Evidence map›Paper›PMID 25314703›Full record

ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2015

Assist-as-Needed Robot-Aided Gait Training Improves Walking Function in Individuals Following Stroke.

Shraddha Srivastava, Pei-Chun Kao, Seok Hun Kim, Paul Stegall, Damiano Zanotto, Jill S Higginson, Sunil K Agrawal, John P Scholz

Open access · greenAbstract read
In one paragraph

Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 2 pooled it
12.6field-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.

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

44 citing papers in PubMed, 2 syntheses or guidelines pooled it, 168 citations in OpenAlex.

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  6. Effects of Robot-Assisted Gait Training with Body Weight Support on Gait and Balance in Stroke Patients.International journal of environmental research and public health · 2022
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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

8 authors at 3 institutions in 1 country.

Shraddha Srivastava
Pei-Chun Kao
Seok Hun Kim
Paul Stegall
Damiano Zanotto
Jill S Higginson
Sunil K Agrawal
John P Scholz
University of Delaware · USColumbia University · USUniversity of South Florida · US

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

A novel robot-aided assist-as-needed gait training paradigm has been developed recently. This paradigm encourages subjects' active participation during training. Previous pilot studies demonstrated that assist-as-needed robot-aided gait training (RAGT) improves treadmill walking performance post-stroke. However, it is not known if there is an over-ground transfer of the training effects from RAGT on treadmill or long-term retention of the effects. The purpose of the current study was to examine the effects of assist-as-needed RAGT on over-ground walking pattern post-stroke. Nine stroke subjects received RAGT with visual feedback of each subject's instantaneous ankle malleolus position relative to a target template for 15 40-minute sessions. Clinical evaluations and gait analyses were performed before, immediately after, and 6 months post-training. Stroke subjects demonstrated significant improvements and some long-term retention of the improvements in their self-selected over-ground walking speed, Dynamic Gait Index, Timed Up and Go, peak knee flexion angle during swing phase and total hip joint excursion over the whole gait cycle for their affected leg . These preliminary results demonstrate that subjects improved their over-ground walking pattern and some clinical gait measures post-training suggesting that assist-as-needed RAGT including visual feedback may be an effective approach to improve over-ground walking pattern post-stroke.

Indexed as

RoboticsStroke RehabilitationWalkingAgedAged, 80 and overAnkleBiomechanical PhenomenaEquipment DesignExercise TherapyFeedback, SensoryFemaleGait Disorders, NeurologicHip JointHumansMaleMiddle Aged

Identifiers

PMID25314703
PMCPMC6050016
OpenAlexW2072395926

What OpenQuestion holds

Textmetadata
LicenceTDM
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 OpenQuestion graph.