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Home / Equine Research Bank / PLoS One / Automatic detection of break-over phase onset in horses usin...
PloS one2020; 15(5); e0233649; doi: 10.1371/journal.pone.0233649

Automatic detection of break-over phase onset in horses using hoof-mounted inertial measurement unit sensors.

Abstract: A prolonged break-over phase might be an indication of a variety of musculoskeletal disorders and can be measured with optical motion capture (OMC) systems, inertial measurement units (IMUs) and force plates. The aim of this study was to present two algorithms for automatic detection of the break-over phase onset from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. The performance of these algorithms was evaluated by internal validation with an OMC system and a force plate separately. Seven Warmblood horses were equipped with two wireless IMUs which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted over a force plate for internal validation while simultaneously the 3D position of three reflective markers, attached to lateral heel, lateral toe and lateral coronet of each hoof, were measured by six infrared cameras of an OMC system. The performance of the algorithms was evaluated by linear mixed model analysis. The acceleration algorithm was the most accurate with an accuracy between -9 and 23 ms and a precision around 24 ms (against OMC system), and an accuracy between -37 and 20 ms and a precision around 29 ms (against force plate), depending on gait and hoof. This algorithm seems promising for quantification of the break-over phase onset although the applicability for clinical purposes, such as lameness detection and evaluation of trimming and shoeing techniques, should be investigated more in-depth.
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Publication Date: 2020-05-29 PubMed ID: 32469939PubMed Central: PMC7259550DOI: 10.1371/journal.pone.0233649Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • 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 assesses the effectiveness of two algorithms in automatically detecting the start of the break-over phase in horse gaits using sensors mounted on the horses’ hoofs. The break-over phase is an important part of a horse’s gait and abnormalities in this phase may be indicative of musculoskeletal disorders. The algorithms available to automatically detect the onset of the break-over phase had their performance evaluated against other systems such as optical motion capture and force plates.

Experimental Design

  • Seven Warmblood horses were equipped with two wireless inertial measurement units (IMUs) attached to the lateral wall of the right front (RF) and hind (RH) hooves.
  • These horses were made to walk and trot over a force plate. The force plate served as one of the internal validation tools for the study.
  • At the same time, the 3D position of three reflective markers placed on each hoof of the horse was measured by six infrared cameras part of an optical motion capture (OMC) system. The OMC system served as another internal validation tool.

Algorithm Performance Evaluation

  • The algorithms’ performance was evaluated using linear mixed model analysis. This statistical method evaluates the extent to which each algorithm accurately detected the onset of the break-over phase by comparing algorithm results with measurements from the force plate and OMC system.
  • The study revealed that one of the algorithms, the acceleration algorithm, was more accurate than the other, with a precision ranging from -9 and 23 milliseconds when validated against the OMC system, and between -37 and 20 milliseconds when compared to the force plate.

Conclusions and Implications

  • The algorithm’s accuracy and precision indicate its potential for accurately identifying the onset of the break-over phase, though the range of accuracy could see some improvements.
  • The findings of the study propose that this acceleration algorithm despite its promise, should be investigated more in-depth for its applicability in real-world clinical applications. These may include in detecting lameness in horses, or evaluating the effectiveness of different hoof-trimming and shoeing techniques.

Cite This Article

APA
Tijssen M, Hernlund E, Rhodin M, Bosch S, Voskamp JP, Nielen M, Serra Braganςa FM. (2020). Automatic detection of break-over phase onset in horses using hoof-mounted inertial measurement unit sensors. PLoS One, 15(5), e0233649. https://doi.org/10.1371/journal.pone.0233649

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 15
Issue: 5
Pages: e0233649

Researcher Affiliations

Tijssen, M
  • Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Hernlund, E
  • Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Rhodin, M
  • Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Bosch, S
  • Inertia Technology B.V., Enschede, The Netherlands.
  • Department of Computer Science, Pervasive Systems Group, University of Twente, Enschede, The Netherlands.
Voskamp, J P
  • Rosmark Consultancy, Wekerom, The Netherlands.
  • Department Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Nielen, M
  • Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Serra Braganςa, F M
  • Department Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.

MeSH Terms

  • Algorithms
  • Animals
  • Biomechanical Phenomena
  • Biosensing Techniques
  • Hoof and Claw / physiology
  • Hoof and Claw / physiopathology
  • Horse Diseases / diagnosis
  • Horse Diseases / physiopathology
  • Horses / physiology
  • Musculoskeletal Diseases / diagnosis
  • Musculoskeletal Diseases / physiopathology
  • Musculoskeletal Diseases / veterinary
  • Musculoskeletal Physiological Phenomena
  • Walking
  • Wireless Technology

Conflict of Interest Statement

The authors have read the journal\'s policy and the authors of this manuscript have the following competing interests: S. Bosch is a paid employee of Inertia-Technology B.V., the company that sells the inertial sensor system used for data collection, and has received salary support for his role in this study. J.P. Voskamp is founder of Rosmark Consultancy and has received salary support for his role in this study. Inertia-Technology B.V., Rosmark Consultancy and Utrecht University are partners in the EquiMoves® corporation. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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