Evidence map›Paper›PMID 34698082›Full record

ArticleBiomimetics (Basel, Switzerland)2021

Intra-Subject and Inter-Subject Movement Variability Quantified with Muscle Synergies in Upper-Limb Reaching Movements.

Kunkun Zhao, Zhisheng Zhang, Haiying Wen, Alessandro Scano

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2021. 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. Article
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  4. User preference in the personalized control of an ankle prosthesis: a case study.Journal of neuroengineering and rehabilitation · 2026
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  19. Muscle synergies in joystick manipulation.Frontiers in physiology · 2023
    Article
  20. 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.

Kunkun ZhaoSchool of Mechanical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0002-0962-494X
Zhisheng ZhangSchool of Mechanical Engineering, Southeast University, Nanjing 211189, China.
Haiying WenSchool of Mechanical Engineering, Southeast University, Nanjing 211189, China.ORCID 0000-0001-7096-7581
Alessandro ScanoUOS STIIMA Lecco-Human-Centered, Smart & Safe, Living Environment, Italian National Research Council (CNR), Via Previati 1/E, 23900 Lecco, Italy.ORCID 0000-0002-1896-9325

Funding

Fundamental Research Funds for the Central Universities KYCX19_0061National Natural Science Foundation of China 51775108Natural Science Foundation of Jiangsu Province BK20190368
6 · The paper itself

Abstract

Quantifying movement variability is a crucial aspect for clinical and laboratory investigations in several contexts. However, very few studies have assessed, in detail, the intra-subject variability across movements and the inter-subject variability. Muscle synergies are a valuable method that can be used to assess such variability. In this study, we assess, in detail, intra-subject and inter-subject variability in a scenario based on a comprehensive dataset, including multiple repetitions of multi-directional reaching movements. The results show that muscle synergies are a valuable tool for quantifying variability at the muscle level and reveal that intra-subject variability is lower than inter-subject variability in synergy modules and related temporal coefficients, and both intra-subject and inter-subject similarity are higher than random synergy matching, confirming shared underlying control structures. The study deepens the available knowledge on muscle synergy-based motor function assessment and rehabilitation applications, discussing their applicability to real scenarios.

Indexed as

inter-subjectintra-subjectmuscle synergiesreaching movementsupper limbvariability

Identifiers

PMID34698082
PMCPMC8544238

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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.