Evidence map›Paper›PMID 29808098›Full record

ReviewApplied bionics and biomechanics2018

Feasibility of Muscle Synergy Outcomes in Clinics, Robotics, and Sports: A Systematic Review.

Juri Taborri, Valentina Agostini, Panagiotis K Artemiadis, Marco Ghislieri, Daniel A Jacobs, Jinsook Roh, Stefano Rossi

Abstract readReview
In one paragraph

Review in Applied bionics and biomechanics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 pooled it
–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

38 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  19. Cognitive impairment in people with previous COVID-19 infection: A scoping review.Cortex; a journal devoted to the study of the nervous system and behavior · 2022
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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.

Juri TaborriDepartment of Economics, Engineering, Society and Business Organization, University of Tuscia, Viterbo, Italy.ORCID 0000-0002-8997-7605
Valentina AgostiniDepartment of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy.ORCID 0000-0001-5887-1499
Panagiotis K ArtemiadisDepartment of Mechanical and Aerospace Engineering, Arizona State University, Tempe, AZ, USA.
Marco GhislieriDepartment of Electronics and Telecommunications, Politecnico di Torino, Torino, Italy.ORCID 0000-0001-7626-1563
Daniel A JacobsDepartment of Mechanical Engineering, College of Engineering, Temple University, Philadelphia, PA, USA.
Jinsook RohDepartment of Kinesiology, College of Public Health, Temple University, Philadelphia, PA, USA.ORCID 0000-0002-5615-1735
Stefano RossiDepartment of Economics, Engineering, Society and Business Organization, University of Tuscia, Viterbo, Italy.ORCID 0000-0003-0006-7013

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last years, several studies have been focused on understanding how the central nervous system controls muscles to perform a specific motor task. Although it still remains an open question, muscle synergies have come to be an appealing theory to explain the modular organization of the central nervous system. Even though the neural encoding of muscle synergies remains controversial, a large number of papers demonstrated that muscle synergies are robust across different tested conditions, which are within a day, between days, within a single subject, and between subjects that have similar demographic characteristics. Thus, muscle synergy theory has been largely used in several research fields, such as clinics, robotics, and sports. The present systematical review aims at providing an overview on the applications of muscle synergy theory in clinics, robotics, and sports; in particular, the review is focused on the papers that provide tangible information for (i) diagnosis or pathology assessment in clinics, (ii) robot-control design in robotics, and (iii) athletes' performance assessment or training guidelines in sports.

Identifiers

PMID29808098
PMCPMC5902115

What OpenQuestion holds

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Registered trials

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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.