Evidence map›Paper›PMID 32517013›Full record

ReviewSensors (Basel, Switzerland)2020

Muscle Synergies in Parkinson's Disease.

Ilaria Mileti, Alessandro Zampogna, Alessandro Santuz, Francesco Asci, Zaccaria Del Prete, Adamantios Arampatzis, Eduardo Palermo, Antonio Suppa

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

Ilaria MiletiDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0002-1064-7962
Alessandro ZampognaDepartment of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy.
Alessandro SantuzDepartment of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.ORCID 0000-0002-6577-5101
Francesco AsciDepartment of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0000-0003-0717-3521
Zaccaria Del PreteDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.
Adamantios ArampatzisDepartment of Training and Movement Sciences, Humboldt-Universität zu Berlin, 10115 Berlin, Germany.ORCID 0000-0002-4985-0335
Eduardo PalermoDepartment of Mechanical and Aerospace Engineering, Sapienza University of Rome, 00184 Rome, Italy.ORCID 0000-0002-3213-8261
Antonio SuppaDepartment of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy.ORCID 0000-0001-9903-5550

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last two decades, experimental studies in humans and other vertebrates have increasingly used muscle synergy analysis as a computational tool to examine the physiological basis of motor control. The theoretical background of muscle synergies is based on the potential ability of the motor system to coordinate muscles groups as a single unit, thus reducing high-dimensional data to low-dimensional elements. Muscle synergy analysis may represent a new framework to examine the pathophysiological basis of specific motor symptoms in Parkinson's disease (PD), including balance and gait disorders that are often unresponsive to treatment. The precise mechanisms contributing to these motor symptoms in PD remain largely unknown. A better understanding of the pathophysiology of balance and gait disorders in PD is necessary to develop new therapeutic strategies. This narrative review discusses muscle synergies in the evaluation of motor symptoms in PD. We first discuss the theoretical background and computational methods for muscle synergy extraction from physiological data. We then critically examine studies assessing muscle synergies in PD during different motor tasks including balance, gait and upper limb movements. Finally, we speculate about the prospects and challenges of muscle synergy analysis in order to promote future research protocols in PD.

Indexed as

ElectromyographyMuscle, SkeletalParkinson DiseaseGaitHumansMovementbalanceelectromyographygaitlocomotionmotor modulesmotor primitivesmuscle synergiesParkinson’s disease

Identifiers

PMID32517013
PMCPMC7308810

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.