Evidence map›Paper›PMID 34770493›Full record

ArticleSensors (Basel, Switzerland)2021

Evaluation of Muscle Function by Means of a Muscle-Specific and a Global Index.

Samanta Rosati, Marco Ghislieri, Gregorio Dotti, Daniele Fortunato, Valentina Agostini, Marco Knaflitz, Gabriella Balestra

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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

2 citing papers in PubMed.

  1. Review
  2. 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

7 authors.

Samanta RosatiDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-0620-594X
Marco GhislieriDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0001-7626-1563
Gregorio DottiDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-0004-0243
Daniele FortunatoDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0002-7856-9518
Valentina AgostiniDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0001-5887-1499
Marco KnaflitzDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0001-5396-5103
Gabriella BalestraDepartment of Electronics and Telecommunications and PoliToBIOMed Lab, Politecnico di Torino, 10129 Torino, Italy.ORCID 0000-0003-2717-648X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gait analysis applications in clinics are still uncommon, for three main reasons: (1) the considerable time needed to prepare the subject for the examination; (2) the lack of user-independent tools; (3) the large variability of muscle activation patterns observed in healthy and pathological subjects. Numerical indices quantifying the muscle coordination of a subject could enable clinicians to identify patterns that deviate from those of a reference population and to follow the progress of the subject after surgery or completing a rehabilitation program. In this work, we present two user-independent indices. First, a muscle-specific index (MFI) that quantifies the similarity of the activation pattern of a muscle of a specific subject with that of a reference population. Second, a global index (GFI) that provides a score of the overall activation of a muscle set. These two indices were tested on two groups of healthy and pathological children with encouraging results. Hence, the two indices will allow clinicians to assess the muscle activation, identifying muscles showing an abnormal activation pattern, and associate a functional score to every single muscle as well as to the entire muscle set. These opportunities could contribute to facilitating the diffusion of surface EMG analysis in clinics.

Indexed as

GaitMuscle, SkeletalChildElectromyographyHumansEMGgait analysismovement analysismuscle activation patterns

Identifiers

PMID34770493
PMCPMC8587884

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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.