Evidence map›Paper›PMID 39202064›Full record

ReviewJournal of personalized medicine2024

Sensing and Control Strategies Used in FES Systems Aimed at Assistance and Rehabilitation of Foot Drop: A Systematic Literature Review.

Estefanía González-Graniel, Jorge A Mercado-Gutierrez, Saúl Martínez-Díaz, Iliana Castro-Liera, Israel M Santillan-Mendez, Oscar Yanez-Suarez, Ivett Quiñones-Uriostegui, Gerardo Rodríguez-Reyes

Abstract readReview
In one paragraph

Review in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Estefanía González-GranielDivisión de estudios de Posgrado e Investiagación, TecNM-Instituto Tecnológico de la Paz, La Paz 28080, Mexico.
Jorge A Mercado-GutierrezInstituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.
Saúl Martínez-DíazDivisión de estudios de Posgrado e Investiagación, TecNM-Instituto Tecnológico de la Paz, La Paz 28080, Mexico.ORCID 0000-0003-4962-5995
Iliana Castro-LieraDivisión de estudios de Posgrado e Investiagación, TecNM-Instituto Tecnológico de la Paz, La Paz 28080, Mexico.ORCID 0000-0001-5090-1067
Israel M Santillan-MendezDivisión de estudios de Posgrado e Investiagación, TecNM-Instituto Tecnológico de la Paz, La Paz 28080, Mexico.
Oscar Yanez-SuarezElectrical Engineering Department, Universidad Autónoma Metropolitana-Unidad Iztapalapa, Mexico City 09340, Mexico.
Ivett Quiñones-UriosteguiInstituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.
Gerardo Rodríguez-ReyesInstituto Nacional de Rehabilitación Luis Guillermo Ibarra Ibarra, Mexico City 14389, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional electrical stimulation (FES) is a rehabilitation and assistive technique used for stroke survivors. FES systems mainly consist of sensors, a control algorithm, and a stimulation unit. However, there is a critical need to reassess sensing and control techniques in FES systems to enhance their efficiency. This SLR was carried out following the PRISMA 2020 statement. Four databases (PubMed, Scopus, Web of Science, Wiley Online Library) from 2010 to 2024 were searched using terms related to sensing and control strategies in FES systems. A total of 322 articles were chosen in the first stage, while only 60 of them remained after the final filtering stage. This systematic review mainly focused on sensor techniques and control strategies to deliver FES. The most commonly used sensors reported were inertial measurement units (IMUs), 45% (27); biopotential electrodes, 36.7% (22); vision-based systems, 18.3% (11); and switches, 18.3% (11). The control strategy most reported is closed-loop; however, most of the current commercial FES systems employ open-loop strategies due to their simplicity. Three main factors were identified that should be considered when choosing a sensor for gait-oriented FES systems: wearability, accuracy, and affordability. We believe that the combination of computer vision systems with artificial intelligence-based control algorithms can contribute to the development of minimally invasive and personalized FES systems for the gait rehabilitation of patients with FDS.

Indexed as

EMGfoot dropfunctional electrical stimulationinertial measurement unitrehabilitationsensingstrokevision systems

Identifiers

PMID39202064
PMCPMC11355777

What OpenQuestion holds

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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.