Evidence map›Paper›PMID 36531918›Full record

ArticleFrontiers in neurorobotics2022

A novel gait analysis system for detecting abnormal hemiparetic gait patterns during robot-assisted gait training: A criterion validity study among healthy adults.

Daisuke Imoto, Satoshi Hirano, Masahiko Mukaino, Eiichi Saitoh, Yohei Otaka

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neurorobotics, 2022. 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
0.6field-weighted citation impact, top 30% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Daisuke ImotoDepartment of Rehabilitation, Fujita Health University Hospital, Toyoake, Aichi, Japan.
Satoshi HiranoDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan.
Masahiko MukainoDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan.
Eiichi SaitohDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan.
Yohei OtakaDepartment of Rehabilitation Medicine I, School of Medicine, Fujita Health University, Toyoake, Aichi, Japan.
Fujita Health University · JPFujita Health University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Robot-assisted gait training has been reported to improve gait in individuals with hemiparetic stroke. Ideally, the gait training program should be customized based on individuals' gait characteristics and longitudinal changes. However, a gait robot that uses gait characteristics to provide individually tailored gait training has not been proposed. The new gait training robot, "Welwalk WW-2000," permits modification of various parameters, such as time and load of mechanical assistance for a patient's paralyzed leg. The robot is equipped with sensors and a markerless motion capture system to detect abnormal hemiparetic gait patterns during robot-assisted gait training. Thus, it can provide individually tailored gait training. This study aimed to investigate the criterion validity of the gait analysis system in the Welwalk WW-2000 in healthy adults. Materials and methods: Twelve healthy participants simulated nine abnormal gait patterns that were often manifested in individuals with hemiparetic stroke while wearing the robot. Each participant was instructed to perform a total of 36 gait trials, with four levels of severity for each abnormal gait pattern. Fifteen strides for each gait trial were recorded using the markerless motion capture system in the Welwalk WW-2000 and a marker-based three-dimensional (3D) motion analysis system. The abnormal gait pattern index was then calculated for each stride from both systems. The correlation of the index values between the two methods was evaluated using Spearman's rank correlation coefficients for each gait pattern in each participant. Results: Using the participants' index values for each abnormal gait pattern obtained using the two motion analysis methods, the median Spearman's rank correlation coefficients ranged from 0.68 to 0.93, which corresponded to moderate to very high correlation. Conclusion: The gait analysis system in the Welwalk WW-2000 for real-time detection of abnormal gait patterns during robot-assisted gait training was suggested to be a valid method for assessing gait characteristics in individuals with hemiparetic stroke. Clinical trial registration: [https://jrct.niph.go.jp], identifier [jRCT 042190109].

Indexed as

cerebrovascular disordersgait analysisrehabilitationrobot-assisted gait trainingvalidation study

Identifiers

PMID36531918
PMCPMC9751383
OpenAlexW4310525749

What OpenQuestion holds

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LicenceCC BY
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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.