Evidence map›Paper›PMID 33925928›Full record

SynthesisSensors (Basel, Switzerland)2021

A Systematic Review of EMG Applications for the Characterization of Forearm and Hand Muscle Activity during Activities of Daily Living: Results, Challenges, and Open Issues.

Néstor J Jarque-Bou, Joaquín L Sancho-Bru, Margarita Vergara

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis 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 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 4% of its field
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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 95 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Hand movements prediction via fNIRS and AI algorithms.BMC medical informatics and decision making · 2026
    Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. Clinical Features to Predict the Use of a sEMG Wearable Device (REMOInternational journal of environmental research and public health · 2023
    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

3 authors at 1 institution in 1 country.

Néstor J Jarque-BouDepartment of Mechanical Engineering and Construction, Universitat Jaume I, E12071 Castellón, Spain.ORCID 0000-0001-7793-3309
Joaquín L Sancho-BruDepartment of Mechanical Engineering and Construction, Universitat Jaume I, E12071 Castellón, Spain.ORCID 0000-0001-8486-5113
Margarita VergaraDepartment of Mechanical Engineering and Construction, Universitat Jaume I, E12071 Castellón, Spain.ORCID 0000-0001-9158-247X
Universitat Jaume I · ES

Funding

Spanish MINECO and the European Union (FEDER funds BES-2015-072480Spanish MINECO and the European Union (FEDER funds) DPI2014-52095-PSpanish Ministry of Science, Innovation and Universities PGC2018-095606-B-C21
6 · The paper itself

Abstract

The role of the hand is crucial for the performance of activities of daily living, thereby ensuring a full and autonomous life. Its motion is controlled by a complex musculoskeletal system of approximately 38 muscles. Therefore, measuring and interpreting the muscle activation signals that drive hand motion is of great importance in many scientific domains, such as neuroscience, rehabilitation, physiotherapy, robotics, prosthetics, and biomechanics. Electromyography (EMG) can be used to carry out the neuromuscular characterization, but it is cumbersome because of the complexity of the musculoskeletal system of the forearm and hand. This paper reviews the main studies in which EMG has been applied to characterize the muscle activity of the forearm and hand during activities of daily living, with special attention to muscle synergies, which are thought to be used by the nervous system to simplify the control of the numerous muscles by actuating them in task-relevant subgroups. The state of the art of the current results are presented, which may help to guide and foster progress in many scientific domains. Furthermore, the most important challenges and open issues are identified in order to achieve a better understanding of human hand behavior, improve rehabilitation protocols, more intuitive control of prostheses, and more realistic biomechanical models.

Indexed as

Activities of Daily LivingForearmElectromyographyHandHumansMuscle, SkeletalADLEMGforearm musclesmuscle coordinationmuscles rolesynergies

Identifiers

PMID33925928
PMCPMC8123433
OpenAlexW3157218934

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.