Evidence map›Paper›PMID 35992955›Full record

ArticleFrontiers in human neuroscience2022

Embodiment of a virtual prosthesis through training using an EMG-based human-machine interface: Case series.

Karina Aparecida Rodrigues, João Vitor da Silva Moreira, Daniel José Lins Leal Pinheiro, Rodrigo Lantyer Marques Dantas, Thaís Cardoso Santos, João Luiz Vieira Nepomuceno, Maria Angélica Ratier Jajah Nogueira, Esper Abrão Cavalheiro, Jean Faber

Open access · goldAbstract readCase Reports
In one paragraph

Article in Frontiers in human neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 37% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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  3. 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

9 authors at 1 institution in 1 country.

Karina Aparecida RodriguesNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
João Vitor da Silva MoreiraNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
Daniel José Lins Leal PinheiroNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
Rodrigo Lantyer Marques DantasNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
Thaís Cardoso SantosNeuroengineering Laboratory, Department of Biomedical Engineering, Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, Brazil.
João Luiz Vieira NepomucenoNeuroengineering Laboratory, Department of Biomedical Engineering, Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, Brazil.
Maria Angélica Ratier Jajah NogueiraCenter of Rehabilitation Lucy Montoro, São José dos Campos, Brazil.
Esper Abrão CavalheiroNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
Jean FaberNeuroengineering and Neurocognition Laboratory, Paulista School of Medicine, Department of Neurology and Neurosurgery, Federal University of São Paulo, São Paulo, Brazil.
Universidade Federal de São Paulo · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic strategies capable of inducing and enhancing prosthesis embodiment are a key point for better adaptation to and acceptance of prosthetic limbs. In this study, we developed a training protocol using an EMG-based human-machine interface (HMI) that was applied in the preprosthetic rehabilitation phase of people with amputation. This is a case series with the objective of evaluating the induction and enhancement of the embodiment of a virtual prosthesis. Six men and a woman with unilateral transfemoral traumatic amputation without previous use of prostheses participated in the study. Participants performed a training protocol with the EMG-based HMI, composed of six sessions held twice a week, each lasting 30 mins. This system consisted of myoelectric control of the movements of a virtual prosthesis immersed in a 3D virtual environment. Additionally, vibrotactile stimuli were provided on the participant's back corresponding to the movements performed. Embodiment was investigated from the following set of measurements: skin conductance response (affective measurement), crossmodal congruency effect (spatial perception measurement), ability to control the virtual prosthesis (motor measurement), and reports before and after the training. The increase in the skin conductance response in conditions where the virtual prosthesis was threatened, recalibration of the peripersonal space perception identified by the crossmodal congruency effect, ability to control the virtual prosthesis, and participant reports consistently showed the induction and enhancement of virtual prosthesis embodiment. Therefore, this protocol using EMG-based HMI was shown to be a viable option to achieve and enhance the embodiment of a virtual prosthetic limb.

Indexed as

agencyamputeeembodimentownershipprosthesisvirtual reality

Identifiers

PMID35992955
PMCPMC9387771
OpenAlexW4289731029

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.