Effect of brain-computer interface training based on non-invasive electroencephalography using motor imagery on functional recovery after stroke - a systematic review and meta-analysis.


Journal

BMC neurology
ISSN: 1471-2377
Titre abrégé: BMC Neurol
Pays: England
ID NLM: 100968555

Informations de publication

Date de publication:
22 Oct 2020
Historique:
received: 21 04 2020
accepted: 14 10 2020
entrez: 23 10 2020
pubmed: 24 10 2020
medline: 1 12 2020
Statut: epublish

Résumé

Training with brain-computer interface (BCI) technology in the rehabilitation of patients after a stroke is rapidly developing. Numerous RCT investigated the effects of BCI training (BCIT) on recovery of motor and brain function in patients after stroke. A systematic literature search was performed in Medline, IEEE Xplore Digital Library, Cochrane library, and Embase in July 2018 and was repeated in March 2019. RCT or controlled clinical trials that included BCIT for improving motor and brain recovery in patients after a stroke were identified. Data were meta-analysed using the random-effects model. Standardized mean difference (SMD) with 95% confidence (95%CI) and 95% prediction interval (95%PI) were calculated. A meta-regression was performed to evaluate the effects of covariates on the pooled effect-size. In total, 14 studies, including 362 patients after ischemic and hemorrhagic stroke (cortical, subcortical, 121 females; mean age 53.0+/- 5.8; mean time since stroke onset 15.7+/- 18.2 months) were included. Main motor recovery outcome measure used was the Fugl-Meyer Assessment. Quantitative analysis showed that a BCI training compared to conventional therapy alone in patients after stroke was effective with an SMD of 0.39 (95%CI: 0.17 to 0.62; 95%PI of 0.13 to 0.66) for motor function recovery of the upper extremity. An SMD of 0.41 (95%CI: - 0.29 to 1.12) for motor function recovery of the lower extremity was found. BCI training enhanced brain function recovery with an SMD of 1.11 (95%CI: 0.64 to 1.59; 95%PI ranging from 0.33 to 1.89). Covariates such as training duration, impairment level of the upper extremity, and the combination of both did not show significant effects on the overall pooled estimate. This meta-analysis showed evidence that BCI training added to conventional therapy may enhance motor functioning of the upper extremity and brain function recovery in patients after a stroke. We recommend a standardised evaluation of motor imagery ability of included patients and the assessment of brain function recovery should consider neuropsychological aspects (attention, concentration). Further influencing factors on motor recovery due to BCI technology might consider factors such as age, lesion type and location, quality of performance of motor imagery, or neuropsychological aspects. PROSPERO registration: CRD42018105832 .

Sections du résumé

BACKGROUND BACKGROUND
Training with brain-computer interface (BCI) technology in the rehabilitation of patients after a stroke is rapidly developing. Numerous RCT investigated the effects of BCI training (BCIT) on recovery of motor and brain function in patients after stroke.
METHODS METHODS
A systematic literature search was performed in Medline, IEEE Xplore Digital Library, Cochrane library, and Embase in July 2018 and was repeated in March 2019. RCT or controlled clinical trials that included BCIT for improving motor and brain recovery in patients after a stroke were identified. Data were meta-analysed using the random-effects model. Standardized mean difference (SMD) with 95% confidence (95%CI) and 95% prediction interval (95%PI) were calculated. A meta-regression was performed to evaluate the effects of covariates on the pooled effect-size.
RESULTS RESULTS
In total, 14 studies, including 362 patients after ischemic and hemorrhagic stroke (cortical, subcortical, 121 females; mean age 53.0+/- 5.8; mean time since stroke onset 15.7+/- 18.2 months) were included. Main motor recovery outcome measure used was the Fugl-Meyer Assessment. Quantitative analysis showed that a BCI training compared to conventional therapy alone in patients after stroke was effective with an SMD of 0.39 (95%CI: 0.17 to 0.62; 95%PI of 0.13 to 0.66) for motor function recovery of the upper extremity. An SMD of 0.41 (95%CI: - 0.29 to 1.12) for motor function recovery of the lower extremity was found. BCI training enhanced brain function recovery with an SMD of 1.11 (95%CI: 0.64 to 1.59; 95%PI ranging from 0.33 to 1.89). Covariates such as training duration, impairment level of the upper extremity, and the combination of both did not show significant effects on the overall pooled estimate.
CONCLUSION CONCLUSIONS
This meta-analysis showed evidence that BCI training added to conventional therapy may enhance motor functioning of the upper extremity and brain function recovery in patients after a stroke. We recommend a standardised evaluation of motor imagery ability of included patients and the assessment of brain function recovery should consider neuropsychological aspects (attention, concentration). Further influencing factors on motor recovery due to BCI technology might consider factors such as age, lesion type and location, quality of performance of motor imagery, or neuropsychological aspects.
TRIAL REGISTRATION BACKGROUND
PROSPERO registration: CRD42018105832 .

Identifiants

pubmed: 33092554
doi: 10.1186/s12883-020-01960-5
pii: 10.1186/s12883-020-01960-5
pmc: PMC7584076
doi:

Types de publication

Journal Article Meta-Analysis Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

385

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Auteurs

Antje Kruse (A)

Department of Health Professions, Bern University Applied Science, Schwarztorstrasse 48, 3007, Bern, Switzerland.
Private Practice, Baslerstrasse 60, 4102, Binningen, Switzerland.

Zorica Suica (Z)

Research Department, Reha Rheinfelden, Salinenstrasse 98, 4310, Rheinfelden, Switzerland.

Jan Taeymans (J)

Department of Health Professions, Bern University Applied Science, Schwarztorstrasse 48, 3007, Bern, Switzerland.
Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium.

Corina Schuster-Amft (C)

Research Department, Reha Rheinfelden, Salinenstrasse 98, 4310, Rheinfelden, Switzerland. c.schuster@reha-rhf.ch.
Department of Engineering and Information Technology, Pestalozzistrasse 20, 3401, Burgdorf, Switzerland. c.schuster@reha-rhf.ch.
Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320 B, 4052, Basel, Switzerland. c.schuster@reha-rhf.ch.

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