Evidence map›Paper›PMID 30894192›Full record

Trial reportJournal of neuroengineering and rehabilitation2019

Boosting robot-assisted rehabilitation of stroke hemiparesis by individualized selection of upper limb movements - a pilot study.

Orna Rosenthal, Alan M Wing, Jeremy L Wyatt, David Punt, Briony Brownless, Chit Ko-Ko, R Christopher Miall

Erratum issuedOpen access · goldAbstract readClinical Trial
In one paragraph

Trial report in Journal of neuroengineering and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 16 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 3 pooled it
3.2field-weighted citation impact, top 9% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 3 syntheses or guidelines pooled it, 31 citations in OpenAlex.

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  11. Moving towards precision neurological rehabilitation: a mandatory path to follow in the era of precision neurology.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
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  14. JNER at 15 years: analysis of the state of neuroengineering and rehabilitation.Journal of neuroengineering and rehabilitation · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Orna RosenthalSchool of Psychology, University of Birmingham, B15 2TT, Birmingham, UK. o.rosenthal.bham@gmail.com.ORCID 0000-0002-4259-8878
Alan M WingSchool of Psychology, University of Birmingham, B15 2TT, Birmingham, UK.
Jeremy L WyattSchool of Computer Science, University of Birmingham, B15 2TT, Birmingham, UK.
David PuntSchool of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, B15 2TT, Birmingham, UK.
Briony BrownlessSchool of Psychology, University of Birmingham, B15 2TT, Birmingham, UK.
Chit Ko-KoWest Midlands Rehabilitation Centre, Birmingham, B29 6JA, UK.
R Christopher MiallSchool of Psychology, University of Birmingham, B15 2TT, Birmingham, UK.
University of Birmingham · GB

Funding

Medical Research Council MC_PC_15032Medical Research Council MR/J012610/1Wellcome TrustWellcome Trust 105611-Z-14-ZWellcome Trust WT087554
6 · The paper itself

Abstract

backgroundIntensive robot-assisted training of the upper limb after stroke can reduce motor impairment, even at the chronic stage. However, the effectiveness of practice for recovery depends on the selection of the practised movements. We hypothesized that rehabilitation can be optimized by selecting the movements to be practiced based on the trainee's performance profile.

methodsWe present a novel principle ('steepest gradients') for performance-based selection of movements. The principle is based on mapping motor performance across a workspace and then selecting movements located at regions of the steepest transition between better and worse performance. To assess the benefit of this principle we compared the effect of 15 sessions of robot-assisted reaching training on upper-limb motor impairment, between two groups of people who have moderate-to-severe chronic upper-limb hemiparesis due to stroke. The test group (N = 7) received steepest gradients-based training, iteratively selected according to the steepest gradients principle with weekly remapping, whereas the control group (N = 9) received a standard "centre-out" reaching training. Training intensity was identical.

resultsBoth groups showed improvement in Fugl-Meyer upper-extremity scores (the primary outcome measure). Moreover, the test group showed significantly greater improvement (twofold) compared to control. The score remained elevated, on average, for at least 4 weeks although the additional benefit of the steepest-gradients -based training diminished relative to control.

conclusionsThis study provides a proof of concept for the superior benefit of performance-based selection of practiced movements in reducing upper-limb motor impairment due to stroke. This added benefit was most evident in the short term, suggesting that performance-based steepest-gradients training may be effective in increasing the rate of initial phase of practice-based recovery; we discuss how long-term retention may also be improved.

trial registrationISRCTN, ISRCTN65226825 , registered 12 June 2018 - Retrospectively registered.

Indexed as

AdultAgedFemaleHumansMaleMiddle AgedMovementParesisPhysical Therapy ModalitiesPilot ProjectsRoboticsStroke RehabilitationUpper ExtremityYoung AdultReaching taskRehabilitationRobot-assisted therapyStrokeUpper limb movements

Identifiers

PMID30894192
PMCPMC6425657
OpenAlexW2944121790

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.