Evidence map›Paper›PMID 40370838›Full record

ArticleFrontiers in veterinary science2025

Analysis of dog movement using a single accelerometer in different body positions-a new approach.

Rainer da Silva Reinstein, Franciéli Mallmann Pozzobon, Pâmela Caye, Amanda Oliveira Paraguassú, Brenda Viviane Götz Socolhoski, Otávio Henrique de Melo Schiefler, Ricardo Pozzobon, Daniel Curvello de Mendonça Müller, Maurício Veloso Brun

Abstract read
In one paragraph

Article in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. 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

9 authors.

Rainer da Silva ReinsteinPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Franciéli Mallmann PozzobonPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Pâmela CayePostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Amanda Oliveira ParaguassúPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Brenda Viviane Götz SocolhoskiPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Otávio Henrique de Melo SchieflerPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Ricardo PozzobonPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.
Daniel Curvello de Mendonça MüllerDepartment of Small Animal Clinic, Rural Science Center, Federal University of Santa Maria, Santa Maria, Brazil.
Maurício Veloso BrunPostgraduate Program in Veterinary Medicine, Center for Rural Sciences, Federal University of Santa Maria, Santa Maria, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The analysis of canine locomotion has significantly advanced over the past few decades with the advent of technologies that enable more precise measurements. Traditional methods, such as force platforms and three-dimensional kinematic systems, though accurate, are often costly and require specialized equipment, limiting their broader application. This study aims to evaluate an alternative approach using a single triaxial accelerometer positioned in different anatomical regions (neck, sternum, pelvis, and right knee) to analyze gait patterns in healthy dogs. Methods: Twenty-four clinically healthy dogs were used, divided into two groups based on body weight: ≤ 15 kg (G-15) and >15 kg (G+15). A wireless triaxial accelerometer sensor was utilized. Acceleration data were collected during walking and trotting in different anatomical positions: neck, sternum, pelvis, and right knee. The data were processed using Fourier analysis to extract harmonic frequencies and analyzed for acceleration peaks and autocorrelation to assess gait symmetry. Results: The findings showed that larger and heavier dogs (G+15) exhibited lower movement frequencies and more stable patterns, especially during trotting, while smaller and lighter dogs (G-15) demonstrated higher frequencies and greater variability. Significant differences in acceleration peaks were observed between body regions, with the pelvis and knee showing the highest values. However, harmonic frequencies did not vary significantly between the different anatomical regions. The autocorrelation analysis revealed that, in larger dogs, the sternum and pelvis regions presented greater consistency, indicating enhanced stability during locomotion. Discussion: These findings suggest that using a single accelerometer in different body regions is a practical and effective methodology for gait analysis in dogs, allowing the identification of locomotion differences among dogs of varying sizes and movement phases. This approach offers an accurate alternative for veterinary biomechanical studies, with potential clinical applications in the diagnosis and monitoring of gait abnormalities. The use of a single triaxial accelerometer proved effective for canine gait analysis, revealing differences by body weight. The sternum and pelvis are ideal monitoring regions, suggesting applications in biomechanical and clinical studies.

Indexed as

accelerometrybiomechanicsdogsgait analysislocomotion

Identifiers

PMID40370838
PMCPMC12076518

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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.