Evidence map›Paper›PMID 30458788›Full record

ArticleBiomedical engineering online2018

Modeling hind-limb kinematics using a bio-inspired algorithm with a local search.

S Ivvan Valdez, Josué González-Sandoval, Sergio Dueñas-Jiménez, Nancy Elizabeth Franco Rodríguez, Sulema Torres-Ramos, Gerardo Mendizabal-Ruiz

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 1 country.

S Ivvan ValdezDivisión de Ingenierías, Universidad de Guanajuato, Carr. Salamanca-Valle de Santiago km 3.5+1.8, 36885, Salamanca, Guanajuato, México.
Josué González-SandovalDepartamento de Ciencias Computacionales, Universidad de Guadalajara, Av.Revolución 1500, Guadalajara, Jalisco, México.
Sergio Dueñas-JiménezDepartamento de Neurociencias, Universidad de Guadalajara, Sierra Mojada 950, Guadalajara, Jalisco, México.
Nancy Elizabeth Franco RodríguezDepartamento de Farmacobiología, Universidad de Guadalajara, Blvd. Marcelino García Barragan, 1421, Guadalajara, Jalisco, México.
Sulema Torres-RamosDepartamento de Ciencias Computacionales, Universidad de Guadalajara, Av.Revolución 1500, Guadalajara, Jalisco, México.
Gerardo Mendizabal-RuizDepartamento de Ciencias Computacionales, Universidad de Guadalajara, Av.Revolución 1500, Guadalajara, Jalisco, México. gerardo.mendizabal@academicos.udg.mx.
Universidad de Guadalajara · MXUniversidad de Guanajuato · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLaboratory rats play a critical role in research because they provide a biological model that can be used for evaluating the affectation of diseases and injuries, and for the evaluation of the effectiveness of new drugs and treatments. The analysis of locomotion in laboratory rats facilitates the understanding of motor defects in many diseases, as well as the damage and recovery after peripheral and central nervous system injuries. However, locomotion analysis of rats remains a great challenge due to the necessity of labor intensive manual annotations of video data required to obtain quantitative measurements of the kinematics of the rodent extremities. In this work, we present a method that is based on the use of a bio-inspired algorithm that fits a kinematic model of the hind limbs of rats to binary images corresponding to the segmented marker of images corresponding to the rat's gait. The bio-inspired algorithm combines a genetic algorithm for a group of the optimization variables with a local search for a second group of the optimization variables.

resultsOur results indicate the feasibility of employing the proposed approach for the automatic annotation and analysis of the locomotion patterns of the posterior extremities of laboratory rats.

conclusionsThe adjustment of the hind limb kinematic model to markers of the video frames corresponding to rat's gait sequences could then be used to analyze the motion patterns during the steps, which, in turn, can be useful for performing quantitative evaluations of the effect of lesions and treatments on rats models.

Indexed as

AlgorithmsComputational BiologyLocomotionAnimalsBiomechanical PhenomenaGaitHindlimbJointsMotionRatsSoftwareVideo RecordingGenetic algorithmHind limbKinematics analysisLaboratory ratsLocal search

Identifiers

PMID30458788
PMCPMC6245690
OpenAlexW2900920706

What OpenQuestion holds

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LicenceCC BY
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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.