FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
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.
© 2021 The Authors. Equine Veterinary Journal published by John Wiley & Sons Ltd on behalf of EVJ Ltd.
Get Full Text
Publication Date: 2021-06-23 PubMed ID: 34085312PubMed Central: PMC9290451DOI: 10.1111/evj.13451Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • 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 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 Bragança 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

Equine veterinary journal
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 René
  • 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 Bragança, 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.

References

This article includes 26 references
  1. Serra Bragança FM, Rhodin M, van Weeren PR. On the brink of daily clinical application of objective gait analysis: What evidence do we have so far from studies using an induced lameness model?. Vet J 2018 Apr;234:11-23.
    pubmed: 29680381doi: 10.1016/j.tvjl.2018.01.006google scholar: lookup
  2. Buchner HH, Savelberg HH, Schamhardt HC, Barneveld A. Head and trunk movement adaptations in horses with experimentally induced fore- or hindlimb lameness.. Equine Vet J 1996 Jan;28(1):71-6.
    pubmed: 8565958doi: 10.1111/j.2042-3306.1996.tb01592.xgoogle scholar: lookup
  3. Kelmer G, Keegan KG, Kramer J, Wilson DA, Pai FP, Singh P. Computer-assisted kinematic evaluation of induced compensatory movements resembling lameness in horses trotting on a treadmill.. Am J Vet Res 2005 Apr;66(4):646-55.
    pubmed: 15900946doi: 10.2460/ajvr.2005.66.646google scholar: lookup
  4. Rhodin M, Pfau T, Roepstorff L, Egenvall A. Effect of lungeing on head and pelvic movement asymmetry in horses with induced lameness.. Vet J 2013 Dec;198 Suppl 1:e39-45.
    pubmed: 24140227doi: 10.1016/j.tvjl.2013.09.031google scholar: lookup
  5. Starke SD, Willems E, May SA, Pfau T. Vertical head and trunk movement adaptations of sound horses trotting in a circle on a hard surface.. Vet J 2012 Jul;193(1):73-80.
    pubmed: 22104508doi: 10.1016/j.tvjl.2011.10.019google scholar: lookup
  6. Weishaupt MA. Adaptation strategies of horses with lameness.. Vet Clin North Am Equine Pract 2008 Apr;24(1):79-100.
    pubmed: 18314037doi: 10.1016/j.cveq.2007.11.010google scholar: lookup
  7. Bell RP, Reed SK, Schoonover MJ, Whitfield CT, Yonezawa Y, Maki H, Pai PF, Keegan KG. Associations of force plate and body-mounted inertial sensor measurements for identification of hind limb lameness in horses.. Am J Vet Res 2016 Apr;77(4):337-45.
    pubmed: 27027831doi: 10.2460/ajvr.77.4.337google scholar: lookup
  8. Buchner HH, Savelberg HH, Schamhardt HC, Barneveld A. Bilateral lameness in horses--a kinematic study.. Vet Q 1995 Sep;17(3):103-5.
    pubmed: 8525594doi: 10.1080/01652176.1995.9694543google scholar: lookup
  9. Pataky TC, Robinson MA, Vanrenterghem J. Vector field statistical analysis of kinematic and force trajectories.. J Biomech 2013 Sep 27;46(14):2394-401.
    pubmed: 23948374doi: 10.1016/j.jbiomech.2013.07.031google scholar: lookup
  10. Ramsay JO, Silverman BW. Principal components analysis for functional data. Functional data analysis 2005;147–72.
  11. Diloksumpan P, Abinzano F, de Ruijter M, Mensinga A, Plomp S, Khan I. The complexity of joint regeneration: how an advanced implant could fail by its in vivo proven bone component. J. Trial Error .
    doi: 10.36850/e3google scholar: lookup
  12. Bächi B, Wiestner T, Stoll A, Waldern NM, Imboden I, Weishaupt MA. Changes of ground reaction force and timing variables in the course of habituation of horses to the treadmill. J Equine Vet Sci 2018;63:13–23.
  13. Bragança FS, Roepstorff C, Rhodin M, Pfau T, Van Weeren PR, Roepstorff L. Quantitative lameness assessment in the horse based on upper body movement symmetry: the effect of different filtering techniques on the quantification of motion symmetry. Biomed Signal Process Control 2020;57:101674.
  14. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 1995;57(1):289–300.
  15. Keegan KG, Dent EV, Wilson DA, Janicek J, Kramer J, Lacarrubba A, Walsh DM, Cassells MW, Esther TM, Schiltz P, Frees KE, Wilhite CL, Clark JM, Pollitt CC, Shaw R, Norris T. Repeatability of subjective evaluation of lameness in horses.. Equine Vet J 2010 Mar;42(2):92-7.
    pubmed: 20156242doi: 10.2746/042516409x479568google scholar: lookup
  16. Weishaupt MA, Wiestner T, Hogg HP, Jordan P, Auer JA. Compensatory load redistribution of horses with induced weightbearing hindlimb lameness trotting on a treadmill.. Equine Vet J 2004 Dec;36(8):727-33.
    pubmed: 15656505doi: 10.2746/0425164044848244google scholar: lookup
  17. Hobbs SJ, Robinson MA, Clayton HM. A simple method of equine limb force vector analysis and its potential applications.. PeerJ 2018;6:e4399.
    pmc: PMC5827015pubmed: 29492341doi: 10.7717/peerj.4399google scholar: lookup
  18. Hobbs SJ, Nauwelaerts S, Sinclair J, Clayton HM, Back W. Sagittal plane fore hoof unevenness is associated with fore and hindlimb asymmetrical force vectors in the sagittal and frontal planes.. PLoS One 2018;13(8):e0203134.
    pmc: PMC6114892pubmed: 30157249doi: 10.1371/journal.pone.0203134google scholar: lookup
  19. Worsley KJ, Taylor JE, Tomaiuolo F, Lerch J. Unified univariate and multivariate random field theory.. Neuroimage 2004;23 Suppl 1:S189-95.
    pubmed: 15501088doi: 10.1016/j.neuroimage.2004.07.026google scholar: lookup
  20. Adler RJ. Some new random field tools for spatial analysis. Stochastic Environ Res Risk Assessment 2008;22(6):809–22.
  21. van Weeren PR, van den Bogert AJ, Barneveld A. A quantitative analysis of skin displacement in the trotting horse.. Equine Vet J Suppl 1990 Jun;(9):101-9.
    pubmed: 9259817doi: 10.1111/j.2042-3306.1990.tb04745.xgoogle scholar: lookup
  22. Serra Bragança FM, Rhodin M, Wiestner T, Hernlund E, Pfau T, van Weeren PR, Weishaupt MA. Quantification of the effect of instrumentation error in objective gait assessment in the horse on hindlimb symmetry parameters.. Equine Vet J 2018 May;50(3):370-376.
    pmc: PMC5900976pubmed: 29032614doi: 10.1111/evj.12766google scholar: lookup
  23. Williams GE, Silverman BW, Wilson AM, Goodship AE. Disease-specific changes in equine ground reaction force data documented by use of principal component analysis.. Am J Vet Res 1999 May;60(5):549-55.
    pubmed: 10328423
  24. Weidow J, Tranberg R, Saari T, Kärrholm J. Hip and knee joint rotations differ between patients with medial and lateral knee osteoarthritis: gait analysis of 30 patients and 15 controls.. J Orthop Res 2006 Sep;24(9):1890-9.
    pubmed: 16838360doi: 10.1002/jor.20194google scholar: lookup
  25. Astephen JL, Deluzio KJ, Caldwell GE, Dunbar MJ. Biomechanical changes at the hip, knee, and ankle joints during gait are associated with knee osteoarthritis severity.. J Orthop Res 2008 Mar;26(3):332-41.
    pubmed: 17960658doi: 10.1002/jor.20496google scholar: lookup
  26. Shull PB, Shultz R, Silder A, Dragoo JL, Besier TF, Cutkosky MR, Delp SL. Toe-in gait reduces the first peak knee adduction moment in patients with medial compartment knee osteoarthritis.. J Biomech 2013 Jan 4;46(1):122-8.
    pubmed: 23146322doi: 10.1016/j.jbiomech.2012.10.019google scholar: lookup

Citations

This article has been cited 6 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 Bragança 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
  3. St George L, Nankervis K, Walker V, Maddock C, Robinson A, Sinclair J, Hobbs SJ. A Feasibility Study to Determine Whether Neuromuscular Adaptations to Equine Water Treadmill Exercise Can Be Detected Using Synchronous Surface Electromyography and Kinematic Data. Animals (Basel) 2025 Nov 1;15(21).
    doi: 10.3390/ani15213189pubmed: 41227519google scholar: lookup
  4. Chen W, Gong M, Pu F, Ren W, Tan J, Fan Y. mRUST Estimation of Tibial Fracture Healing After Intramedullary Nailing Using Deep Forest Model with a Genetically Optimized Wearable Sensor Layout. Ann Biomed Eng 2025 Dec;53(12):3302-3313.
    doi: 10.1007/s10439-025-03873-1pubmed: 41055854google scholar: lookup
  5. Scheike AS, Plomp S, Fugazzola MC, Meurot C, Berenbaum F, van Weeren PR, Tryfonidou MA, von Hegedus JH. The Anti-Inflammatory Effects of Liraglutide in Equine Inflammatory Joint Models. J Orthop Res 2025 May;43(5):893-903.
    doi: 10.1002/jor.26050pubmed: 39904754google scholar: lookup
  6. Byström A, Hardeman AM, Engell MT, Swagemakers JH, Koene MHW, Serra-Bragança FM, Rhodin M, Hernlund E. Normal variation in pelvic roll motion pattern during straight-line trot in hand in warmblood horses. Sci Rep 2023 Oct 10;13(1):17117.
    doi: 10.1038/s41598-023-44223-2pubmed: 37816848google scholar: lookup
Subscribe to our newsletter
Join 99,850 horse owners like you who receive our email updates on horse health and nutrition.