Evidence map›Paper›PMID 37082189›Full record

Trial reportBioMed research international2023

Three-Dimensional Gait Analysis and sEMG Measures for Robotic-Assisted Gait Training in Subacute Stroke: A Randomized Controlled Trial.

Huihuang Zhang, Xiang Li, Yichen Gong, Jianing Wu, Jianer Chen, Weihai Chen, Zhongcai Pei, Wanying Zhang, Lei Dai, Xinxin Shu and 1 more

Registry-linked trialOpen access · hybridAbstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in BioMed research international, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06715098 (Comparison of Robot Assisted Gait Training and Body Weight Supported Treadmill Training in Chronic Stroke Patients Using Gait Analysis and SEMG Measurements), which is not on this map. Cited by 20 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 9 pooled it
3.7field-weighted citation impact, top 7% 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.

NCT06715098 nacompletednot on this map

Comparison of Robot Assisted Gait Training and Body Weight Supported Treadmill Training in Chronic Stroke Patients Using Gait Analysis and SEMG Measurements

TypeinterventionalSponsorPamukkale UniversityRan2023 to 2024Enrolled45ConditionsStroke, IschemicArmsRoboGait, RehaWalk, Conventional
3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 9 syntheses or guidelines pooled it, 27 citations in OpenAlex.

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  3. Electromechanical-assisted training for walking after stroke.The Cochrane database of systematic reviews · 2025
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  15. Effect and optimal exercise prescription of robot-assisted gait training on lower extremity motor function in stroke patients: a network meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
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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

11 authors at 3 institutions in 1 country.

Huihuang ZhangThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.ORCID https://orcid.org/0009-0006-7385-2572
Xiang LiThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.
Yichen GongDepartment of Center for Rehabilitation Assessment and Therapy, Zhejiang Rehabilitation Medical Center, 310053 Hangzhou, Zhejiang, China.
Jianing WuThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.
Jianer ChenThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.ORCID https://orcid.org/0000-0002-7101-208X
Weihai ChenDepartment of Hangzhou Innovation Institute, Beihang University, 310053 Hangzhou, Zhejiang, China.
Zhongcai PeiDepartment of Hangzhou Innovation Institute, Beihang University, 310053 Hangzhou, Zhejiang, China.
Wanying ZhangThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.
Lei DaiThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310053 Hangzhou, Zhejiang, China.
Xinxin ShuDepartment of Center for Rehabilitation Assessment and Therapy, Zhejiang Rehabilitation Medical Center, 310053 Hangzhou, Zhejiang, China.
Cheng ShenDepartment of Hangzhou Innovation Institute, Beihang University, 310053 Hangzhou, Zhejiang, China.
Zhejiang Chinese Medical University · CNBeihang University · CNZhejiang Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The efficacy of robotic-assisted gait training (RAGT) should be considered versatilely; among which, gait assessment is one of the most important measures; observational gait assessment is the most commonly used method in clinical practice, but it has certain limitations due to the deviation of subjectivity; instrumental assessments such as three-dimensional gait analysis (3DGA) and surface electromyography (sEMG) can be used to obtain gait data and muscle activation during walking in stroke patients with hemiplegia, so as to better evaluate the rehabilitation effect of RAGT. Objective: This single-blind randomized controlled trial is aimed at analyzing the impact of RAGT on the 3DGA parameters and muscle activation in patients with subacute stroke and evaluating the clinical effect of improving walking function of RAGT. Methods: This randomized controlled trial evaluated the improvement of 4-week RAGT on patients with subacute stroke by 3DGA and surface electromyography (sEMG), combined with clinical scales: experimental group ( Results: After 4 weeks of intervention, intragroup comparison showed that walking speed, temporal symmetry, bilateral stride length, range of motion (ROM) of the bilateral hip, flexion angle of the affected knee, ROM of the affected ankle, FMA-LE, FAC, and 6MWT in the experimental group were significantly improved ( Conclusions: Compared with conventional gait training, RAGT successfully improved part of the spatiotemporal parameters of patients and optimized the motion of the affected lower limb joints and muscle activation patterns during walking, which is crucial for further rehabilitation of walking ability in patients with subacute stroke. This trial is registered with ChiCTR2200066402.

Indexed as

Gait Disorders, NeurologicRobotic Surgical ProceduresStrokeStroke RehabilitationElectromyographyGaitGait AnalysisHumansSingle-Blind MethodWalking

Identifiers

PMID37082189
PMCPMC10113045
OpenAlexW4364377298

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.