Evidence map›Paper›PMID 36679587›Full record

ArticleSensors (Basel, Switzerland)2023

Benchmarking the Effects on Human-Exoskeleton Interaction of Trajectory, Admittance and EMG-Triggered Exoskeleton Movement Control.

Camila Rodrigues-Carvalho, Marvin Fernández-García, David Pinto-Fernández, Clara Sanz-Morere, Filipe Oliveira Barroso, Susana Borromeo, Cristina Rodríguez-Sánchez, Juan C Moreno, Antonio J Del-Ama

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.3field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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  5. 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

9 authors at 2 institutions in 1 country.

Camila Rodrigues-CarvalhoNeural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002 Madrid, Spain.ORCID 0000-0003-4351-3749
Marvin Fernández-GarcíaElectronic Technology Department, Rey Juan Carlos University, 28933 Móstoles, Spain.
David Pinto-FernándezNeural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002 Madrid, Spain.ORCID 0000-0003-0139-1261
Clara Sanz-MorereCenter for Clinical Neuroscience, Hospital Los Madroños, 28690 Madrid, Spain.ORCID 0000-0002-8195-8346
Filipe Oliveira BarrosoNeural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002 Madrid, Spain.ORCID 0000-0003-0228-6447
Susana BorromeoElectronic Technology Department, Rey Juan Carlos University, 28933 Móstoles, Spain.ORCID 0000-0002-2353-2902
Cristina Rodríguez-SánchezElectronic Technology Department, Rey Juan Carlos University, 28933 Móstoles, Spain.ORCID 0000-0001-9243-2166
Juan C MorenoNeural Rehabilitation Group, Cajal Institute, Spanish National Research Council (CSIC), 28002 Madrid, Spain.ORCID 0000-0001-9561-7764
Antonio J Del-AmaElectronic Technology Department, Rey Juan Carlos University, 28933 Móstoles, Spain.ORCID 0000-0001-6215-2593
Consejo Superior de Investigaciones Científicas · ESUniversidad Rey Juan Carlos · ES

Funding

European Union 779963European Union Next Generation IJC2020-044467-IMinisterio de Ciencia e Innovación 10.13039/501100011033Spanish National Research Council NEURO-AGINGl+ (PTI-NEURO-AGING+)
6 · The paper itself

Abstract

Nowadays, robotic technology for gait training is becoming a common tool in rehabilitation hospitals. However, its effectiveness is still controversial. Traditional control strategies do not adequately integrate human intention and interaction and little is known regarding the impact of exoskeleton control strategies on muscle coordination, physical effort, and user acceptance. In this article, we benchmarked three types of exoskeleton control strategies in a sample of seven healthy volunteers: trajectory assistance (TC), compliant assistance (AC), and compliant assistance with EMG-Onset stepping control (OC), which allows the user to decide when to take a step during the walking cycle. This exploratory study was conducted within the EUROBENCH project facility. Experimental procedures and data analysis were conducted following EUROBENCH's protocols. Specifically, exoskeleton kinematics, muscle activation, heart and breathing rates, skin conductance, as well as user-perceived effort were analyzed. Our results show that the OC controller showed robust performance in detecting stepping intention even using a corrupt EMG acquisition channel. The AC and OC controllers resulted in similar kinematic alterations compared to the TC controller. Muscle synergies remained similar to the synergies found in the literature, although some changes in muscle contribution were found, as well as an overall increase in agonist-antagonist co-contraction. The OC condition led to the decreased mean duration of activation of synergies. These differences were not reflected in the overall physiological impact of walking or subjective perception. We conclude that, although the AC and OC walking conditions allowed the users to modulate their walking pattern, the application of these two controllers did not translate into significant changes in the overall physiological cost of walking nor the perceived experience of use. Nonetheless, results suggest that both AC and OC controllers are potentially interesting approaches that can be explored as gait rehabilitation tools. Furthermore, the INTENTION project is, to our knowledge, the first study to benchmark the effects on human-exoskeleton interaction of three different exoskeleton controllers, including a new EMG-based controller designed by us and never tested in previous studies, which has made it possible to provide valuable third-party feedback on the use of the EUROBENCH facility and testbed, enriching the apprenticeship of the project consortium and contributing to the scientific community.

Indexed as

Exoskeleton DeviceBenchmarkingBiomechanical PhenomenaElectromyographyGaitHumansMuscle, SkeletalWalkingbenchmarkingelectromyographyEMG controlexoskeletonexoskeleton controlhuman–robot interaction

Identifiers

PMID36679587
PMCPMC9867281
OpenAlexW4315571627

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.