Evidence map›Paper›PMID 33371295›Full record

ArticleSensors (Basel, Switzerland)2020

Principal Characteristics of Affected and Unaffected Side Trunk Movement and Gait Event Parameters during Hemiplegic Stroke Gait with IMU Sensor.

Jeong-Woo Seo, Seul-Gee Kim, Joong Il Kim, Boncho Ku, Kahye Kim, Sangkwan Lee, Jaeuk U Kim

Abstract readLetter
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

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

6 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. Wearable Sensors Improve Prediction of Post-Stroke Walking Function Following Inpatient Rehabilitation.IEEE journal of translational engineering in health and medicine · 2022
    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

7 authors.

Jeong-Woo SeoFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.ORCID 0000-0003-2661-349X
Seul-Gee KimFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.ORCID 0000-0003-2717-8418
Joong Il KimFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.ORCID 0000-0001-5538-6674
Boncho KuFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.ORCID 0000-0001-5520-9782
Kahye KimFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.
Sangkwan LeeDepartment of Internal Medicine and Neuroscience, College of Korean Medicine, Wonkwang University, Iksan 54538, Korea.
Jaeuk U KimFuture medicine division, Korea Institute of Oriental Medicine, Daejeon 34504, Korea.ORCID 0000-0003-0408-5569

Funding

Korea Institute of Oriental Medicine KSN2013130, K18021
6 · The paper itself

Abstract

This study describe the characteristics of hemiplegic stroke gait with principal component analysis (PCA) of trunk movement (TM) and gait event (GE) parameters by the inertial measurement unit (IMU) sensors: (1) Background: This process can determine dominant variables through multivariate examination to identify the affected, unaffected, and healthy lower-limb sides; (2) Methods: The study monitored forty patients with stroke and twenty-eight healthy individuals comprising the control group for comparison. The IMU sensors were attached to each subject while performing a 6 m walking test. Sixteen variables extracted from the measured data were divided into 7 GE and 9 TM variables explaining pelvis tilt, oblique, and rotation. (3) Results: The tilt range variables of the trunk movement on the affected and unaffected sides were lower than those of the healthy side; this showed between-group differences in various GE variables. For the healthy and affected sides, 80% of variances were explained with 2 or 3 PCs involving only a few dominant variables; and (4) Conclusions: The difference between each side leg should be considered during the development of a diagnosis method. This research can be utilized to develop functional assessment tools for personalized treatment and to design appropriate training protocols.

Indexed as

Gait AnalysisStrokeTorsoAgedBiomechanical PhenomenaFemaleGait Disorders, NeurologicHemiplegiaHumansMaleMiddle AgedMonitoring, PhysiologicPelvisPrincipal Component Analysisgait eventhemiplegic gaitIMU sensorprincipal component analysisstroke

Identifiers

PMID33371295
PMCPMC7765925

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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.