Evidence map›Paper›PMID 38770104›Full record

ArticleJournal of kinesiology and exercise sciences2024

ROBOT-ASSISTED TARGETED GAIT TRAINING.

Vaughn Chambers, Madison Johnson, Panagiotis Artemiadis

Abstract read
In one paragraph

Article in Journal of kinesiology and exercise sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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.

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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Vaughn ChambersMechanical Engineering Department at the University of Delaware, USA.
Madison JohnsonMechanical Engineering Department at the University of Delaware, USA.
Panagiotis ArtemiadisMechanical Engineering Department at the University of Delaware, USA.

Funding

SCH: Model-informed patient-specific rehabilitation using robotics and neuromuscular modelingR01HD111071 · NICHD · UNIVERSITY OF DELAWARE · PI ARTEMIADIS, PANAGIOTIS · 2022 to 2025
$1.2M
NICHD NIH HHS R01 HD111071
6 · The paper itself

Abstract

Background: Millions of people are affected yearly by "runner's knee" and osteoarthritis, which is thought to be related to impact force. Millions are also affected by chronic falling, who are usually both difficult to identify and train. While at first glance, these topics seem to be entirely disconnected, there appears to be a need for a device that would address both issues. This paper proposes and investigates the use of the Variable Stiffness Treadmill (VST) as a targeted training device for the different populations described above. Materials and Methods: The VST is the authors' unique robotic split-belt treadmill that can reduce the vertical ground stiffness of the left belt, while the right belt remains rigid. In this work, heart rate and energy expenditure are measured for healthy subjects in the challenging asymmetric environment created by the VST and compared to a traditional treadmill setting. Results: This study shows that this asymmetric environment results in an increase in heart rate and energy expenditure, an increase in activity in the muscles about the hip and knee, and a decrease in impact force at heel strike. Conclusions: Compliant environments, like those created on the VST, may be a beneficial tool as they can: reduce high-impact forces during running and walking, significantly engage the muscles surrounding the hip and knee allowing for targeted training and rehabilitation, and assist in identifying and training high fall-risk individuals.

Indexed as

compliantHuman gaitrehabilitationroboticsstiffness perturbationstraining

Identifiers

PMID38770104
PMCPMC11104734

What OpenQuestion holds

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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.