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Home / Equine Research Bank / Equine Vet J / Research trends in equine movement analysis, future opportun...
Equine veterinary journal2019; 51(6); 813-824; doi: 10.1111/evj.13076

Research trends in equine movement analysis, future opportunities and potential barriers in the digital age: A scoping review from 1978 to 2018.

Abstract: Since Muybridge's 'horse in motion', researchers in the equine movement analysis field continue to improve objective analysis and performance monitoring while ensuring representative data capture. However, subjective evaluation remains the primary method of equine gait analysis in the applied setting, despite evidence highlighting the unreliability of this approach. Objective: To map research trends, limitations and opportunities across the diverse equine gait analysis literature. Methods: Joanna Briggs Institute and Cochrane systematic scoping review. Methods: Search terms were chosen based on the 'PICO' framework and included keywords such as: Equine, Gait, Kinematics and Analysis. Studies were excluded based on predetermined criteria by two independent researchers. Data were extracted from 510 articles from 1978 to 2018. Results: Insights derived from movement analysis appear to be driven by tool availability. Observational research (42.9%) was the most popular study design. Use of wearable technology as a primary research tool is established within the field, accounting for 13.5% of studies. Analysis of limitations identified 17.8% of studies citing challenges to the transferability of research results. Restricted sample size appears to be an underlying contributor to many of the limitations identified. In terms of research opportunities, advances in intervention studies were called for (10.4% of studies) in the following three areas; clinical, rehabilitative exercise and performance/training. Conclusions: This review was confined to research in the English language. Conclusions: Standardised research reporting may alleviate sample size issues by facilitating data pooling, database creation and meta-analyses. Large holistic data collections and application frameworks based on wearable technologies are not reflected in the current equine gait analysis literature and thus represent an interesting opportunity for this field. Progress and lessons learned from the human field of movement analysis can be useful in supporting this potential development.
© 2019 EVJ Ltd.
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Publication Date: 2019-02-03 PubMed ID: 30659639DOI: 10.1111/evj.13076Google Scholar: Lookup
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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 article is a comprehensive exploration of research trends in equine movement analysis. It emphasizes the need for more objective approaches to this type of analysis, pointing out potential opportunities and barriers to progress within the field in the digital age.

Research Methods

  • The authors used the Joanna Briggs Institute and Cochrane systematic scoping review to map research trends in equine gait analysis literature.
  • They selected search terms based on the ‘PICO’ framework and included keywords such as Equine, Gait, Kinematics, and Analysis.
  • The researchers excluded studies based on predetermined criteria, and the remaining data was extracted from 510 articles spanning from 1978 to 2018.

Findings

  • The insights derived from the analysis seem to be largely driven by the availability of tools.
  • They found that observational research was the most popular study design, followed by the use of wearable technology as the primary research tool, which featured in 13.5% of the studies.
  • The analysis of the limitations identified that 17.8% of studies citing challenges to the transferability of research results. The most common underlying contributor to these limitations was restricted sample size.
  • The review also identified future research opportunities, particularly in clinical and rehabilitative exercise studies, and performance/training studies.

Conclusion

  • Despite the research being limited to English language studies, the authors conclude that standardizing research reporting could alleviate sample size issues by enabling the pooling of data, creation of databases, and conducting meta-analyses.
  • Moreover, they point out that the current equine gait analysis literature does not reflect large holistic data collections and application frameworks based on wearable technologies, which represent interesting potential areas of development for the field.
  • The authors suggest that progress and lessons learned from the human field of movement analysis could be useful in supporting these potential developments in equine gait analysis.

Cite This Article

APA
Egan S, Brama P, McGrath D. (2019). Research trends in equine movement analysis, future opportunities and potential barriers in the digital age: A scoping review from 1978 to 2018. Equine Vet J, 51(6), 813-824. https://doi.org/10.1111/evj.13076

Publication

Equine veterinary journal
ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 51
Issue: 6
Pages: 813-824

Researcher Affiliations

Egan, S
  • Institute for Sport and Health, School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland.
Brama, P
  • Section Veterinary Clinical Sciences, School of Veterinary Medicine, University College Dublin, Dublin, Ireland.
McGrath, D
  • Institute for Sport and Health, School of Public Health, Physiotherapy and Sport Science, University College Dublin, Dublin, Ireland.

MeSH Terms

  • Animals
  • Biomechanical Phenomena
  • Gait / physiology
  • Horses / physiology
  • Motor Activity / physiology
  • Research / trends

Grant Funding

  • Institute for Sport and Health
  • University College Dublin, Ireland
  • Irish Research Council Postgraduate Government of Ireland Programme

References

This article includes 80 references
  1. Muybridge E. Animals in Motion. .
  2. van Weeren R. Equine biomechanics: from an adjunct of art to a science in its own right. Equine Vet. J. 44, 506-508.
  3. Schmidt M, Rheinländer CC, Wille S, Wehn N, Jaitner T. IMU-Based Determination of Fatigue During Long Sprint. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct 2016, pp 899-903.
  4. Cummins C, Orr R, O'Connor H, West C. Global positioning systems (GPS) and microtechnology sensors in team sports: a systematic review. Sports Med. 43, 1025-1042.
  5. Moe-Nilssen R, Helbostad JL. Interstride trunk acceleration variability but not step width variability can differentiate between fit and frail older adults. Gait Posture 21, 164-170.
  6. Bierbaum S, Peper A, Karamanidis K, Arampatzis A. Adaptational responses in dynamic stability during disturbed walking in the elderly. J. Biomech. 43, 2362-2368.
  7. Lamoth CJ, van Deudekom FJ, van Campen JP, Appels BA, de Vries OJ, Pijnappels M. Gait stability and variability measures show effects of impaired cognition and dual tasking in frail people. J. Neuroeng. Rehabil. 8, 2.
  8. Cunniffe B, Proctor W, Baker JS, Davies B. An evaluation of the physiological demands of elite rugby union using Global Positioning System tracking software. J. Strength Cond. Res. 23, 1195-1203.
  9. Cahill N, Lamb K, Worsfold P, Headey R, Murray S. The movement characteristics of English Premiership rugby union players. J. Sports Sci. 31, 229-237.
  10. Hamill J, Knutzen KM. Biomechanical Basis of Human Movement. .
  11. Armstrong R, Hall BJ, Doyle J, Waters E. Cochrane update. ‘Scoping the scope’ of a cochrane review. J. Public Health (Oxf) 33, 147-150.
  12. Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement. Sci. 5, 69.
  13. Barnett-Page E, Thomas J. Methods for the synthesis of qualitative research: a critical review. BMC Med. Res. Methodol. 9, 59.
  14. Moher D, Liberati A. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann. Intern. Med. 151, 264-269.
  15. Peters MD, Godfrey CM, Khalil H, McInerney P, Parker D, Soares CB. Guidance for conducting systematic scoping reviews. Int. J. Evid. Based Healthc. 13, 141-146.
  16. Peters MDJ, Godfrey C, McInerney P, Baldini Soares C, Khalil H, Parker D. Joanna Briggs Institute Reviewer's Manual. .
  17. Sampson M, McGowan J, Cogo E, Grimshaw J, Moher D, Lefebvre C. An evidence-based practice guideline for the peer review of electronic search strategies. J. Clin. Epidemiol. 62, 944-952.
  18. Harris JD, Quatman CE, Manring MM, Siston RA, Flanigan DC. How to write a systematic review. Am. J. Sport. Med. 42, 2761-2768.
  19. Buchner HH, Savelberg HH, Schamhardt HC, Merkens HW, Barneveld A. Kinematics of treadmill versus overground locomotion in horses. Vet. Q. 16, Suppl. 2, S87-S90.
  20. Barrey E. Methods, applications and limitations of Gait analysis in horses. Vet. J. 157, 7-22.
  21. Crevier-Denoix N, Ravary-Plumioen B, Vergari C, Camus M, Holden-Douilly L, Falala S, Jerbi H, Desquilbet L, Chateau H, Denoix JM, Pourcelot P. Comparison of superficial digital flexor tendon loading on asphalt and sand in horses at the walk and trot. Vet. J. 198, Suppl. 1, e130-e136.
  22. Peinen K, Wiestner T, Bogisch S, Roepstorff L, Weeren PR, Weishaupt MA. Relationship between the forces acting on the horse's back and the movements of rider and horse while walking on a treadmill. Equine Vet. J. 41, 285-291.
  23. Weishaupt MA, Hogg HP, Auer JA, Wiestner T. Velocity-dependent changes of time, force and spatial parameters in Warmblood horses walking and trotting on a treadmill. Equine Vet. J. 42, Suppl. 38, 530-537.
  24. Barrey E, Galloux P, Valette JP, Auvinet B, Wolter R. Stride characteristics of overground versus treadmill locomotion in the saddle horse. Acta Anat. (Basel) 146, 90-94.
  25. Alvarez CBG, Rhodin M, Bystrom A, Back W, van Werren PR. Back kinematics of healthy trotting horses during treadmill versus over ground locomotion. Equine Vet. J. 41, 297-300.
  26. Oosterlinck M, Hardeman LC, van der Meij BR, Veraa S, van der Kolk JH, Wijnberg ID, Pille F, Back W. Pressure plate analysis of toe-heel and medio-lateral hoof balance at the walk and trot in sound sport horses. Vet. J. 198, Suppl. 1, e9-e13.
  27. Back W, Schamhardt HC. A comparison between the trot of pony and horse foals to characterise equine locomotion at young age. Equine Vet. J. 31, 240-244.
  28. Leach DH, Dagg AI. A review of research on equine locomotion and biomechanics. Equine Vet. J. 15, 93-102.
  29. Jeffcott LB, Rossdale PD, Freestone J, Frank CJ, Towers-Clark PF. An assessment of wastage in thoroughbred racing from conception to 4 years of age. Equine Vet. J. 14, 185-198.
  30. Rossdale PD, Hopes R, Digby NJW. Epidemiological-study of wastage among racehorses 1982 and 1983. Vet. Rec. 116, 66-69.
  31. Olivier A, Nurton JP, Guthrie AJ. An epizoological study of wastage in thoroughbred racehorses in Gauteng, South Africa. J. S. Afr. Vet. Ass. 68, 125-129.
  32. Wilsher S, Allen WR, Wood JL. Factors associated with failure of thoroughbred horses to train and race. Equine Vet. J. 38, 113-118.
  33. Schaer BLD, Ryan CT, Boston RC, Nunamaker DM. The horse-racetrack interface: a preliminary study on the effect of shoeing on impact trauma using a novel wireless data acquisition system. Equine Vet. J. 38, 664-670.
  34. Dyson PK, Jackson BF, Pfeiffer DU, Price JS. Days lost from training by two- and three-year-old Thoroughbred horses: a survey of seven UK training yards. Equine Vet. J. 40, 650-657.
  35. Stover SM. The epidemiology of Thoroughbred racehorse injuries. Clin. Tech. Equine Pract. 2, 312-322.
  36. Preedy DF, Colborne GR. A method to determine mechanical energy conservation and efficiency in equine gait: a preliminary study. Equine Vet. J. 33, Suppl. 33, 94-98.
  37. Campbell MLH. The role of veterinarians in equestrian sport: a comparative review of ethical issues surrounding human and equine sports medicine. Vet. J. 197, 535-540.
  38. 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. 44, 652-656.
  39. Van Weeren P, Pfau T, Rhodin M, Roepstorff L, Serra Bragança F, Weishaupt M. Do we have to redefine lameness in the era of quantitative gait analysis?. Equine Vet. J. 49, 567-569.
  40. Kaido M, Kilborne AH, Sizemore JL, Reisbig NA, Aarnes TK, Bertone AL. Effects of repetition within trials and frequency of trial sessions on quantitative parameters of vertical force peak in horses with naturally occurring lameness. Am. J. Vet. Res. 77, 756-765.
  41. 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. 42, 92-97.
  42. Weishaupt MA, Wiestner T, Hogg HP, Jordan P, Auer JA, Barrey E. Assessment of gait irregularities in the horse: eye vs. gait analysis. Equine Vet. J. 33, Suppl. 33, 135-140.
  43. Leach DH. Locomotion analysis technology for evaluation of lameness in horses. Equine Vet. J. 19, 97-99.
  44. Lord S, Galna B, Rochester L. Moving forward on gait measurement: toward a more refined approach. Mov. Disord. 28, 1534-1543.
  45. Matyas JR, Gutmann A, Randev J, Hurtig M, Bertram JEA. Intra-articular anaesthesia mitigates established pain in experimental osteoarthritis: a preliminary study of gait impulse redistribution as a biomarker of analgesia pharmacodynamics. Osteoarthritis Cartilage 21, 1365-1373.
  46. Braganca FM, Bosch S, Voskamp JP, Marin-Perianu M, Van der Zwaag BJ, Vernooij JCM, van Weeren PR, Back W. Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot. Equine Vet. J. 49, 545-551.
  47. Pfau T, Weller R. Comparison of a standalone consumer grade smartphone with a specialist inertial measurement unit for quantification of movement symmetry in the trotting horse. Equine Vet. J. 49, 124-129.
  48. Pfau T, Fiske-Jackson A, Rhodin M. Quantitative assessment of gait parameters in horses: useful for aiding clinical decision making?. Equine Vet. Educ. 28, 209-215.
  49. Pfau T, Parkes RS, Burden ER, Bell N, Fairhurst H, Witte TH. Movement asymmetry in working polo horses. Equine Vet. J. 48, 517-522.
  50. 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. 72, 1156-1163.
  51. Clayton HM, Schamhardt HC. Measurement Techniques for Gait Analysis. Equine locomotion, 2nd edn. 2001, pp 31-66.
  52. Schork NJ. Personalized medicine: time for one-person trials. Nature 520, 609-611.
  53. Brighton C, Olsen E, Pfau T. Is a standalone inertial measurement unit accurate and precise enough for quantification of movement symmetry in the horse?. Comput. Methods Biomech. Biomed. Engin. 18, 527-532.
  54. Ashley FH, Waterman-Pearson AE, Whay HR. Behavioural assessment of pain in horses and donkeys: application to clinical practice and future studies. Equine Vet. J. 37, 565-575.
  55. Bathe A, Judy C, Dyson S. Letter to the Editor: do we have to redefine lameness in the era of quantitative gait analysis?. Equine Vet. J. 50, 273-273.
  56. Pfau T, Noordwijk K, Sepulveda Caviedes M, Persson-Sjodin E, Barstow A, Forbes B, Rhodin M. Head, withers and pelvic movement asymmetry and their relative timing in trot in racing Thoroughbreds in training. Equine Vet. J. 50, 117-124.
  57. Bragança FMS, 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. 234, 11-23.
  58. Goodhill GJ. Is Neuroscience Facing Up to Statistical Power?. arXiv preprint arXiv:1701.01219 .
  59. Etz KE, Arroyo JA. Small sample research: considerations beyond statistical power. Prev. Sci. 16, 1033-1036.
  60. Bacchetti P, Deeks SG, McCune JM. Breaking free of sample size dogma to perform innovative translational research. Sci. Transl. Med. 3, 87 ps24-87 ps24.
  61. Christley R. Presenting and interpreting the results of statistical analyses: taking sample size into account. Equine Vet. J. 48, 272-274.
  62. Kacker R, Jones A. On use of Bayesian statistics to make the guide to the expression of uncertainty in measurement consistent. Metrologia 40, 235.
  63. Anderson JG. Social, ethical and legal barriers to e-health. Int. J. Med. Inform. 76, 480-483.
  64. Miller RH, Sim I. Physicians’ use of electronic medical records: barriers and solutions. Health Aff. 23, 116-126.
  65. Christodoulakis C, Asgarian A, Easterbrook S. Barriers to Adoption of Information Technology in Healthcare. Proc. 27th Ann. Inter. Conf. on Computer Science and Software Engineering 66-75.
  66. Hersh W. Health care information technology: progress and barriers. JAMA 292, 2273-2274.
  67. Heathfield H, Pitty D, Hanka R. Evaluating information technology in health care: barriers and challenges. BMJ 316, 1959-1961.
  68. Liebermann DG, Katz L, Hughes MD, Bartlett RM, McClements J, Franks IM. Advances in the application of information technology to sport performance. J. Sports Sci. 20, 755-769.
  69. Dyer B. The controversy of sports technology: a systematic review. Springerplus 4, 524.
  70. Okuda K, Abe N, Katayama Y, Senda M, Kuroda T, Inoue H. Effect of vision on postural sway in anterior cruciate ligament injured knees. J. Orthop. Sci. 10, 277-283.
  71. Kerr G, Morrison S, Silburn P. Coupling between limb tremor and postural sway in Parkinson's disease. Mov. Disord. 23, 386-394.
  72. Clayton HM, Buchholz R, Nauwelaerts S. Relationship between morphological and stabilographic variables in standing horses. Vet. J. 198, Suppl. 1, e65-e69.
  73. Clayton HM, Bialski DE, Lanovaz JL, Mullineaux DR. Assessment of the reliability of a technique to measure postural sway in horses. Am. J. Vet. Res. 64, 1354-1359.
  74. Bialski D, Lanovaz JL. Effect of detomidine on postural sway in horses. Equine Comp. Exerc. Physiol. 1, 45-50.
  75. Pentland A, Reid TG, Heidbeck T. Big data and Health. Revolutionizing Medicine and Public Health, Report of the Big Data and Health Working Group. .
  76. Andreu-Perez J, Poon CC, Merrifield RD, Wong ST, Yang GZ. Big data for health. IEEE J. Biomed. Health Inform. 19, 1193-1208.
  77. Swan M. Sensor mania! the internet of things, wearable computing, objective metrics, and the quantified self 2.0. J. Sens. Actuator Netw. 1, 217-253.
  78. Klonoff DC. Continuous glucose monitoring: roadmap for 21st century diabetes therapy. Diabetes Care 28, 1231-1239.
  79. Stergiou N, Harbourne R, Cavanaugh J. Optimal movement variability: a new theoretical perspective for neurologic physical therapy. J. Neurol. Phys. Ther. 30, 120-129.
  80. Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J. Royal Soc. Med. 104, 510-520.

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This article has been cited 10 times.
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  2. Briggs EV, Mazzà C. Automatic methods of hoof-on and -off detection in horses using wearable inertial sensors during walk and trot on asphalt, sand and grass.. PLoS One 2021;16(7):e0254813.
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  3. Marunova E, Dod L, Witte S, Pfau T. Smartphone-Based Pelvic Movement Asymmetry Measures for Clinical Decision Making in Equine Lameness Assessment.. Animals (Basel) 2021 Jun 3;11(6).
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  5. Dugué M, Dumont Saint Priest B, Crichan H, Danvy S, Ricard A. Genomic Correlations Between the Gaits of Young Horses Measured by Accelerometry and Functional Longevity in Jumping Competition.. Front Genet 2021;12:619947.
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  6. Ricard A, Dumont Saint Priest B, Chassier M, Sabbagh M, Danvy S. Genetic consistency between gait analysis by accelerometry and evaluation scores at breeding shows for the selection of jumping competition horses.. PLoS One 2020;15(12):e0244064.
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  7. Serra Bragança FM, Broomé S, Rhodin M, Björnsdóttir S, Gunnarsson V, Voskamp JP, Persson-Sjodin E, Back W, Lindgren G, Novoa-Bravo M, Gmel AI, Roepstorff C, van der Zwaag BJ, Van Weeren PR, Hernlund E. Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.. Sci Rep 2020 Oct 20;10(1):17785.
    doi: 10.1038/s41598-020-73215-9pubmed: 33082367google scholar: lookup
  8. Tijssen M, Hernlund E, Rhodin M, Bosch S, Voskamp JP, Nielen M, Serra Braganςa FM. Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors.. PLoS One 2020;15(6):e0233266.
    doi: 10.1371/journal.pone.0233266pubmed: 32492034google scholar: lookup
  9. Egan S, Brama P, McGrath D. Irish Equine Industry Stakeholder Perspectives of Objective Technology for Biomechanical Analyses in the Field.. Animals (Basel) 2019 Aug 8;9(8).
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  10. Curtis L, Burford JH, England GCW, Freeman SL. Risk factors for acute abdominal pain (colic) in the adult horse: A scoping review of risk factors, and a systematic review of the effect of management-related changes.. PLoS One 2019;14(7):e0219307.
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