Evidence map›Paper›PMID 35273244›Full record

ArticleScientific reports2022

Visual guidance can help with the use of a robotic exoskeleton during human walking.

Myunghee Kim, Hyeongkeun Jeong, Prakyath Kantharaju, Dongyual Yoo, Michael Jacobson, Dongbin Shin, Changsoo Han, James L Patton

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 27 citations in OpenAlex.

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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 2 institutions in 2 countries.

Myunghee KimMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA. myheekim@uic.edu.
Hyeongkeun JeongMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA.
Prakyath KantharajuMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA.
Dongyual YooMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA.
Michael JacobsonMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA.
Dongbin ShinDepartment of Robot Engineering, Hanyang University, 55 Hanyangdaehak-ro, Ansan, South Korea.
Changsoo HanDepartment of Robot Engineering, Hanyang University, 55 Hanyangdaehak-ro, Ansan, South Korea.
James L PattonMechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL, 60607, USA.
University of Illinois Chicago · USHanyang University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Walking is an important activity that supports the health-related quality of life, and for those who need assistance, robotic devices are available to help. Recent progress in wearable robots has identified the importance of customizing the assistance provided by the robot to the individual, resulting in robot adaptation to the human. However, current implementations minimize the role of human adaptation to the robot, for example, by the users modifying their movements based on the provided robot assistance. This study investigated the effect of visual feedback to guide the users in adapting their movements in response to wearable robot assistance. The visual feedback helped the users reduce their metabolic cost of walking without any changes in robot assistance in a given time. In a case with the initially metabolic expensive (IMExp) exoskeleton condition, both training methods helped reduce the metabolic cost of walking. The results suggest that visual feedback training is helpful to use the exoskeleton for various conditions. Without feedback, the training is helpful only for the IMExp exoskeleton condition. This result suggests visual feedback training can be useful to facilitate the use of non-personalized, generic assistance, where the assistance is not tuned for each user, in a relatively short time.

Indexed as

Exoskeleton DeviceAdaptation, PhysiologicalBiomechanical PhenomenaGaitHumansQuality of LifeWalking

Identifiers

PMID35273244
PMCPMC8913727
OpenAlexW4221049293

What OpenQuestion 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 OpenQuestion graph.