Evidence map›Paper›PMID 35360179›Full record

ArticleFrontiers in neuroscience2022

Real-Time Control of a Multi-Degree-of-Freedom Mirror Myoelectric Interface During Functional Task Training.

Andrea Sarasola-Sanz, Eduardo López-Larraz, Nerea Irastorza-Landa, Giulia Rossi, Thiago Figueiredo, Joseph McIntyre, Ander Ramos-Murguialday

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 10 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

7 authors at 2 institutions in 2 countries.

Andrea Sarasola-SanzNeurotechnology Unit, TECNALIA, Basque Research and Technology Alliance, Donostia-San Sebastian, Spain.
Eduardo López-LarrazInstitute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.
Nerea Irastorza-LandaNeurotechnology Unit, TECNALIA, Basque Research and Technology Alliance, Donostia-San Sebastian, Spain.
Giulia RossiInstitute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.
Thiago FigueiredoInstitute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany.
Joseph McIntyreNeurotechnology Unit, TECNALIA, Basque Research and Technology Alliance, Donostia-San Sebastian, Spain.
Ander Ramos-MurguialdayNeurotechnology Unit, TECNALIA, Basque Research and Technology Alliance, Donostia-San Sebastian, Spain.
University of Tübingen · DETecnalia · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motor learning mediated by motor training has in the past been explored for rehabilitation. Myoelectric interfaces together with exoskeletons allow patients to receive real-time feedback about their muscle activity. However, the number of degrees of freedom that can be simultaneously controlled is limited, which hinders the training of functional tasks and the effectiveness of the rehabilitation therapy. The objective of this study was to develop a myoelectric interface that would allow multi-degree-of-freedom control of an exoskeleton involving arm, wrist and hand joints, with an eye toward rehabilitation. We tested the effectiveness of a myoelectric decoder trained with data from one upper limb and mirrored to control a multi-degree-of-freedom exoskeleton with the opposite upper limb (i.e., mirror myoelectric interface) in 10 healthy participants. We demonstrated successful simultaneous control of multiple upper-limb joints by all participants. We showed evidence that subjects learned the mirror myoelectric model within the span of a five-session experiment, as reflected by a significant decrease in the time to execute trials and in the number of failed trials. These results are the necessary precursor to evaluating if a decoder trained with EMG from the healthy limb could foster learning of natural EMG patterns and lead to motor rehabilitation in stroke patients.

Indexed as

motor learningmulti-DoF exoskeleton controlmyoelectric interfacerehabilitationstroke

Identifiers

PMID35360179
PMCPMC8962619
OpenAlexW4220843519

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.