Evidence map›Paper›PMID 36707817›Full record

ArticleJournal of neuroengineering and rehabilitation2023

Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation.

Christopher L Hunt, Yinghe Sun, Shipeng Wang, Ahmed W Shehata, Jacqueline S Hebert, Marlis Gonzalez-Fernandez, Rahul R Kaliki, Nitish V Thakor

Open access · goldAbstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 16% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Review
  5. Article
  6. 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

8 authors at 3 institutions in 2 countries.

Christopher L HuntDepartment of Biomedical Engineering, The Johns Hopkins University, Baltimore, USA. chunt11@jh.edu.
Yinghe SunDepartment of Electrical and Computer Engineering, Tufts University, Medford, USA.
Shipeng WangDepartment of Biomedical Engineering, The Johns Hopkins University, Baltimore, USA.
Ahmed W ShehataDivision of Physical Medicine & Rehabilitation, University of Alberta, Edmonton, Canada.
Jacqueline S HebertDivision of Physical Medicine & Rehabilitation, University of Alberta, Edmonton, Canada.
Marlis Gonzalez-FernandezDepartment of Physical Medicine and Rehabilitation, The Johns Hopkins University, Baltimore, USA.
Rahul R KalikiDepartment of Biomedical Engineering, The Johns Hopkins University, Baltimore, USA.
Nitish V ThakorDepartment of Biomedical Engineering, The Johns Hopkins University, Baltimore, USA.
Johns Hopkins University · USUniversity of Alberta · CATufts University · US

Funding

NIH HHS DM190888
6 · The paper itself

Abstract

backgroundVirtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completing the same tasks in physical reality. Limb loading is a possible dimension of motor skill execution that is absent in current AR solutions that may help to increase skill transfer between the virtual and physical domains.

methodsWe implemented an immersive AR environment where individuals could operate a myoelectric virtual prosthesis to accomplish a variety of object relocation manipulations. Intact limb participants were separated into three groups, the load control (CG

resultsThe EG experienced a greater increase in completion rate post-training than both the CG

conclusionThe results demonstrated that limb loading plays an important role in transferring complex motor skills learned in virtual spaces to their physical reality analogs. While participants who did not receive limb loading were able to receive some functional benefit from AR training, participants who received the loading experienced a greater positive change in motor performance with their performance saturating in fewer training sessions.

Indexed as

AmputeesAugmented RealityHumansMotor SkillsPhysical ExaminationUpper ExtremityAugmented realityMyoelectric controlProprioceptionUpper-limb prostheses

Identifiers

PMID36707817
PMCPMC9881335
OpenAlexW4318215116

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.