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Sensors (Basel, Switzerland)2022; 22(16); 6052; doi: 10.3390/s22166052

Application of the Two-Dimensional Entropy Measures in the Infrared Thermography-Based Detection of Rider: Horse Bodyweight Ratio in Horseback Riding.

Abstract: As obesity is a serious problem in the human population, overloading of the horse's thoracolumbar region often affects sport and school horses. The advances in using infrared thermography (IRT) to assess the horse's back overload will shortly integrate the IRT-based rider-horse fit into everyday equine practice. This study aimed to evaluate the applicability of entropy measures to select the most informative measures and color components, and the accuracy of rider:horse bodyweight ratio detection. Twelve horses were ridden by each of the six riders assigned to the light, moderate, and heavy groups. Thermal images were taken pre- and post-exercise. For each thermal image, two-dimensional sample (SampEn), fuzzy (FuzzEn), permutation (PermEn), dispersion (DispEn), and distribution (DistEn) entropies were measured in the withers and the thoracic spine areas. Among 40 returned measures, 30 entropy measures were exercise-dependent, whereas 8 entropy measures were bodyweight ratio-dependent. Moreover, three entropy measures demonstrated similarities to entropy-related gray level co-occurrence matrix (GLCM) texture features, confirming the higher irregularity and complexity of thermal image texture when horses worked under heavy riders. An application of DispEn to red color components enables identification of the light and heavy rider groups with higher accuracy than the previously used entropy-related GLCM texture features.
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Publication Date: 2022-08-13 PubMed ID: 36015813PubMed Central: PMC9414866DOI: 10.3390/s22166052Google Scholar: Lookup
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  • Journal Article

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.

The research discusses the utilization of infrared thermography (IRT) in determining the impact of a rider’s bodyweight ratio on the horse’s thoracolumbar region, especially applicable in sports and school horse contexts. Using two-dimensional entropy measures, the study intends to find more precise and informative measures to accurately detect the rider-horse bodyweight ratio, contributing to substantial gains in equine practice.

Objective and Methodology of the Study

  • The main objective of the study is to examine the usage and effectiveness of entropy measures, specifically in determining the most informative measures and color components, to accurately evaluate the bodyweight ratio between the rider and the horse.
  • Twelve horses were ridden by six riders, each of whom were categorized into light, moderate, and heavy groups. Thermal images of the horses were captured before and after exercise.
  • Five types of two-dimensional entropy measures were conducted on each thermal image, including sample (SampEn), dispersion (DispEn), fuzzy (FuzzEn), permutation (PermEn), and distribution (DistEn) entropies. This data analysis took place across two body areas on the horses – the withers and the thoracic spine area.

Results of the Study

  • Out of the forty measures returned, thirty were found to be dependent on the exercise, and eight were affected by the bodyweight ratio.
  • Three out of the five entropy measures exhibited similarities to entropy-related gray level co-occurrence matrix (GLCM), which pointed out the increased irregularity and texture complexity in the thermal images when horses were ridden by heavier riders.
  • The research found that applying DispEn to the red color components led to better identification of the light and heavy rider groups, showcasing a higher level of accuracy than previously used entropy-related GLCM texture methods.

Importance and Implications of the Study

  • This research may have significant implications in the field of equine treatment and wellness. Specifically, the use of infrared thermography (IRT), in conjunction with two-dimensional entropy measures, can provide a new method to evaluate horse-rider fit, contributing to the overall equine health and performance.
  • The study’s findings suggest that rider weight does indeed have a measurable impact on the horse, which might lead to regulations or recommendations for weight thresholds or ratios in sports and school horses.
  • Additionally, the accurate identification of the rider-horse bodyweight ratio can be used to guide practice routines and treatment plans for both sport and school horses, thereby improving their performance and wellbeing.

Cite This Article

APA
Domino M, Borowska M, Zdrojkowski Ł, Jasiński T, Sikorska U, Skibniewski M, Maśko M. (2022). Application of the Two-Dimensional Entropy Measures in the Infrared Thermography-Based Detection of Rider: Horse Bodyweight Ratio in Horseback Riding. Sensors (Basel), 22(16), 6052. https://doi.org/10.3390/s22166052

Publication

Sensors (Basel, Switzerland)
ISSN: 1424-8220
NlmUniqueID: 101204366
Country: Switzerland
Language: English
Volume: 22
Issue: 16
PII: 6052

Researcher Affiliations

Domino, Małgorzata
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Borowska, Marta
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.
Zdrojkowski, Łukasz
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Jasiński, Tomasz
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Sikorska, Urszula
  • Department of Animal Breeding, Institute of Animal Science, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Skibniewski, Michał
  • Department of Morphological Sciences, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-776 Warsaw, Poland.
Maśko, Małgorzata
  • Department of Animal Breeding, Institute of Animal Science, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.

MeSH Terms

  • Animals
  • Back
  • Biomechanical Phenomena
  • Body Weight
  • Entropy
  • Horses
  • Humans
  • Sports
  • Thermography

Grant Funding

  • WI/WM-IIB/2/2021 / Polish Ministry of Science and Higher Education

Conflict of Interest Statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Citations

This article has been cited 2 times.
  1. Perpetuini D, Formenti D, Cardone D, Trecroci A, Rossi A, Di Credico A, Merati G, Alberti G, Di Baldassarre A, Merla A. Can Data-Driven Supervised Machine Learning Approaches Applied to Infrared Thermal Imaging Data Estimate Muscular Activity and Fatigue?. Sensors (Basel) 2023 Jan 11;23(2).
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  2. Górski K, Borowska M, Stefanik E, Polkowska I, Turek B, Bereznowski A, Domino M. Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model.. Biomedicines 2022 Nov 13;10(11).
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