Evidence map›Paper›PMID 32909949›Full record

Trial reportJMIR mHealth and uHealth2020

Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study.

Minseok Seo, Myung-Jun Shin, Tae Sung Park, Jong-Hwan Park

Open access · goldAbstract readClinical Trial
In one paragraph

Trial report in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

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  10. Investigating the relationship of trunk and postural control with pulmonary functions in subacute stroke patients.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

4 authors at 2 institutions in 1 country.

Minseok SeoSchool of Medicine, Pusan National University, Busan, Republic of Korea.ORCID 0000-0003-1877-367X
Myung-Jun ShinDepartment of Rehabilitation Medicine, School of Medicine, Pusan National University, Busan, Republic of Korea.ORCID 0000-0003-4010-0383
Tae Sung ParkBiomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.ORCID 0000-0001-6554-7638
Jong-Hwan ParkBiomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.ORCID 0000-0003-2815-7248
Pusan National University · KRPusan National University Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFor effective rehabilitation after stroke, it is essential to conduct an objective assessment of the patient's functional status. Several stroke severity scales have been used for this purpose, but such scales have various limitations.

objectiveGait analysis using smart insole technology can be applied continuously, objectively, and quantitatively, thereby overcoming the shortcomings of other assessment tools.

methodsTo confirm the reliability of gait analysis using smart insole technology, normal healthy controls wore insoles in their shoes during the Timed Up and Go (TUG) test. The gait parameters were compared with the manually collected data. To determine the gait characteristics of patients with hemiplegia due to stroke, they were asked to wear insoles and take the TUG test; gait parameters were calculated and compared with those of control subjects. To investigate whether the gait analysis accurately reflected the patients' clinical condition, we analyzed the relationships of 22 gait parameters on 4 stroke severity scales.

resultsThe smart insole gait parameter data were similar to those calculated manually. Among the 18 gait parameters tested, 14 were significantly effective at distinguishing patients from healthy controls. The smart insole data revealed that the stance duration on both sides was longer in patients than controls, which has proven difficult to show using other methods. Furthermore, the sound side in patients showed a markedly longer stance duration. Regarding swing duration, that of the sound side was shorter in patients than controls, whereas that of the hemiplegic side was longer. We identified 10 significantly correlated gait parameters on the stroke severity scales. Notably, the difference in stance duration between the sound and hemiplegic sides was significantly correlated with the Fugl-Meyer Assessment (FMA) lower extremity score.

conclusionsThis study confirmed the feasibility and applicability of the smart insole as a device to assess the gait of patients with hemiplegia due to stroke. In addition, we demonstrated that the FMA score was significantly correlated with the smart insole data. Providing an environment where stroke patients can easily measure walking ability helps to maintain chronic functions as well as acute rehabilitation.

trial registrationUMIN Clinical Trials Registry UMIN000041646, https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047538.

Indexed as

HemiplegiaStrokeGait AnalysisHumansPilot ProjectsReproducibility of ResultsShoesassessmentgaithemiplegiamedical informaticsobservationalrehabilitationsmart insolestrokewearable

Identifiers

PMID32909949
PMCPMC7516684
OpenAlexW3059832801

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.