Evidence map›Paper›PMID 30616663›Full record

ArticleJournal of neuroengineering and rehabilitation2019

Fixed muscle synergies and their potential to improve the intuitive control of myoelectric assistive technology for upper extremities.

Tim A Valk, Leonora J Mouton, Egbert Otten, Raoul M Bongers

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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

4 authors.

Tim A ValkCenter for Human Movement Sciences, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713, AV, Groningen, the Netherlands. t.a.valk@umcg.nl.ORCID 0000-0001-9189-6858
Leonora J MoutonCenter for Human Movement Sciences, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713, AV, Groningen, the Netherlands.
Egbert OttenCenter for Human Movement Sciences, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713, AV, Groningen, the Netherlands.
Raoul M BongersCenter for Human Movement Sciences, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713, AV, Groningen, the Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUsers of myoelectric controlled assistive technology (AT) for upper extremities experience difficulties in controlling this technology in daily life, partly because the control is non-intuitive. Making the control of myoelectric AT intuitive may resolve the experienced difficulties. The present paper was inspired by the suggestion that intuitive control may be achieved if the control of myoelectric AT is based on neuromotor control principles. A significant approach within neurocomputational motor control suggests that myosignals are produced via a limited number of fixed muscle synergies. To effectively employ this approach in myoelectric AT, it is required that a limited number of muscle synergies is systematically exploited, also when muscles are used differently as required in controlling myoelectric AT. Therefore, the present study examined the systematic exploitation of muscle synergies when muscles were used differently to complete point-to-point movements with and without a rod.

methodsHealthy participants made multidirectional point-to-point movements with different end-effectors, i.e. with the index finger and with rods of different lengths. Myosignals were collected from 22 muscles in the arm, trunk, and back, and subsequently partitioned into muscle synergies per end-effector and for a pooled dataset including all end-effectors. The exploitation of these muscle synergies was assessed by evaluating the similarity of structure and explanatory ability of myosignals of per end-effector muscle synergies and the contribution of pooled muscle synergies across end-effectors.

resultsPer end-effector, 3-5 muscle synergies could explain 73.8-81.1% of myosignal variation, whereas 6-8 muscle synergies from the pooled dataset also captured this amount of myosignal variation. Subsequent analyses showed that gradually different muscle synergies-extracted from separate end-effectors-were exploited across end-effectors. In line with this result, the order of contribution of muscle synergies extracted from the pooled dataset gradually reversed across end-effectors.

conclusionA limited number of muscle synergies was systematically exploited in the examined set of movements, indicating a potential for the fixed muscle synergy approach to improve the intuitive control of myoelectric AT. Given the gradual change in muscle synergy exploitation across end-effectors, future research should examine whether this potential can be extended to a larger range of movements and tasks.

Indexed as

Self-Help DevicesAdultBiomechanical PhenomenaElectromyographyFemaleHealthy VolunteersHumansMaleMovementMuscle, SkeletalUpper ExtremityAssistive technologyElectromyographyIntuitive controlMuscle synergiesPoint-to-point movementsUpper extremity

Identifiers

PMID30616663
PMCPMC6323752

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.