Evidence map›Paper›PMID 31547437›Full record

ArticleSensors (Basel, Switzerland)2019

Preliminary Clinical Application of Textile Insole Sensor for Hemiparetic Gait Pattern Analysis.

Changwon Wang, Young Kim, Hangsik Shin, Se Dong Min

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
9.0field-weighted citation impact, top 2% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
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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.

Changwon WangDepartment of Medical IT Engineering, Soonchunhyang University, Asan 31538, Korea.
Young KimWellness Coaching Service Research Center, Soonchunhyang University, Asan 31538, Korea.ORCID 0000-0002-0043-1623
Hangsik ShinDepartment of Biomedical Engineering, Chonnam National University, Yeosu 59626, Korea.ORCID 0000-0002-8095-356X
Se Dong MinDepartment of Medical IT Engineering, Soonchunhyang University, Asan 31538, Korea. sedongmin@sch.ac.kr.
Soonchunhyang University · KRChonnam National University · KR

Funding

Ministry of Science and ICT, Republic of Korea NRF-2015M3A9D7067388
6 · The paper itself

Abstract

Post-stroke gait dysfunction occurs at a very high prevalence. A practical method to quantitatively analyze the characteristics of hemiparetic gait is needed in both clinical and community settings. This study developed a 10-channeled textile capacitive pressure sensing insole (TCPSI) with a real-time monitoring system and tested its performance through hemiparetic gait pattern analysis. Thirty-five subjects (18 hemiparetic, 17 healthy) walked down a 40-m long corridor at a comfortable speed while wearing TCPSI inside the shoe. For gait analysis, the percentage of the plantar pressure difference (PPD), the step count, the stride time, the coefficient of variation, and the phase coordination index (PCI) were used. The results of the stroke patients showed a threefold higher PPD, a higher step count (41.61 ± 10.7), a longer average stride time on the affected side, a lower mean plantar pressure on the affected side, higher plantar pressure in the toe area and the lateral side of the foot, and a threefold higher PCI (hemi: 19.50 ± 13.86%, healthy: 5.62 ± 5.05%) compared to healthy subjects. This study confirmed that TCPSI is a promising tool for distinguishing hemiparetic gait patterns and thus may be used as a wearable gait function evaluation tool, the external feedback gait training device, and a simple gait pattern analyzer for both hemiparetic patients and healthy individuals.

Indexed as

AdultAgedEquipment DesignFemaleGait AnalysisHumansMaleMiddle AgedParesisPressureStrokeTextilesWearable Electronic Devicesconductive textilegaithemipareticreal-time monitoringstroke

Identifiers

PMID31547437
PMCPMC6767662
OpenAlexW2972572303

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.