Evidence map›Paper›PMID 22832470›Full record

Trial reportGait & posture2013

Effect of robotic performance-based error-augmentation versus error-reduction training on the gait of healthy individuals.

Pei-Chun Kao, Shraddha Srivastava, Sunil K Agrawal, John P Scholz

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Gait & posture, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03444688 (Development and Evaluation of a Novel Portable Robotic Gait Rehabilitation Platform in Older Chronic Stroke Survivors), which is not on this map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 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.

NCT03444688 naunknown statusnot on this mapstarted 2018, after this paper: background citation

Development and Evaluation of a Novel Portable Robotic Gait Rehabilitation Platform in Older Chronic Stroke Survivors (Phase 2)

TypeinterventionalSponsorNational University Hospital, SingaporeRan2018 to 2018Enrolled100ConditionsStrokeArmsConventional Gait Training, Gait rehabilitation with walker
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  16. Review
  17. Human Gait Analysis Metric for Gait Retraining.Applied bionics and biomechanics · 2019
    Article
  18. Variable Damping Force Tunnel for Gait Training Using ALEX III.IEEE robotics and automation letters · 2017
    Article
  19. Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2015
    Article
  20. Review
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

4 authors.

Pei-Chun KaoDepartment of Physical Therapy, University of Delaware, Newark, DE 19716, USA.
Shraddha Srivastava
Sunil K Agrawal
John P Scholz

Funding

Robotic Exoskeletons, FES, and Biomechanics: Treating Movement DisordersR01HD038582 · NICHD · UNIVERSITY OF DELAWARE · PI BINDER-MACLEOD, STUART A. · 2002 to 2012
$6.1M
NICHD NIH HHS R01 HD038582NICHD NIH HHS R01HD038582
6 · The paper itself

Abstract

Effective locomotion training with robotic exoskeletons requires identification of optimal control algorithms to better facilitate motor learning. Two commonly employed training protocols emphasize use of training stimuli that either augment or reduce performance errors. The current study sought to identify which of these training strategies promote better short-term modification of a typical gait pattern in healthy individuals as a framework for future application to neurologically impaired individuals. Ten subjects were assigned to each of a performance-based error-augmentation or error-reduction training group. All subjects completed a 45-min session of treadmill walking at their preferred speed with a robotic exoskeleton. Target templates prescribed an ankle path for training that corresponded to an increased step height. When subjects' instantaneous ankle positions fell below the inferior virtual wall of the target ankle path, robotic forces were applied that either decreased (error-reduction) or increased (error-augmentation) the deviation from the target path. When the force field was turned on, both groups walked with ankle paths better approximating the target template compared to baseline. When the force field was removed unexpectedly during catch and post-training trials, only the error-augmentation group maintained an ankle path close to the target ankle path. Further investigation is required to determine if a similar training advantage is provided for neurologically impaired individuals.

Indexed as

Feedback, SensoryGaitOrthotic DevicesRoboticsAdultBiomechanical PhenomenaCuesFemaleGait Disorders, NeurologicHumansLocomotionMaleTime Factors

Identifiers

PMID22832470
PMCPMC3513649

What OpenQuestion holds

Textmetadata
LicenceTDM
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.