Evidence map›Paper›PMID 35526003›Full record

SynthesisJournal of neuroengineering and rehabilitation2022

EMG-driven control in lower limb prostheses: a topic-based systematic review.

Andrea Cimolato, Josephus J M Driessen, Leonardo S Mattos, Elena De Momi, Matteo Laffranchi, Lorenzo De Michieli

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
8.0field-weighted citation impact, top 1% 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

33 citing papers in PubMed, 106 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Locomotion Decoding (Applied bionics and biomechanics · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Vibrotactile Haptic and Gesture Feedback in a Smartwatch for Controlling a Multi-Activity Powered Knee-Ankle Prosthesis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025
    Article
  13. Ambilateral Activity Recognition and Continuous Adaptation with a Powered Knee-Ankle Prosthesis.IEEE transactions on robotics : a publication of the IEEE Robotics and Automation Society · 2025
    Article
  14. Article
  15. Unified Control of a Powered Knee-Ankle Prosthesis Enables Walking, Stairs, Transitions, and Other Daily Ambulation Activities.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2025
    Article
  16. Article
  17. Review
  18. Beyond Flexible: Unveiling the Next Era of Flexible Electronic Systems.Advanced materials (Deerfield Beach, Fla.) · 2024
    Review
  19. Article
  20. Review
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

6 authors at 2 institutions in 1 country.

Andrea CimolatoRehab Technologies Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy. andrea.cimolato@iit.it.ORCID 0000-0002-4095-0233
Josephus J M DriessenRehab Technologies Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy.
Leonardo S MattosDepartment of Advanced Robotics, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy.
Elena De MomiDepartment of Electronics, Information and Bioengineering (DEIB), Neuroengineering and Medical Robotics Laboratory, Politecnico di Milano, Building 32.2, Via Giuseppe Colombo, 20133, Milan, Italy.
Matteo LaffranchiRehab Technologies Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy.
Lorenzo De MichieliRehab Technologies Lab, Fondazione Istituto Italiano di Tecnologia, Via Morego, 30, 16163, Genova, Italy.
Italian Institute of Technology · ITPolitecnico di Milano · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe inability of users to directly and intuitively control their state-of-the-art commercial prosthesis contributes to a low device acceptance rate. Since Electromyography (EMG)-based control has the potential to address those inabilities, research has flourished on investigating its incorporation in microprocessor-controlled lower limb prostheses (MLLPs). However, despite the proposed benefits of doing so, there is no clear explanation regarding the absence of a commercial product, in contrast to their upper limb counterparts. OBJECTIVE AND METHODOLOGIES: This manuscript aims to provide a comparative overview of EMG-driven control methods for MLLPs, to identify their prospects and limitations, and to formulate suggestions on future research and development. This is done by systematically reviewing academical studies on EMG MLLPs. In particular, this review is structured by considering four major topics: (1) type of neuro-control, which discusses methods that allow the nervous system to control prosthetic devices through the muscles; (2) type of EMG-driven controllers, which defines the different classes of EMG controllers proposed in the literature; (3) type of neural input and processing, which describes how EMG-driven controllers are implemented; (4) type of performance assessment, which reports the performance of the current state of the art controllers. RESULTS AND

conclusionsThe obtained results show that the lack of quantitative and standardized measures hinders the possibility to analytically compare the performances of different EMG-driven controllers. In relation to this issue, the real efficacy of EMG-driven controllers for MLLPs have yet to be validated. Nevertheless, in anticipation of the development of a standardized approach for validating EMG MLLPs, the literature suggests that combining multiple neuro-controller types has the potential to develop a more seamless and reliable EMG-driven control. This solution has the promise to retain the high performance of the currently employed non-EMG-driven controllers for rhythmic activities such as walking, whilst improving the performance of volitional activities such as task switching or non-repetitive movements. Although EMG-driven controllers suffer from many drawbacks, such as high sensitivity to noise, recent progress in invasive neural interfaces for prosthetic control (bionics) will allow to build a more reliable connection between the user and the MLLPs. Therefore, advancements in powered MLLPs with integrated EMG-driven control have the potential to strongly reduce the effects of psychosomatic conditions and musculoskeletal degenerative pathologies that are currently affecting lower limb amputees.

Indexed as

AmputeesArtificial LimbsElectromyographyHumansWalkingElectromyograhyLegged locomotionMicroprocessored-controlled lower limb prosthesisNeuro-control

Identifiers

PMID35526003
PMCPMC9077893
OpenAlexW4228998618

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.