Evidence map›Paper›PMID 29018339›Full record

ArticleFrontiers in human neuroscience2017

Gravitational and Dynamic Components of Muscle Torque Underlie Tonic and Phasic Muscle Activity during Goal-Directed Reaching.

Erienne V Olesh, Bradley S Pollard, Valeriya Gritsenko

Abstract read
In one paragraph

Article in Frontiers in human neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. A framework for quantifying the mechanics of dexterous grasp.bioRxiv : the preprint server for biology · 2026
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  8. Neural Networks-Based Approach to Solve Inverse Kinematics Problems for Medical Applications.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2024
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  16. A segmented forearm model of hand pronation-supination approximates joint moments for real time applications.International IEEE/EMBS Conference on Neural Engineering : [proceedings]. International IEEE EMBS Conference on Neural Engineering · 2021
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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

3 authors.

Erienne V OleshDepartment of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.
Bradley S PollardDepartment of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.
Valeriya GritsenkoDepartment of Human Performance, School of Medicine, West Virginia University, Morgantown, WV, United States.

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI GARY O RANKIN · 2012 to 2026
$81.0M
West Virginia University Stroke COBREP20GM109098 · NIGMS · WEST VIRGINIA UNIVERSITY · PI DEVRIES, ANNE COURTNEY · 2014 to 2024
$24.5M
COBRE Transitional Center in NeuroscienceP30GM103503 · NIGMS · WEST VIRGINIA UNIVERSITY · PI SPIROU, GEORGE A · 2012 to 2014
$3.2M
NIGMS NIH HHS P20 GM109098NIGMS NIH HHS P30 GM103503NIGMS NIH HHS U54 GM104942
6 · The paper itself

Abstract

Human reaching movements require complex muscle activations to produce the forces necessary to move the limb in a controlled manner. How gravity and the complex kinetic properties of the limb contribute to the generation of the muscle activation pattern by the central nervous system (CNS) is a long-standing and controversial question in neuroscience. To tackle this issue, muscle activity is often subdivided into static and phasic components. The former corresponds to posture maintenance and transitions between postures. The latter corresponds to active movement production and the compensation for the kinetic properties of the limb. In the present study, we improved the methodology for this subdivision of muscle activity into static and phasic components by relating them to joint torques. Ten healthy subjects pointed in virtual reality to visual targets arranged to create a standard center-out reaching task in three dimensions. Muscle activity and motion capture data were synchronously collected during the movements. The motion capture data were used to calculate postural and dynamic components of active muscle torques using a dynamic model of the arm with 5 degrees of freedom. Principal Component Analysis (PCA) was then applied to muscle activity and the torque components, separately, to reduce the dimensionality of the data. Muscle activity was also reconstructed from gravitational and dynamic torque components. Results show that the postural and dynamic components of muscle torque represent a significant amount of variance in muscle activity. This method could be used to define static and phasic components of muscle activity using muscle torques.

Indexed as

armEMGkinematics and dynamicsmotor systems and movement controlprincipal component analysis

Identifiers

PMID29018339
PMCPMC5623018

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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.