Evidence map›Paper›PMID 36236276›Full record

ArticleSensors (Basel, Switzerland)2022

The Automatization of the Gait Analysis by the Vicon Video System: A Pilot Study.

Victoriya Smirnova, Regina Khamatnurova, Nikita Kharin, Elena Yaikova, Tatiana Baltina, Oskar Sachenkov

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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
–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. Article
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  3. Review
  4. Article
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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

6 authors.

Victoriya SmirnovaInstitute of Computational Mathematics and Information Technologies, Kazan Federal University, 420008 Kazan, Russia.
Regina KhamatnurovaInterdisciplinary Neuroscience Faculty, Goethe-Universität Frankfurt am Main, 60323 Frankfurt am Main, Germany.
Nikita KharinN.I. Lobachevsky Institute of Mathematics and Mechanics, Kazan Federal University, 420008 Kazan, Russia.ORCID 0000-0003-4850-143X
Elena YaikovaNeurosurgical Department, Central City Clinical Hospital, 432017 Ulyanovsk, Russia.
Tatiana BaltinaInstitute of Fundamental Medicine and Biology, Kazan Federal University, 420008 Kazan, Russia.ORCID 0000-0003-3798-7665
Oskar SachenkovN.I. Lobachevsky Institute of Mathematics and Mechanics, Kazan Federal University, 420008 Kazan, Russia.ORCID 0000-0002-8554-2938

Funding

Kazan Federal University Strategic Academic Leadership Program PRIORITY-2030Russian Foundation for Basic Research 20-01-00535
6 · The paper itself

Abstract

The quality of modern measuring instruments has a strong influence on the speed of diagnosing diseases of the human musculoskeletal system. The research is focused on automatization of the method of gait analysis. The study involved six healthy subjects. The subjects walk straight. Each subject made several gait types: casual walking and imitation of a non-standard gait, including shuffling, lameness, clubfoot, walking from the heel, rolling from heel to toe, walking with hands in pockets, and catwalk. Each type of gait was recorded three times. For video fixation, the Vicon Nexus system was used. A total of 27 reflective markers were placed on the special anatomical regions. The goniometry methods were used. The walk data were divided by steps and by step phases. Kinematic parameters for estimation were formulated and calculated. An approach for data clusterization is presented. For this purpose, angle data were interpolated and the interpolation coefficients were used for clustering the data. The data were processed and four cluster groups were found. Typical angulograms for cluster groups were presented. For each group, average angles were calculated. A statistically significant difference was found between received cluster groups.

Indexed as

GaitGait AnalysisBiomechanical PhenomenaHumansPilot ProjectsWalkingclustering high-dimensional datagaitmachine learningstep phasesVicon

Identifiers

PMID36236276
PMCPMC9571292

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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.