Evidence map›Paper›PMID 33485365›Full record

SynthesisJournal of neuroengineering and rehabilitation2021

Brain-computer interface robotics for hand rehabilitation after stroke: a systematic review.

Paul Dominick E Baniqued, Emily C Stanyer, Muhammad Awais, Ali Alazmani, Andrew E Jackson, Mark A Mon-Williams, Faisal Mushtaq, Raymond J Holt

Registry-linked trialOpen access · goldAbstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07435688 (Comparison of The Effectiveness Of Mirror Therapy And Mirror Mode of a Hand Robot in Upper Extremity Motor Recovery After Stroke), which is not on this map. Cited by 87 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 11 pooled it
17.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07435688 nacompletednot on this mapstarted 2024, after this paper: background citation

Comparison of The Effectiveness Of Mirror Therapy And Mirror Mode of a Hand Robot in Upper Extremity Motor Recovery After Stroke

TypeinterventionalSponsorZeynep Lide UzRan2024 to 2024Enrolled30ConditionsStroke, Ischemic, Stroke, CVA (Cerebrovascular Accident)ArmsHand Robot Mirror Mode, Therapy Mirror
3 · Its place in the literature

Who cites it

87 citing papers in PubMed, 11 syntheses or guidelines pooled it, 218 citations in OpenAlex.

  1. Pooled it
  2. Efficacy of digital health technologies as adjunctive functional training in occupational therapy for stroke rehabilitation: a meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
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27 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 1 institution in 1 country.

Paul Dominick E BaniquedSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.ORCID 0000-0001-7141-8330
Emily C StanyerSchool of Psychology, University of Leeds, Leeds, LS2 9JZ, UK.
Muhammad AwaisSchool of Psychology, University of Leeds, Leeds, LS2 9JZ, UK.
Ali AlazmaniSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.
Andrew E JacksonSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.
Mark A Mon-WilliamsSchool of Psychology, University of Leeds, Leeds, LS2 9JZ, UK.
Faisal MushtaqSchool of Psychology, University of Leeds, Leeds, LS2 9JZ, UK. f.mushtaq@leeds.ac.uk.
Raymond J HoltSchool of Mechanical Engineering, University of Leeds, Leeds, LS2 9JT, UK.
University of Leeds · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHand rehabilitation is core to helping stroke survivors regain activities of daily living. Recent studies have suggested that the use of electroencephalography-based brain-computer interfaces (BCI) can promote this process. Here, we report the first systematic examination of the literature on the use of BCI-robot systems for the rehabilitation of fine motor skills associated with hand movement and profile these systems from a technical and clinical perspective.

methodsA search for January 2010-October 2019 articles using Ovid MEDLINE, Embase, PEDro, PsycINFO, IEEE Xplore and Cochrane Library databases was performed. The selection criteria included BCI-hand robotic systems for rehabilitation at different stages of development involving tests on healthy participants or people who have had a stroke. Data fields include those related to study design, participant characteristics, technical specifications of the system, and clinical outcome measures.

results30 studies were identified as eligible for qualitative review and among these, 11 studies involved testing a BCI-hand robot on chronic and subacute stroke patients. Statistically significant improvements in motor assessment scores relative to controls were observed for three BCI-hand robot interventions. The degree of robot control for the majority of studies was limited to triggering the device to perform grasping or pinching movements using motor imagery. Most employed a combination of kinaesthetic and visual response via the robotic device and display screen, respectively, to match feedback to motor imagery.

conclusion19 out of 30 studies on BCI-robotic systems for hand rehabilitation report systems at prototype or pre-clinical stages of development. We identified large heterogeneity in reporting and emphasise the need to develop a standard protocol for assessing technical and clinical outcomes so that the necessary evidence base on efficiency and efficacy can be developed.

Indexed as

Brain-Computer InterfacesActivities of Daily LivingFemaleHandHumansMaleMiddle AgedMotor SkillsRoboticsStroke RehabilitationBrain–computer interfaceEEGMotor imageryRehabilitationRoboticsStroke

Identifiers

PMID33485365
PMCPMC7825186
OpenAlexW3122597721

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.