FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Heliyon / Tranquilizer effect on the Lyapunov exponents of lame horses...
Heliyon2020; 6(4); e03726; doi: 10.1016/j.heliyon.2020.e03726

Tranquilizer effect on the Lyapunov exponents of lame horses.

Abstract: Tranquilization of horses with acepromazine has been used to suppress erratic head movements and increase the accuracy of a lameness examination. Some equine clinicians believe that tranquilization with acepromazine will make lameness more evident by causing the horse to focus on adjusting its gait to avoid limb pain rather than its surroundings. The aim of this study was to investigate the effect of acepromazine on the Lyapunov exponents of lame horses. Ten lame horses were trotted in a straight line for a minimum of 25 strides. Kinematic data created by head movement were analyzed. Nonlinear analysis methods were applied to lame horse locomotion. The effect of acepromazine on the largest Lyapunov exponents of the lame horses were investigated. There was no statistically significant effect of acepromazine on the maximum value of Lyapunov exponents. The nonlinear dynamic methods can be used to analyze the gait in horses. Local stability of horse gait remains unchanged after the administration of acepromazine.
© 2020 The Authors.
Get Full Text
Publication Date: 2020-04-08 PubMed ID: 32322720PubMed Central: PMC7160577DOI: 10.1016/j.heliyon.2020.e03726Google 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 study investigates the impact of tranquilizer acepromazine on the locomotion of lame horses, specifically the Lyapunov exponents, and finds that there is no significant effect.

Context and Aim of the Study

  • The research focuses on the use of acepromazine tranquilization in lame horses, a practice often employed to curb erratic head movements. This in turn is expected to improve the precision of lameness examinations.
  • Some equine clinicians hypothesize that tranquilizing with acepromazine brings out lameness more prominently by forcing the horse to adjust its movement avoiding limb pain, rather than focusing on its surroundings.
  • The specific aim of this study was to investigate the influence of acepromazine on the Lyapunov exponents of lame horses. Lyapunov exponents are measures used in systems theory to analyze the rate of separation of infinitesimally close trajectories, providing a quantitative measure of the predictability of a dynamic system.

Methodology

  • A sample group of 10 lame horses were inclined to trot in a straight line for a minimum of 25 strides.
  • Data captured from the head movement of the horses were used for kinematic analysis.
  • Then, methods of nonlinear analysis were applied to the data collected from the locomotion of the lame horses.
  • Following the tranquilization of horses with acepromazine, the researchers assessed its impact on the largest Lyapunov exponents, which is a measure of the chaos or unpredictability of the horse’s movement.

Findings and Conclusions

  • Contrary to expectations, there was no statistically significant impact of acepromazine on the maximum value of Lyapunov exponents.
  • The findings suggest that the gait’s local stability of horses remains basically the same even after administering acepromazine.
  • Despite the tranquilizer not having a significant effect on the horses’ gait, the study concludes that nonlinear dynamic methods can still be effectively employed to analyze horse gait.

Cite This Article

APA
Zhao J, Marghitu DB, Schumacher J. (2020). Tranquilizer effect on the Lyapunov exponents of lame horses. Heliyon, 6(4), e03726. https://doi.org/10.1016/j.heliyon.2020.e03726

Publication

Heliyon
ISSN: 2405-8440
NlmUniqueID: 101672560
Country: England
Language: English
Volume: 6
Issue: 4
Pages: e03726

Researcher Affiliations

Zhao, J
  • Department of Mechanical Engineering, 1418 Wiggins Hall, Auburn University, Auburn, AL, 36849, USA.
Marghitu, D B
  • Department of Mechanical Engineering, 1418 Wiggins Hall, Auburn University, Auburn, AL, 36849, USA.
Schumacher, J
  • Department of Clinical Sciences, College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA.

References

This article includes 49 references
  1. Biewener A, Daniel T. A moving topic: control and dynamics of animal locomotion.. Biol. Lett. 2010;6:387–388.
    pmc: PMC2880073pubmed: 20410030
  2. Buchnner HHF, Kübber P, Zohmann E, Peham C. Sedation and antisedation as tools in equine lameness examination.. Equine Vet. J. 1999;31:227–230.
    pubmed: 10659257
  3. Buzzi UH, Stergiou N, Kurz MJ, Hageman PA, Heidel J. Nonlinear dynamics indicates aging affects variability during gait.. Clin. Biomech. 2003;18:435–443.
    pubmed: 12763440
  4. da Silva Azevedo M, De La Côrte FD, Brass KE, Gallio M, Pozzobon R, Lopes MAF, Lopes LFD. The use of xylazine or acepromazine does not interfere in the lameness evaluation by inertial sensors.. J. Equine Vet. Sci. 2015;35:27–30.
  5. Dingwell JB, Cusumano JP. Nonlinear time series analysis of normal and pathological human walking.. Chaos Interdiscipl. J. Nonlinear Sci. 2000;10:848.
    pubmed: 12779434
  6. Dingwell JB, Cusumano JP, Cavanagh PR, Sternad D. Local dynamic stability versus kinematic variability of continuous overground and treadmill walking.. J. Biomech. Eng. 2001;123:27.
    pubmed: 11277298
  7. Dingwell JB, Cusumano JP, Sternad D, Cavanagh PR. Slower speeds in patients with diabetic neuropathy lead to improved local dynamic stability of continuous overground walking.. J. Biomech. 2000;33:1269–1277.
    pubmed: 10899337
  8. Fallah Yakhdani HR, Bafghi HA, Meijer OG, Bruijn SM, van den Dikkenberg N, Stibbe AB, van Royen BJ, van Dieën JH. Stability and variability of knee kinematics during gait in knee osteoarthritis before and after replacement surgery.. Clin. Biomech. 2010;25:230–236.
    pubmed: 20060628
  9. Fraser AM, Swinney HL. Independent coordinates for strange attractors from mutual information.. Phys. Rev. A. 1986;33:1134.
    pubmed: 9896728
  10. Goshvarpour Atefeh, Goshvarpour Ateke. Nonlinear analysis of human gait signals.. Int. J. Inf. Eng. Electron. Bus. 2012;4:15.
  11. Hinchcliff KW, Kaneps AJ, Geor RJ. Equine Sports Medicine and Surgery E-Book.. Elsevier Health Sciences; 2013.
  12. Hollman JH, Watkins MK, Imhoff AC, Braun CE, Akervik KA, Ness DK. Complexity, fractal dynamics and determinism in treadmill ambulation: implications for clinical biomechanists.. Clin. Biomech. 2016;37:91–97.
    pubmed: 27380204
  13. Jordan K, Challis JH, Cusumano JP, Newell KM. Stability and the time-dependent structure of gait variability in walking and running.. Hum. Mov. Sci. 2009;28:113–128.
    pubmed: 19042050
  14. Kang HG, Dingwell JB. Effects of walking speed, strength and range of motion on gait stability in healthy older adults.. J. Biomech. 2008;41:2899–2905.
    pmc: PMC9135052pubmed: 18790480
  15. Kantz H, Schreiber T. Nonlinear Time Series Analysis.. Cambridge University Press; 2003.
  16. 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;42:92–97.
    pubmed: 20156242
  17. Keegan KG, Kramer J, Yonezawa Y, Maki H, Pai PF, Dent EV, Kellerman TE, Wilson DA, Reed SK. Assessment of repeatability of a wireless, inertial sensor-based lameness evaluation system for horses.. Am. J. Vet. Res. 2011;72:1156–1163.
    pubmed: 21879972
  18. Keegan KG, MacAllister CG, Wilson DA, Gedon CA, Kramer J, Yonezawa Y, Maki H, Frank Pai P. Comparison of an inertial sensor system with a stationary force plate for evaluation of horses with bilateral forelimb lameness.. Am. J. Vet. Res. 2012;73:368–374.
    pubmed: 22369528
  19. Keegan KG, Yonezawa Y, Pai PF, Wilson DA. Accelerometer-based system for the detection of lameness in horses.. Biomed. Sci. Instrum. 2002;38:107–112.
    pubmed: 12085585
  20. Keegan KG, Yonezawa Y, Pai PF, Wilson DA, Kramer J. Evaluation of a sensor-based system of motion analysis for detection and quantification of forelimb and hind limb lameness in horses.. Am. J. Vet. Res. 2004;65:665–670.
    pubmed: 15141889
  21. Kennel MB, Brown R, Abarbanel HDI. Determining embedding dimension for phase-space reconstruction using a geometrical construction.. Phys. Rev. A. 1992;45:3403–3411.
    pubmed: 9907388
  22. Kincaid C. Guidelines for selecting the covariance structure in mixed model analysis. Proceedings of the Thirtieth Annual SAS Users Group International Conference SAS Institute Inc Cary NC; 2005; pp. 130–198.
  23. Littell RC, Milliken GA, Stroup WW, Wolfinger RD, Oliver S. SAS for Mixed Models.. SAS publishing; 2006.
  24. López-Sanromán FJ, Cisneros GD, del Arco VM, Llorente SI, González SM. The use of low doses of acepromazine as an aid for lameness diagnosis in horses: an accelerometric evaluation.. Vet. Comp. Orthop. Traumatol. 2015;28:312–317.
    pubmed: 26219640
  25. Marghitu DB, Nalluri P. Nonlinear dynamic stability of normal and arthritic greyhounds.. Nonlinear Dynam. 1997;12:237–250.
  26. Marghitu DB, Swaim SF, Rumph PF, Cojocaru D, Gillette RL, Scardino MS. Dynamics analysis of ground contact pressure of English pointer dogs.. Nonlinear Dynam. 2003;33:253–265.
  27. Marroum PJ, Webb AI, Aeschbacher G, Curry SH. Pharmacokinetics and pharmacodynamics of acepromazine in horses.. Am. J. Vet. Res. 1994;55:1428–1433.
    pubmed: 7998701
  28. McCracken MJ, Kramer J, Keegan KG, Lopes M, Wilson DA, Reed SK, LaCarrubba A, Rasch M. Comparison of an inertial sensor system of lameness quantification with subjective lameness evaluation.. Equine Vet. J. 2012;44:652–656.
    pubmed: 22563674
  29. Moorman VJ, Frisbie DD, Kawcak CE, McIlwraith CW. The effect of horse velocity on the output of an inertial sensor system.. J. Equine Vet. Sci. 2017;58:34–39.
  30. Negahban H, Sanjari MA, Karimi M, Parnianpour M. Complexity and variability of the center of pressure time series during quiet standing in patients with knee osteoarthritis.. Clin. Biomech. 2016;32:280–285.
    pubmed: 26588884
  31. Nessler JA, De Leone CJ, Gilliland S. Nonlinear time series analysis of knee and ankle kinematics during side by side treadmill walking.. Chaos Interdiscipl. J. Nonlinear Sci. 2009;19 26104.
    pubmed: 19566264
  32. Packard NH, Crutchfield JP, Farmer JD, Shaw RS. Geometry from a time series.. Phys. Rev. Lett. 1980;45:712–716.
  33. Peham C, Scheidl M, Licka T. A method of signal processing in motion analysis of the trotting horse.. J. Biomech. 1996;29:1111–1114.
    pubmed: 8817379
  34. Pfau T, Boultbee H, Davis H, Walker A, Rhodin M. Agreement between two inertial sensor gait analysis systems for lameness examinations in horses.. Equine Vet. Educ. 2016;28:203–208.
  35. Pilsworth R, Dyson S. Where does it hurt? Problems with interpretation of regional and intra-synovial diagnostic analgesia.. Equine Vet. Educ. 2015;27:595–603.
  36. Reynard F, Terrier P. Local dynamic stability of treadmill walking: intrasession and week-to-week repeatability.. J. Biomech. 2014;47:74–80.
    pubmed: 24200341
  37. Rhodin M, Roepstorff L, French A, Keegan KG, Pfau T, Egenvall A. Head and pelvic movement asymmetry during lungeing in horses with symmetrical movement on the straight.. Equine Vet. J. 2016;48:315–320.
    pmc: PMC5032979pubmed: 25808700
  38. Robert C, Valette JP, Pourcelot P, Audigie F, Denoix JM. Effects of trotting speed on muscle activity and kinematics in saddlehorses.. Equine Vet. J. Suppl. 2002:295–301.
    pubmed: 12405704
  39. Rosenstein MT, Collins JJ, De Luca CJ. A practical method for calculating largest Lyapunov exponents from small data sets.. Phys. Nonlinear Phenom. 1993;65:117–134.
  40. Sepulveda Caviedes MF, Forbes BS, Pfau T. Repeatability of gait analysis measurements in Thoroughbreds in training.. Equine Vet. J. 2018;50:513–518.
    pubmed: 29284186
  41. Sornsanam S, Sukawat D. Attractor of a shallow water equations model.. Thai J. Math. 2012;5:299–307.
  42. Strogatz SH. Nonlinear Dynamics and Chaos: with Applications to Physics, Biology, Chemistry, and Engineering.. CRC press; 2018.
  43. Taintor J, DeGraves F, Schumacher J. Effect of tranquilization or sedation on the gait of lame horses.. J. Equine Vet. Sci. 2016;43:97–100.
  44. Tarnita D, Marghitu DB. Analysis of a hand arm system.. Robot. Comput. Integrated Manuf. 2013;29:493–501.
  45. Tian W, Cong Q, Menon C. Investigation on walking and pacing stability of German Shepherd dog for different locomotion speeds.. J. Bionic Eng. 2011;8:18–24.
  46. USDA. National Economic Cost of Equine Lameness, Colic, and Equine Protozoal Myeloencephalitis in the United States.. Inf. Sheet. 2001.
  47. Williams G. Chaos Theory Tamed.. CRC Press; 1997.
  48. Wolf A, Swift JB, Swinney HL, Vastano JA. Determining Lyapunov exponents from a time series.. Phys. Nonlinear Phenom. 1985;16:285–317.
  49. Yang C, Wu Q. On stabilization of bipedal robots during disturbed standing using the concept of Lyapunov exponents. 2006 American Control Conference 2006; p. 6.
Subscribe to our newsletter
Join 99,344 horse owners like you who receive our email updates on horse health and nutrition.