bioRxivZoology
Technology applications in bovine gait analysis: a scoping review
Abstract
Quantitative bovine gait analysis using technology has evolved significantly over the last two decades. However, subjective methods of gait assessment using visual locomotion scoring remain the primary on-farm and experimental approach. The objective of this review is to map research trends in quantitative bovine gait analysis and to explore the technologies that have been utilized to measure biomechanical parameters of gait. A scoping literature review was conducted according to PRISMA guidelines. A search algorithm based on PICO framework generated three components - bovine, gait, and technology - to address our objectives. Three online databases were searched for original work published from January 2000 to June 2020. A two-step screening process was then conducted, starting with the review of article titles and abstracts based on inclusion criteria. A remaining 125 articles then underwent a full-text assessment, resulting in 82 final articles. Thematic analysis of research aims resulted in four major themes among the studies: gait/claw biomechanics, lameness detection, intervention/comparison, and system development. Lameness detection (55 % of studies) was the most common reason for technology use. Studies in the field of bovine gait analysis used three main technologies: force and pressure platforms (FPP), vision-based systems (VB), and accelerometers. FPP were the first and most popular technologies to evaluate bovine gait and were used in 58.5 % of studies. They include force platforms, pressure mapping systems, and weight distribution platforms. The second most applied technology was VB (34.1 % of studies), which predominately consists of video analysis and image processing systems. Accelerometers, another technological method to measure gait characteristics, were used in 14.6 % of studies. A strong demand for automatic lameness detection influences the path of development for quantitative gait analysis technologies. Although progress has been made, more research is needed to achieve more accurate, practical, and user-friendly technologies.
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- A simple analytical model for predicting locomotive ground reaction forces
Melany Opolz, Sara G. Moshage, … Mariana E. Kersh·bioRxiv·Dec 9, 2024
- Technical Note: DeepLabCut-Display: open-source desktop application for visualizing and analyzing two-dimensional gait parameter data in livestock
J. Shirey, M. Smythe, … S. A. Brooks·bioRxiv·Oct 30, 2023
- Discovering subclinical effects of limited outdoor access on gait and hoof health of cows housed in movement-restricted environments
Shabnaz Mokhtarnazif, Amir Nejati, … E. Vasseur·bioRxiv·Jan 29, 2026
- Evaluating machine learning algorithms to predict lameness in dairy cattle
R. Neupane, A. Aryal, … S. Paudyal·bioRxiv·Mar 13, 2024
- Two-dimensional video-based analysis of human gait using pose estimation
J. Stenum, C. Rossi, R. T. Roemmich·bioRxiv·Jul 24, 2020
- Validating the Nordic Thingy:53 as an Accessible Tool for Equine Behavioural Analysis using Edge AI
Rhune Vanden Eynde, Ivan Herrera Olivares, Lucinda Kirkpatrick·bioRxiv·Dec 10, 2025