA-UE). RevMan 5.4.1 with a random effect model was used for data synthesis and analysis. Mean difference (MD) and 95% confidence interval (95%CI) were calculated.
Results: Twenty-one RCTs (n = 886 patients) were reviewed in the meta-analysis. Compared with control, BCI-based training exerted significant effects on FMA-UE (MD = 3.69, 95%CI 2.41-4.96, P < 0.00001, moderate-quality evidence), Wolf Motor Function Test (WMFT) (MD = 5.00, 95%CI 2.14-7.86, P = 0.0006, low-quality evidence), and Action Research Arm Test (ARAT) (MD = 2.04, 95%CI 0.25-3.82, P = 0.03, high-quality evidence). Additionally, BCI-based training was effective on FMA-UE for both subacute (MD = 4.24, 95%CI 1.81-6.67, P = 0.0006) and chronic patients (MD = 2.63, 95%CI 1.50-3.76, P < 0.00001). BCI combined with functional electrical stimulation (FES) (MD = 4.37, 95%CI 3.09-5.65, P < 0.00001), robots (MD = 2.87, 95%CI 0.69-5.04, P = 0.010), and visual feedback (MD = 4.46, 95%CI 0.24-8.68, P = 0.04) exhibited significant effects on FMA-UE. BCI combined with FES significantly improved FMA-UE for both subacute (MD = 5.31, 95%CI 2.58-8.03, P = 0.0001) and chronic patients (MD = 3.71, 95%CI 2.44-4.98, P < 0.00001), and BCI combined with robots was effective for chronic patients (MD = 1.60, 95%CI 0.15-3.05, P = 0.03). Better results may be achieved with daily training sessions ranging from 20 to 90 min, conducted 2-5 sessions per week for 3-4 weeks.
Conclusions: BCI-based training may be a reliable rehabilitation program to improve upper-limb motor impairment and function.
期刊介绍：
Journal of NeuroEngineering and Rehabilitation considers manuscripts on all aspects of research that result from cross-fertilization of the fields of neuroscience, biomedical engineering, and physical medicine & rehabilitation.
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