ArticlePloS one2023
Detecting fatigue of sport horses with biomechanical gait features using inertial sensors.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Five Domains, Multiple Realities: A Multidimensional Analysis of Equine Welfare in Equestrian Events in Brazil.Animals : an open access journal from MDPI · 2026Article
- Quantitative assessment of gait alterations and variability in sulky-driven Standardbred trotters after a standardised exercise test.Equine veterinary journal · 2026Article
- Technologies for equine welfare and performance monitoring under field conditions - Where do we stand?Equine veterinary journal · 2026Review
- Priorities and Recommendations for Using Artificial Intelligence (AI) to Improve Equid Health and Welfare.Animals : an open access journal from MDPI · 2026Article
- Changes in Fitness Parameters in Ridden Trained Showjumping Horses After Healing of Gastric Ulcers: Preliminary Results.Veterinary sciences · 2025Article
- Dynamic Mobilization Exercises Improve Activity and Stride Parameters Measured with Accelerometry in Sedentary Horses.Animals : an open access journal from MDPI · 2025Article
- Gait kinematics at trot before and after repeated ridden exercise tests in young Friesian stallions during a fatiguing 10-week training program.Frontiers in veterinary science · 2025Article
- A machine learning approach to identify stride characteristics predictive of musculoskeletal injury, enforced rest and retirement in Thoroughbred racehorses.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Detection of fatigue helps prevent injuries and optimize the performance of horses. Previous studies tried to determine fatigue using physiological parameters. However, measuring the physiological parameters, e.g., plasma lactate, is invasive and can be affected by different factors. In addition, the measurement cannot be done automatically and requires a veterinarian for sample collection. This study investigated the possibility of detecting fatigue non-invasively using a minimum number of body-mounted inertial sensors. Using the inertial sensors, sixty sport horses were measured during walk and trot before and after high and low-intensity exercises. Then, biomechanical features were extracted from the output signals. A number of features were assigned as important fatigue indicators using neighborhood component analysis. Based on the fatigue indicators, machine learning models were developed for classifying strides to non-fatigue and fatigue. As an outcome, this study confirmed that biomechanical features can indicate fatigue in horses, such as stance duration, swing duration, and limb range of motion. The fatigue classification model resulted in high accuracy during both walk and trot. In conclusion, fatigue can be detected during exercise by using the output of body-mounted inertial sensors.
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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.