Evidence map›Paper›PMID 28803535›Full record

Trial reportNeurorehabilitation and neural repair2017

Robotic Assistance for Training Finger Movement Using a Hebbian Model: A Randomized Controlled Trial.

Justin B Rowe, Vicky Chan, Morgan L Ingemanson, Steven C Cramer, Eric T Wolbrecht, David J Reinkensmeyer

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Neurorehabilitation and neural repair, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04818073 (Determinants of the Effectiveness of Robot-assisted Hand Movement Training), which is not on this map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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.

NCT04818073 naactive not recruitingnot on this mapstarted 2022, after this paper: background citation

Determinants of the Effectiveness of Robot-assisted Hand Movement Training

TypeinterventionalSponsorUniversity of California, IrvineRan2022 to 2025Enrolled60ConditionsStroke, Ischemic, Cerebrovascular Accident (CVA)ArmsNew FINGER
3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  7. Proprioceptive Gaming: Making Finger Sensation Training Intense and Engaging with the P-Pong Game and PINKIE Robot.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021
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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

6 authors.

Justin B Rowe1 University of California at Irvine, Irvine, CA, USA.
Vicky Chan1 University of California at Irvine, Irvine, CA, USA.
Morgan L Ingemanson1 University of California at Irvine, Irvine, CA, USA.
Steven C Cramer1 University of California at Irvine, Irvine, CA, USA.
Eric T Wolbrecht2 University of Idaho, Moscow, ID, USA.
David J Reinkensmeyer1 University of California at Irvine, Irvine, CA, USA.

Funding

Institute for Clinical and Translational ScienceUL1TR000153 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI COOPER, DAN M · 2012 to 2015
$12.1M
EFFECTIVENESS OF ROBOT-ASSISTED HAND MOVEMENT TRAINING AFTER STROKER01HD062744 · NICHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI David Jay Reinkensmeyer · 2010 to 2026
$3.5M
Brain plasticity and rehabilitation after strokeK24HD074722 · NICHD · UNIVERSITY OF CALIFORNIA-IRVINE · PI CRAMER, STEVEN C. · 2013 to 2017
$588k
NICHD NIH HHS K24 HD074722NICHD NIH HHS R01 HD062744
6 · The paper itself

Abstract

backgroundRobots that physically assist movement are increasingly used in rehabilitation therapy after stroke, yet some studies suggest robotic assistance discourages effort and reduces motor learning.

objectiveTo determine the therapeutic effects of high and low levels of robotic assistance during finger training.

methodsWe designed a protocol that varied the amount of robotic assistance while controlling the number, amplitude, and exerted effort of training movements. Participants (n = 30) with a chronic stroke and moderate hemiparesis (average Box and Blocks Test 32 ± 18 and upper extremity Fugl-Meyer score 46 ± 12) actively moved their index and middle fingers to targets to play a musical game similar to GuitarHero 3 h/wk for 3 weeks. The participants were randomized to receive high assistance (causing 82% success at hitting targets) or low assistance (55% success). Participants performed ~8000 movements during 9 training sessions.

resultsBoth groups improved significantly at the 1-month follow-up on functional and impairment-based motor outcomes, on depression scores, and on self-efficacy of hand function, with no difference between groups in the primary endpoint (change in Box and Blocks). High assistance boosted motivation, as well as secondary motor outcomes (Fugl-Meyer and Lateral Pinch Strength)-particularly for individuals with more severe finger motor deficits. Individuals with impaired finger proprioception at baseline benefited less from the training.

conclusionsRobot-assisted training can promote key psychological outcomes known to modulate motor learning and retention. Furthermore, the therapeutic effectiveness of robotic assistance appears to derive at least in part from proprioceptive stimulation, consistent with a Hebbian plasticity model.

Indexed as

RoboticsDouble-Blind MethodExercise TherapyFemaleFingersFollow-Up StudiesHumansLearningMaleMiddle AgedModels, NeurologicalMotivationMotor ActivityMovementMusicNeuronal Plasticityhandmovementproprioceptionrehabilitationroboticsstroke

Identifiers

PMID28803535
PMCPMC5894506

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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.