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Home / Equine Research Bank / PLoS One / Automatic methods of hoof-on and -off detection in horses us...
PloS one2021; 16(7); e0254813; doi: 10.1371/journal.pone.0254813

Automatic methods of hoof-on and -off detection in horses using wearable inertial sensors during walk and trot on asphalt, sand and grass.

Abstract: Detection of hoof-on and -off events are essential to gait classification in horses. Wearable sensors have been endorsed as a convenient alternative to the traditional force plate-based method. The aim of this study was to propose and validate inertial sensor-based methods of gait event detection, reviewing different sensor locations and their performance on different gaits and exercise surfaces. Eleven horses of various breeds and ages were recruited to wear inertial sensors attached to the hooves, pasterns and cannons. Gait events detected by pastern and cannon methods were compared to the reference, hoof-detected events. Walk and trot strides were recorded on asphalt, grass and sand. Pastern-based methods were found to be the most accurate and precise for detecting gait events, incurring mean errors of between 1 and 6ms, depending on the limb and gait, on asphalt. These methods incurred consistent errors when used to measure stance durations on all surfaces, with mean errors of 0.1 to 1.16% of a stride cycle. In conclusion, the methods developed and validated here will enable future studies to reliably detect equine gait events using inertial sensors, under a wide variety of field conditions.
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Publication Date: 2021-07-26 PubMed ID: 34310630PubMed Central: PMC8312981DOI: 10.1371/journal.pone.0254813Google Scholar: Lookup
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  • Journal Article
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  • Non-U.S. Gov't

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This research paper examined the use of wearable inertial sensors for detecting hoof-on and -off events during horse gaits. It concluded that sensors attached to the pastern, a part of a horse’s leg, were most accurate and consistent for this purpose, across different surfaces and gaits.

Objective of the Study

  • The aim of the study was to propose and test new methods for detecting ‘gait events’ in horses using inertial sensors, with a specific focus on identifying when the horse’s hoof has contact with the ground (hoof-on) and when it doesn’t (hoof-off).
  • Such detection is critical for the classification of horse gaits. While traditionally, force plates were used for this purpose, the researchers wanted to explore the potential and effectiveness of wearable sensors.

Methodology

  • Eleven horses of different breeds and ages were recruited for the study.
  • The researchers attached sensors to different parts of the horse’s leg, including the hooves, pasterns and cannons.
  • They then recorded gait events during walk and trot strides on different surfaces – asphalt, grass, and sand.

Comparisons and Conclusions

  • The researchers compared the gait events detected by the pastern and cannon methods to the hoof-detected events, which were taken as the reference.
  • They found that the pastern-based methods were the most accurate and precise for detecting gait events. The mean error for such detection on asphalt surface was between 1 and 6 ms, depending on the limb and gait.
  • The pastern-based methods also provided consistent measurements of stance durations on all surfaces, with mean errors ranging from 0.1 to 1.16% of a stride cycle.
  • The study concluded that the methods developed could enable future researchers to accurately detect equine gait events using inertial sensors in a variety of field conditions.

Cite This Article

APA
Briggs EV, Mazzà C. (2021). Automatic methods of hoof-on and -off detection in horses using wearable inertial sensors during walk and trot on asphalt, sand and grass. PLoS One, 16(7), e0254813. https://doi.org/10.1371/journal.pone.0254813

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 16
Issue: 7
Pages: e0254813

Researcher Affiliations

Briggs, Eloise V
  • Department of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom.
  • INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.
Mazzà, Claudia
  • Department of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom.
  • INSIGNEO Institute for in silico Medicine, University of Sheffield, Sheffield, United Kingdom.

MeSH Terms

  • Animals
  • Horses / physiology
  • Hydrocarbons
  • Poaceae
  • Sand
  • Walk Test
  • Wearable Electronic Devices / standards

Conflict of Interest Statement

The research of EVB is funded by Worldbase Ltd. and this study was also supported by the UK EPSRC (EP/K03877X/1, EP/S032940/1, https://epsrc.ukri.org). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The commercial funder Worldbase Ltd. is a manufacturing company, specialising in agricultural machinery and currently has no products or services, existing or in design, related to the content of this research. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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Citations

This article has been cited 6 times.
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