Equine veterinary journal2021; 54(3); 626-633; doi: 10.1111/evj.13451

Continuous versus discrete data analysis for gait evaluation of horses with induced bilateral hindlimb lameness.

Abstract: Gait kinematics measured during equine gait analysis are typically evaluated by analysing (asymmetry-based) discrete variables (eg, peak values) obtained from continuous kinematic signals (eg, timeseries of datapoints). However, when used for the assessment of complex cases of lameness, such as bilateral lameness, discrete variable analysis might overlook relevant functional adaptations. Objective: The overall aim of this paper is to compare continuous and discrete data analysis techniques to evaluate kinematic gait adaptations to lameness. Methods: Method comparison. Methods: Sixteen healthy Shetland ponies, enrolled in a research programme in which osteochondral defects were created on the medial trochlear ridges of both femurs, were used in this study. Kinematic data were collected at trot on a treadmill before and at 3 and 6 months after surgical intervention. Statistical parametric mapping and linear mixed models were used to compare kinematic variables between and within timepoints. Results: Both continuous and discrete data analyses identified changes in pelvis and forelimb kinematics. Discrete data analyses showed significant changes in hindlimb and back kinematics, where such differences were not found to be significant by continuous data analysis. In contrast, continuous data analysis provided additional information on the timing and duration of the differences found. Conclusions: A limited number of ponies were included. Conclusions: The use of continuous data provides additional information regarding gait adaptations to bilateral lameness that is complementary to the analysis of discrete variables. The main advantage lies in the additional information regarding time dependence and duration of adaptations, which offers the opportunity to identify functional adaptations during all phases of the stride cycle, not just the events related to peak values.
Publication Date: 2021-06-23 PubMed ID: 34085312PubMed Central: PMC9290451DOI: 10.1111/evj.13451Google Scholar: Lookup
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  • Journal Article

Summary

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The research aims at comparing the effectiveness of continuous and discrete data analysis techniques in evaluating changes in equine gait due to bilateral lameness. The study finds that while both methods spot changes in the animal’s movement, the continuous analysis offers deeper insight by signifying the timing and duration of observable differences.

Study Methodology

  • The study was conducted on sixteen healthy Shetland ponies, enrolled in a research program that artificially induced osteochondral defects on the medial trochlear ridges of both femurs (essentially creating bilateral hindlimb lameness).
  • Walking data of the ponies was recorded while they trotted on a treadmill before the surgery, as well as at three and six months post-surgery.
  • The researchers used Statistical Parametric Mapping and linear mixed models to analyze the changes in kinematic variables over different time points.

Research Findings

  • Both continuous and discrete data analysis techniques successfully identified alterations in the pelvis and forelimb kinematics.
  • However, discrete data analysis alone detected significant transformations in the kinematics of the hindlimb and the back, which continuous data analysis didn’t classify as noteworthy.
  • On the other hand, continuous data analysis supplied extra details about the timing and the duration of the kinematic differences, which discrete data analysis couldn’t provide.

Conclusion

  • The research concludes that although the sample of ponies was limited, the use of continuous data analysis is complementary to discrete variable analysis.
  • Continuous data analysis offers the significant advantage of studying the time dependency and duration of gait adaptations, enabling the identification of functional alterations throughout all phases of the walking cycle.
  • This presents a more inclusive picture that goes beyond only assessing the animal’s movements at peak values, thereby providing a comprehensive evaluation of the equine’s gait adaptations due to induced bilateral hindlimb lameness.

Cite This Article

APA
Smit IH, Hernlund E, Brommer H, van Weeren PR, Rhodin M, Serra Braganu00e7a FM. (2021). Continuous versus discrete data analysis for gait evaluation of horses with induced bilateral hindlimb lameness. Equine Vet J, 54(3), 626-633. https://doi.org/10.1111/evj.13451

Publication

ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 54
Issue: 3
Pages: 626-633

Researcher Affiliations

Smit, Ineke H
  • Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Hernlund, Elin
  • Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Brommer, Harold
  • Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
van Weeren, P Renu00e9
  • Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
Rhodin, Marie
  • Department of Anatomy, Physiology and Biochemistry, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Serra Braganu00e7a, Filipe M
  • Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.

MeSH Terms

  • Animals
  • Biomechanical Phenomena
  • Data Analysis
  • Forelimb
  • Gait
  • Hindlimb
  • Horse Diseases / diagnosis
  • Horses
  • Lameness, Animal / diagnosis

Grant Funding

  • LLP22 / Dutch Arthritis Foundation

Conflict of Interest Statement

No competing interests have been declared.

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Citations

This article has been cited 2 times.
  1. Parmentier JIM, Bosch S, van der Zwaag BJ, Weishaupt MA, Gmel AI, Havinga PJM, van Weeren PR, Braganca FMS. Prediction of continuous and discrete kinetic parameters in horses from inertial measurement units data using recurrent artificial neural networks.. Sci Rep 2023 Jan 13;13(1):740.
    doi: 10.1038/s41598-023-27899-4pubmed: 36639409google scholar: lookup
  2. St George LB, Spoormakers TJP, Smit IH, Hobbs SJ, Clayton HM, Roy SH, van Weeren PR, Richards J, Serra Braganu00e7a FM. Adaptations in equine appendicular muscle activity and movement occur during induced fore- and hindlimb lameness: An electromyographic and kinematic evaluation.. Front Vet Sci 2022;9:989522.
    doi: 10.3389/fvets.2022.989522pubmed: 36425119google scholar: lookup