Evidence map›Paper›PMID 39943472›Full record

ArticleSensors (Basel, Switzerland)2025

Adaptive Exoskeleton Device for Stress Reduction in the Ankle Joint Orthosis.

Andrey Iziumov, Talib Sabah Hussein, Evgeny Kosenko, Anton Nazarov

Registry-linked trialAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07578753 (Clinical Effectiveness of Robot-assisted Gait Training in Patients With Lower Limb Burns Accompanied by Fractures), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT07578753 naenrolling by invitationnot on this map

Clinical Effectiveness of Robot-assisted Gait Training in Patients With Lower Limb Burns Accompanied by Fractures: Pilot Study

TypeinterventionalSponsorHangang Sacred Heart HospitalRan2024 to 2026Enrolled5ConditionsBurn, Fracture, Robot Assisted Gait TrainingArmsrobot assisted gait training
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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.

Andrey IziumovDepartment of the Robotics and Mechatronics, Faculty of Automation, Mechatronics and Control, Don State Technical University, 344003 Rostov-on-Don, Russia.ORCID 0000-0001-9054-448X
Talib Sabah HusseinDepartment of the Robotics and Mechatronics, Faculty of Automation, Mechatronics and Control, Don State Technical University, 344003 Rostov-on-Don, Russia.
Evgeny KosenkoDepartment of the Robotics and Mechatronics, Faculty of Automation, Mechatronics and Control, Don State Technical University, 344003 Rostov-on-Don, Russia.ORCID 0000-0003-0515-9849
Anton NazarovDepartment of the Robotics and Mechatronics, Faculty of Automation, Mechatronics and Control, Don State Technical University, 344003 Rostov-on-Don, Russia.ORCID 0009-0002-5667-0049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Treating ankle fractures in athletes, commonly resulting from training injuries, remains a significant challenge. Current approaches to managing both non-surgical and postoperative foot and ankle disorders have focused on integrating sensory systems into orthotic devices. Recent analyses have identified several gaps in rehabilitation strategies, especially regarding gait pattern reformation during recovery. This work aims to enhance rehabilitation effectiveness for patients with ankle injuries by controlling load distribution and monitoring joint flexion/extension angles, as well as the reactive forces during therapeutic exercises and walking. We developed an exoskeleton device model using SolidWorks 2024 software, based on data from two patients: one healthy and one with an ankle fracture. Pressure measurements in the posterior limb region were taken using the F-Socket system and a custom electromechanical sensor designed by the authors. The collected data were analyzed using the butterfly parameterization method. This research led to the development of an adaptive exoskeleton device that provided pressure distribution data, gait cycle graphs, and a diagram correlating foot angles with the duration of exoskeleton use. The device demonstrated improvement in the patients' conditions, facilitating a more normalized gait pattern. A reduction in the load applied to the ankle joint was also observed, with the butterfly parameter confirming the device's correct operation.

Indexed as

Ankle FracturesAnkle JointExoskeleton DeviceOrthotic DevicesAdultAnkle InjuriesBiomechanical PhenomenaGaitHumansMaleWalkingfoot pressureforce sensorsinterventional pressurerobotic sensor systemssensor arraystactile sensors

Identifiers

PMID39943472
PMCPMC11821154

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Registered trials

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.