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Home / Equine Research Bank / Sensors (Basel) / EquiMoves: A Wireless Networked Inertial Measurement System ...
Sensors (Basel, Switzerland)2018; 18(3); doi: 10.3390/s18030850

EquiMoves: A Wireless Networked Inertial Measurement System for Objective Examination of Horse Gait.

Abstract: In this paper, we describe and validate the EquiMoves system, which aims to support equine veterinarians in assessing lameness and gait performance in horses. The system works by capturing horse motion from up to eight synchronized wireless inertial measurement units. It can be used in various equine gait modes, and analyzes both upper-body and limb movements. The validation against an optical motion capture system is based on a Bland-Altman analysis that illustrates the agreement between the two systems. The sagittal kinematic results (protraction, retraction, and sagittal range of motion) show limits of agreement of ± 2.3 degrees and an absolute bias of 0.3 degrees in the worst case. The coronal kinematic results (adduction, abduction, and coronal range of motion) show limits of agreement of - 8.8 and 8.1 degrees, and an absolute bias of 0.4 degrees in the worst case. The worse coronal kinematic results are most likely caused by the optical system setup (depth perception difficulty and suboptimal marker placement). The upper-body symmetry results show no significant bias in the agreement between the two systems; in most cases, the agreement is within ±5 mm. On a trial-level basis, the limits of agreement for withers and sacrum are within ±2 mm, meaning that the system can properly quantify motion asymmetry. Overall, the bias for all symmetry-related results is less than 1 mm, which is important for reproducibility and further comparison to other systems.
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Publication Date: 2018-03-13 PubMed ID: 29534022PubMed Central: PMC5877382DOI: 10.3390/s18030850Google 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 research article presents and verifies the EquiMoves system, designed for horse veterinarians to evaluate lameness and gait in horses by recording equine motion using synchronized wireless units.

Overview of the EquiMoves System

  • EquiMoves is a system developed to assist equine veterinarians in the objective evaluation of horse gait and identifying any lameness issues.
  • The system uses up to eight synchronized wireless inertial measurement units to capture the horse’s movements. These units can measure various gait modes, analyze both upper-body, and limb movements.

The Validation Process

  • The research validates the effectiveness of this system by comparing it to an optical motion capture system and uses a Bland-Altman analysis to illustrate the agreement between the two systems.
  • It examines the results for both sagittal and coronal kinematic movements, ranging from protraction and retraction to abduction and adduction.
  • The sagittal kinematic results show an absolute bias of 0.3 degrees at worst case scenario, and the coronal kinematic results show an absolute bias of 0.4 degrees.
  • The poorer coronal kinematic results are attributed to the setup of the optical system, such as depth perception difficulty and suboptimal marker placement.

Upper-Body Symmetry Results

  • The study also investigates the measurement’s upper-body symmetry, and finds that the EquiMoves system shows no significant bias in this area as compared to the optical system.
  • The limits of agreement on a trial-level basis for the withers and sacrum are within ±2 mm, indicating that the system can effectively measure motion asymmetry.
  • The overall bias relating to symmetry was less than 1 mm, which underscores the system’s accuracy, reproducibility, and ability to compare well with other systems.

Cite This Article

APA
Bosch S, Serra Bragança F, Marin-Perianu M, Marin-Perianu R, van der Zwaag BJ, Voskamp J, Back W, van Weeren R, Havinga P. (2018). EquiMoves: A Wireless Networked Inertial Measurement System for Objective Examination of Horse Gait. Sensors (Basel), 18(3). https://doi.org/10.3390/s18030850

Publication

Sensors (Basel, Switzerland)
ISSN: 1424-8220
NlmUniqueID: 101204366
Country: Switzerland
Language: English
Volume: 18
Issue: 3

Researcher Affiliations

Bosch, Stephan
  • Inertia Technology B.V., 7521 AG Enschede, The Netherlands. stephan@inertia-technology.com.
  • Department of Computer Science, Pervasive Systems Group, University of Twente, 7522 NB Enschede, The Netherlands. stephan@inertia-technology.com.
Serra Bragança, Filipe
  • Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands. F.M.SerraBraganca@uu.nl.
Marin-Perianu, Mihai
  • Inertia Technology B.V., 7521 AG Enschede, The Netherlands. mihai@inertia-technology.com.
Marin-Perianu, Raluca
  • Inertia Technology B.V., 7521 AG Enschede, The Netherlands. raluca@inertia-technology.com.
van der Zwaag, Berend Jan
  • Inertia Technology B.V., 7521 AG Enschede, The Netherlands. berendjan@inertia-technology.com.
Voskamp, John
  • Rosmark Consultancy, 6733 AA Wekerom, The Netherlands. info@rosmark.nl.
Back, Willem
  • Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands. W.Back@uu.nl.
  • Department of Surgery and Anaesthesia of Domestic Animals, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium. W.Back@uu.nl.
van Weeren, René
  • Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, 3584 CM Utrecht, The Netherlands. r.vanweeren@uu.nl.
Havinga, Paul
  • Department of Computer Science, Pervasive Systems Group, University of Twente, 7522 NB Enschede, The Netherlands. p.j.m.havinga@utwente.nl.

MeSH Terms

  • Animals
  • Biomechanical Phenomena
  • Gait
  • Horses
  • Lameness, Animal
  • Movement
  • Range of Motion, Articular
  • Reproducibility of Results
  • Wireless Technology

Conflict of Interest Statement

Mihai Marin-Perianu, Raluca Marin-Perianu and Paul Havinga founded Inertia-Technology B.V. (Enschede, The Netherlands), which sells the inertial sensor system (ProMove-mini) that is used as the basis of the EquiMoves system, which is evaluated in this study. Stephan Bosch and Berend-Jan van der Zwaag are employees of Inertia-Technology B.V.

References

This article includes 94 references
  1. Van Weeren P.R., Pfau T., Rhodin M., Roepstorff L., Serra Bragança F., Weishaupt M.A.. Do we have to redefine lameness in the era of quantitative gait analysis?. Equine Vet. J. 2017;49:567–569.
    doi: 10.1111/evj.12715pubmed: 28804943google scholar: lookup
  2. United States. National Animal Health Monitoring System (U.S.) National Economic Cost of Equine Lameness, Colic, and Equine Protozoal Myeloencephalitis (EPM) in the United States. U.S. Department of Agriculture, APHIS; Fort Collins, CO, USA: 2001.
  3. Loomans J.B.A., Stolk P.W.T., van Weeren P.R., Vaarkamp H., Barneveld A.. A survey of the workload and clinical skills in current equine practices in The Netherlands. Equine Vet. Educ. 2007;19:162–168.
    doi: 10.2746/095777307X186875google scholar: lookup
  4. Parkes R.S.V., Weller R., Groth A.M., May S., Pfau T.. Evidence of the development of ‘domain-restricted’ expertise in the recognition of asymmetric motion characteristics of hindlimb lameness in the horse. Equine Vet. J. 2009;41:112–117.
    doi: 10.2746/042516408X343000pubmed: 19418737google scholar: lookup
  5. Arkell M., Archer R.M., Guitian F.J., May S.A.. Evidence of bias affecting the interpretation of the results of local anaesthetic nerve blocks when assessing lameness in horses. Vet. Rec. 2006;159:346–348.
    doi: 10.1136/vr.159.11.346pubmed: 16963714google scholar: lookup
  6. Keegan K.G., Dent E.V., Wilson D.A., Janicek J., Kramer J., Lacarrubba A., Walsh D.M., Cassells M.W., Esther T.M., Schiltz P.. Repeatability of subjective evaluation of lameness in horses. Equine Vet. J. 2010;42:92–97.
    doi: 10.2746/042516409X479568pubmed: 20156242google scholar: lookup
  7. Thomsen M.H., Persson A.B., Jensen A.T., Sørensen H., Andersen P.H.. Agreement between accelerometric symmetry scores and clinical lameness scores during experimentally induced transient distension of the metacarpophalangeal joint in horses. Equine Vet. J. 2010;42:510–515.
    doi: 10.1111/j.2042-3306.2010.00287.xpubmed: 21059053google scholar: lookup
  8. McCracken M.J., Kramer J., Keegan K.G., Lopes M., Wilson D.A., Reed S.K., LaCarrubba A., Rasch M.. Comparison of an inertial sensor system of lameness quantification with subjective lameness evaluation. Equine Vet. J. 2012;44:652–656.
    doi: 10.1111/j.2042-3306.2012.00571.xpubmed: 22563674google scholar: lookup
  9. Hammarberg M., Egenvall A., Pfau T., Rhodin M.. Rater agreement of visual lameness assessment in horses during lungeing. Equine Vet. J. 2016;48:78–82.
    doi: 10.1111/evj.12385pmc: PMC4964936pubmed: 25399722google scholar: lookup
  10. Serra Bragança F.M., Rhodin M., van Weeren P.R.. 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;234:11–23.
    doi: 10.1016/j.tvjl.2018.01.006pubmed: 29680381google scholar: lookup
  11. Morris E.A., Seeherman H.J.. Redistribution of ground reaction forces in experimentally induced equine carpal lameness. Equine Exerc. Physiol. 1987;2:553–563.
  12. Ishihara A., Bertone A.L., Rajala-Schultz P.J.. Association between subjective lameness grade and kinetic gait parameters in horses with experimentally induced forelimb lameness. Am. J. Vet. Res. 2005;66:1805–1815.
    doi: 10.2460/ajvr.2005.66.1805pubmed: 16273915google scholar: lookup
  13. Kai M., Aoki O., Hiraga A., Oki H., Tokuriki M.. Use of an instrument sandwiched between the hoof and shoe to measure vertical ground reaction forces and three-dimensional acceleration at the walk, trot, and canter in horses. Am. J. Vet. Res. 2000;61:979–985.
    doi: 10.2460/ajvr.2000.61.979pubmed: 10951994google scholar: lookup
  14. Munoz-Nates F., Chateau H., Hamme A.V., Camus M., Pauchard M., Ravary-Plumioen B., Denoix J.M., Pourcelot P., Crevier-Denoix N.. Accelerometric and dynamometric measurements of the impact shock of the equine forelimb and hindlimb at high speed trot on six different tracks—Preliminary study in one horse. Comput. Methods Biomech. Biomed. Eng. 2015;18:2012–2013.
    doi: 10.1080/10255842.2015.1069601pubmed: 26247449google scholar: lookup
  15. Weishaupt M.A., Hogg H.P., Wiestner T., Denoth J., Stüssi E., Auer J.A.. Instrumented treadmill for measuring vertical ground reaction forces in horses. Am. J. Vet. Res. 2002;63:520–527.
    doi: 10.2460/ajvr.2002.63.520pubmed: 11939313google scholar: lookup
  16. Guerra-filho G.B.. Optical motion capture: Theory and implementation. J. Theor. Appl. Inform. (RITA) 2005;12:61–89.
  17. Eichelberger P., Ferraro M., Minder U., Denton T., Blasimann A., Krause F., Baur H.. Analysis of accuracy in optical motion capture—A protocol for laboratory setup evaluation. J. Biomech. 2016;49:2085–2088.
    doi: 10.1016/j.jbiomech.2016.05.007pubmed: 27230474google scholar: lookup
  18. Alvarez C.B.G., Bobbert M.F., Lamers L., Johnston C., Back W., van Weeren P.R.. The effect of induced hindlimb lameness on thoracolumbar kinematics during treadmill locomotion. Equine Vet. J. 2008;40:147–152.
    pubmed: 18089465
  19. Persson Sjödin E., Serra Braganca F., Pfau T., Egenvall A., Weishaupt M.A., Rhodin M.. Movement Symmetry of the Withers Can Be Used to Discriminate Primary Forelimb Lameness From Compensatory Forelimb Asymmetry in Horses with Induced Lameness. Equine Vet. J. 2016;48:32–33.
    pmc: PMC6175082pubmed: 29658147
  20. Windolf M., Götzen N., Morlock M.. Systematic accuracy and precision analysis of video motion capturing systems—Exemplified on the Vicon-460 system. J. Biomech. 2008;41:2776–2780.
    doi: 10.1016/j.jbiomech.2008.06.024pubmed: 18672241google scholar: lookup
  21. Starke S.D., Willems E., May S.A., Pfau T.. Vertical head and trunk movement adaptations of sound horses trotting in a circle on a hard surface. Vet. J. 2012;193:73–80.
    doi: 10.1016/j.tvjl.2011.10.019pubmed: 22104508google scholar: lookup
  22. Starke S.D., May S.A., Pfau T.. Understanding hind limb lameness signs in horses using simple rigid body mechanics. J. Biomech. 2015;48:3323–3331.
    doi: 10.1016/j.jbiomech.2015.06.019pubmed: 26163753google scholar: lookup
  23. Bolink S.A.A.N., Naisas H., Senden R., Essers H., Heyligers I.C., Meijer K., Grimm B.. Validity of an inertial measurement unit to assess pelvic orientation angles during gait, sit–stand transfers and step-up transfers: Comparison with an optoelectronic motion capture system. Med. Eng. Phys. 2016;38:225–231.
    doi: 10.1016/j.medengphy.2015.11.009pubmed: 26711470google scholar: lookup
  24. Kong W., Sessa S., Cosentino S., Zecca M., Saito K., Wang C., Imtiaz U., Lin Z., Bartolomeo L., Ishii H.. Development of a real-time IMU-based motion capture system for gait rehabilitation. Proceedings of the 2013 IEEE International Conference on Robotics and Biomimetics (ROBIO); Shenzhen, China. 12–14 December 2013; pp. 2100–2105.
  25. Titterton D., Weston J.L.. Strapdown Inertial Navigation Technology. Volume 17 IET; Stevenage, Hertfordshire, UK: 2004.
  26. Pfau T., Robilliard J.J., Weller R., Jespers K., Eliashar E., Wilson A.M.. Assessment of mild hindlimb lameness during over ground locomotion using linear discriminant analysis of inertial sensor data. Equine Vet. J. 2007;39:407–413.
    doi: 10.2746/042516407X185719pubmed: 17910264google scholar: lookup
  27. Keegan K.G.. The Lameness Locator (wireless inertial sensors for detection of lameness in horses). Proceedings of the Congress of the European Society of Veterinary Orthopaedics and Traumatology; Bologna, Italy. 15–18 September 2010; pp. 215–217.
  28. Nankervis K., Hodgins D., Marlin D.. Comparison between a sensor (3D accelerometer) and ProReflex motion capture systems to measure stride frequency of horses on a treadmill. Comp. Exerc. Physiol. 2008;5:107–109.
    doi: 10.1017/S1478061508017027google scholar: lookup
  29. Lopes M.A.F., Dearo A.C.O., Lee A., Reed S.K., Kramer J., Pai P.F., Yonezawa Y., Maki H., Morgan T.L., Wilson D.A.. An attempt to detect lameness in galloping horses by use of body-mounted inertial sensors. Am. J. Vet. Res. 2016;77:1121–1131.
    doi: 10.2460/ajvr.77.10.1121pubmed: 27668584google scholar: lookup
  30. 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. Eng. 2015;18:527–532.
    doi: 10.1080/10255842.2013.819857pubmed: 23947386google scholar: lookup
  31. Pfau T., Fiske-Jackson A., Rhodin M.. Quantitative assessment of gait parameters in horses: Useful for aiding clinical decision making?. Equine Vet. Educ. 2016;28:209–215.
    doi: 10.1111/eve.12372google scholar: lookup
  32. Warner S.M., Koch T.O., Pfau T.. Inertial sensors for assessment of back movement in horses during locomotion over ground. Equine Vet. J. 2010;42:417–424.
    doi: 10.1111/j.2042-3306.2010.00200.xpubmed: 21059039google scholar: lookup
  33. Rhodin M., Roepstorff L., French A., Keegan K.G., 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.
    doi: 10.1111/evj.12446pmc: PMC5032979pubmed: 25808700google scholar: lookup
  34. Pfau T., Witte T.H., Wilson A.M.. A method for deriving displacement data during cyclical movement using an inertial sensor. J. Exp. Biol. 2005;208:2503–2514.
    doi: 10.1242/jeb.01658pubmed: 15961737google scholar: lookup
  35. Buchner H.H., Savelberg H.H., Schamhardt H.C., Merkens H.W., Barneveld A.. Kinematics of treadmill versus overground locomotion in horses. Vet. Q. 1994;16(Suppl. 2):87–90.
    doi: 10.1080/01652176.1994.9694509pubmed: 7801509google scholar: lookup
  36. Gómez Alvarez C.B., Rhodin M., Byström A., Back W., van Weeren P.R.. Back kinematics of healthy trotting horses during treadmill versus over ground locomotion. Equine Vet. J. 2009;41:297–300.
    doi: 10.2746/042516409X397370pubmed: 19469239google scholar: lookup
  37. Keegan K.G., Kramer J., Yonezawa Y., Maki H., Pai P.F., Dent E.V., Kellerman T.E., Wilson D.A., Reed S.K.. Assessment of repeatability of a wireless, inertial sensor-based lameness evaluation system for horses. Am. J. Vet. Res. 2011;72:1156–1163.
    doi: 10.2460/ajvr.72.9.1156pubmed: 21879972google scholar: lookup
  38. AAEP. Guide to Veterinary Services for Horse Shows. 7th ed. American Association of Equine Practitioners; Lexington, KY, USA: 1999.
  39. Calisi R.M., Bentley G.E.. Lab and field experiments: Are they the same animal?. Horm. Behav. 2009;56:1–10.
    doi: 10.1016/j.yhbeh.2009.02.010pubmed: 19281813google scholar: lookup
  40. Van den Noort J.C., Ferrari A., Cutti A.G., Becher J.G., Harlaar J.. Gait analysis in children with cerebral palsy via inertial and magnetic sensors. Med. Biol. Eng. Comput. 2013;51:377–386.
    doi: 10.1007/s11517-012-1006-5pubmed: 23224902google scholar: lookup
  41. El-Gohary M., McNames J.. Shoulder and Elbow Joint Angle Tracking with Inertial Sensors. IEEE Trans. Biomed. Eng. 2012;59:2635–2641.
    doi: 10.1109/TBME.2012.2208750pubmed: 22911538google scholar: lookup
  42. Muro-de-la Herran A., Garcia-Zapirain B., Mendez-Zorrilla A.. Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical Applications. Sensors 2014;14:3362–3394.
    doi: 10.3390/s140203362pmc: PMC3958266pubmed: 24556672google scholar: lookup
  43. Picerno P.. 25 years of lower limb joint kinematics by using inertial and magnetic sensors: A review of methodological approaches. Gait & Posture 2017;51:239–246.
    pubmed: 27833057
  44. Wang Q., Markopoulos P., Yu B., Chen W., Timmermans A.. Interactive wearable systems for upper body rehabilitation: A systematic review. J. NeuroEng. Rehabil. 2017;14:20.
    doi: 10.1186/s12984-017-0229-ypmc: PMC5346195pubmed: 28284228google scholar: lookup
  45. Iosa M., Picerno P., Paolucci S., Morone G.. Wearable inertial sensors for human movement analysis. Expert Rev. Med. Devices. 2016;13:641–659.
    doi: 10.1080/17434440.2016.1198694pubmed: 27309490google scholar: lookup
  46. Chambers R., Gabbett T.J., Cole M.H., Beard A.. The Use of Wearable Microsensors to Quantify Sport-Specific Movements. Sports Med. 2015;45:1065–1081.
    doi: 10.1007/s40279-015-0332-9pubmed: 25834998google scholar: lookup
  47. Ahmadi A., Destelle F., Monaghan D., O’Connor N.E., Richter C., Moran K.. A framework for comprehensive analysis of a swing in sports using low-cost inertial sensors. Proceedings of the 2014 IEEE SENSORS; Valencia, Spain. 2–5 November 2014; pp. 2211–2214.
  48. Neville J.G., Rowlands D.D., Lee J.B., James D.A.. A Model for Comparing Over-Ground Running Speed and Accelerometer Derived Step Rate in Elite Level Athletes. IEEE Sens. J. 2016;16:185–191.
    doi: 10.1109/JSEN.2015.2477497google scholar: lookup
  49. King K., Hough J., McGinnis R., Perkins N.C.. A new technology for resolving the dynamics of a swinging bat. Sports Eng. 2012;15:41–52.
    doi: 10.1007/s12283-012-0084-9google scholar: lookup
  50. Philpott L.K., Weaver S., Gordon D., Conway P.P., West A.A.. Assessing wireless inertia measurement units for monitoring athletics sprint performance. Proceedings of the 2014 IEEE SENSORS; Valencia, Spain. 2–5 November 2014; pp. 2199–2202.
  51. Stamm A., Thiel D.V.. Investigating Forward Velocity and Symmetry in Freestyle Swimming Using Inertial Sensors. Procedia Eng. 2015;112:522–527.
    doi: 10.1016/j.proeng.2015.07.236google scholar: lookup
  52. Thompson R., Kyriazakis I., Holden A., Olivier P., Plötz T.. Dancing with Horses: Automated Quality Feedback for Dressage Riders. Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp ’15); Osaka, Japan. 7–11 September 2015; New York, NY, USA: ACM; 2015. pp. 325–336.
  53. Martin P., Cheze L., Pourcelot P., Desquilbet L., Duray L., Chateau H.. Effects of the rider on the kinematics of the equine spine under the saddle during the trot using inertial measurement units: Methodological study and preliminary results. Vet. J. 2017;221:6–10.
    doi: 10.1016/j.tvjl.2016.12.018pubmed: 28283082google scholar: lookup
  54. Knapkiewicz P., Kosek W., Jozwiak P., Dziuban J., Jaskowski J.. Animals Dedicated, MEMS Sensors Based Mechatronics Movement Assessment System. Procedia Eng. 2014;87:576–579.
    doi: 10.1016/j.proeng.2014.11.554google scholar: lookup
  55. Keegan K.G., Yonezawa Y., Pai P.F., Wilson D.A.. Accelerometer-based system for the detection of lameness in horses. Biomed. Sci. Instrum. 2002;38:107–112.
    pubmed: 12085585
  56. Bailey G.P., Harle R.. Assessment of Foot Kinematics During Steady State Running Using a Foot-mounted IMU. Procedia Eng. 2014;72:32–37.
    doi: 10.1016/j.proeng.2014.06.009google scholar: lookup
  57. Van der Kruk E., Schwab A.L., van der Helm F.C.T., Veeger H.E.J.. Getting the Angles Straight in Speed Skating: A Validation Study on an IMU Filter Design to Measure the Lean Angle of the Skate on the Straights. Procedia Eng. 2016;147:590–595.
    doi: 10.1016/j.proeng.2016.06.245google scholar: lookup
  58. Yuan Q., Chen I.M., Caus A.. Human velocity tracking and localization using 3 IMU sensors. Proceedings of the 2013 6th IEEE Conference on Robotics, Automation and Mechatronics (RAM); Manila, Philippines. 12–15 November 2013; pp. 25–30.
  59. Wundersitz D., Gastin P., Robertson S., Davey P., Netto K.. Validation of a Trunk-mounted Accelerometer to Measure Peak Impacts during Team Sport Movements. Int. J. Sports Med. 2015;36:742–746.
    doi: 10.1055/s-0035-1547265pubmed: 25806591google scholar: lookup
  60. Bichler S., Ogris G., Kremser V., Schwab F., Knott S., Baca A.. Towards high-precision IMU/GPS-based stride-parameter determination in an outdoor runners’ scenario. Procedia Eng. 2012;34:592–597.
    doi: 10.1016/j.proeng.2012.04.101google scholar: lookup
  61. Keegan K.G., Wilson D.A., Kramer J., Reed S.K., Yonezawa Y., Maki H., Pai P.F., Lopes M.A.F.. Comparison of a body-mounted inertial sensor system–based method with subjective evaluation for detection of lameness in horses. Am. J. Vet. Res. 2012;74:17–24.
    doi: 10.2460/ajvr.74.1.17pubmed: 23270341google scholar: lookup
  62. Donnell J.R., Frisbie D.D., King M.R., Goodrich L.R., Haussler K.K.. Comparison of subjective lameness evaluation, force platforms and an inertial-sensor system to identify mild lameness in an equine osteoarthritis model. Vet. J. 2015;206:136–142.
    doi: 10.1016/j.tvjl.2015.08.004pubmed: 26361749google scholar: lookup
  63. Rungsri P., Sfaecker W., Leelamankong P., Estrada R., Rettig M., Klaus C., Lischer C.. Agreement between a body-mounted inertial sensors system and subjective observational analysis when evaluating lameness degree and diagnostic analgesia response in horses with forelimb lameness. Pferdeheilkunde 2014;30:644–650.
    doi: 10.21836/PEM20140603google scholar: lookup
  64. Keegan K.G., MacAllister C.G., Wilson D.A., Gedon C.A., Kramer J., Yonezawa Y., Maki H., Pai P.F.. 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.
    doi: 10.2460/ajvr.73.3.368pubmed: 22369528google scholar: lookup
  65. Bell R.P., Reed S.K., Schoonover M.J., Whitfield C.T., Yonezawa Y., Maki H., Pai P.F., Keegan K.G.. Associations of force plate and body-mounted inertial sensor measurements for identification of hind limb lameness in horses. Am. J. Vet. Res. 2016;77:337–345.
    doi: 10.2460/ajvr.77.4.337pubmed: 27027831google scholar: lookup
  66. 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. 2015;49:124–129.
    doi: 10.1111/evj.12529pubmed: 26518143google scholar: lookup
  67. 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.
    doi: 10.1111/eve.12400google scholar: lookup
  68. Olsen E., Pfau T., Ritz C.. Functional limits of agreement applied as a novel method comparison tool for accuracy and precision of inertial measurement unit derived displacement of the distal limb in horses. J. Biomech. 2013;46:2320–2325.
    doi: 10.1016/j.jbiomech.2013.06.004pubmed: 23891315google scholar: lookup
  69. Roepstorff L., Wiestner T., Weishaupt M.A., Egenvall E.. Comparison of microgyro-based measurements of equine metatarsal/metacarpal bone to a high speed video locomotion analysis system during treadmill locomotion. Vet. J. 2013;198(Suppl. 1):e157–e160.
    doi: 10.1016/j.tvjl.2013.09.052pubmed: 24360759google scholar: lookup
  70. Keegan K.G., Yonezawa Y., Pai P.F., Wilson D.A., 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.
    doi: 10.2460/ajvr.2004.65.665pubmed: 15141889google scholar: lookup
  71. Moorman V.J., Reiser R.F., II, McIlwraith C.W., Kawcak C.E.. Validation of an equine inertial measurement unit system in clinically normal horses during walking and trotting. Am. J. Vet. Res. 2012;73:1160–1170.
    doi: 10.2460/ajvr.73.8.1160pubmed: 22849676google scholar: lookup
  72. Equinosis LLC. The Equinosis with Lameness Locator. Equinosis LLC; Columbia, MO, USA: [(accessed on 6 March 2018)]. Available online: https://equinosis.com.
  73. GaitSmart. GaitSmart Pegasus—Sensor-Based Gait Analysis for Equines. GaitSmart; Codicote, Hitchin, Hertfordshire, UK: [(accessed on 6 March 2018)]. Available online: http://www.gaitsmart.com/gaitsmart-pegasus.
  74. EquiGait. EquiGait—Sensor Based Gait Analysis. EquiGait; Brickendon, Hertford, Hertfordshire, UK: [(accessed on 6 March 2018)]. Available online: http://www.equigait.co.uk.
  75. Back W., Clayton H.. Equine Locomotion. 2nd ed. W.B. Saunders, Elsevier Health; London, UK: 2013.
  76. Inertia Technology. ProMove MINI—Wireless Motion Capture Sensor from Inertia Technology. Inertia Technology; Enschede, The Netherlands: [(accessed on 6 March 2018)]. Available online: http://inertia-technology.com/product/motion-capture-promove-mini.
  77. Olsen E., Andersen P.H., Pfau T.. Accuracy and Precision of Equine Gait Event Detection during Walking with Limb and Trunk Mounted Inertial Sensors. Sensors 2012;12:8145–8156.
    doi: 10.3390/s120608145pmc: PMC3436021pubmed: 22969392google scholar: lookup
  78. Bragança F.M., Bosch S., Voskamp J.P., Marin-Perianu M., Van der Zwaag B.J., Vernooij J.C.M., van Weeren P.R., Back W.. Validation of distal limb mounted inertial measurement unit sensors for stride detection in Warmblood horses at walk and trot. Equine Vet. J. 2017;49:545–551.
    pmc: PMC5484301pubmed: 27862238
  79. Valenti R.G., Dryanovski I., Xiao J.. Keeping a Good Attitude: A Quaternion-Based Orientation Filter for IMUs and MARGs. Sensors 2015;15:19302–19330.
    doi: 10.3390/s150819302pmc: PMC4570372pubmed: 26258778google scholar: lookup
  80. Madgwick S.O.H., Harrison A.J.L., Vaidyanathan R.. Estimation of IMU and MARG orientation using a gradient descent algorithm. Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics; Zurich, Switzerland. 29 June–1 July 2011; pp. 1–7.
    pubmed: 22275550
  81. Peham C., Scheidl M., Licka T.. A method of signal processing in motion analysis of the trotting horse. J. Biomech. 1996;29:1111–1114.
    doi: 10.1016/0021-9290(95)00179-4pubmed: 8817379google scholar: lookup
  82. Keegan K.G., Pai P.F., Wilson D.A., Smith B.K.. Signal decomposition method of evaluating head movement to measure induced forelimb lameness in horses trotting on a treadmill. Equine Vet. J. 2001;33:446–451.
    doi: 10.2746/042516401776254781pubmed: 11558738google scholar: lookup
  83. Howard R., Conway R., Harrison A.J.. Estimation of force during vertical jumps using body fixed accelerometers. Proceedings of the 25th IET Irish Signals Systems Conference 2014 and 2014 China-Ireland International Conference on Information and Communications Technologies (ISSC 2014/CIICT 2014); Limerick, Ireland. 26–27 June 2014; pp. 102–107.
  84. Coutsias E.A., Seok C., Dill K.A.. Using quaternions to calculate RMSD. J. Comput. Chem. 2004;25:1849–1857.
    pubmed: 15376254
  85. Dobrowolski P.. Swing-twist decomposition in Clifford algebra. arXiv 2015. 1506.05481.
  86. Giavarina D.. Understanding Bland Altman analysis. Biochem. Med. 2015;25:141–151.
    doi: 10.11613/BM.2015.015pmc: PMC4470095pubmed: 26110027google scholar: lookup
  87. Barnhart H.X., Yow E., Crowley A.L., Daubert M.A., Rabineau D., Bigelow R., Pencina M., Douglas P.S.. Choice of agreement indices for assessing and improving measurement reproducibility in a core laboratory setting. Stat. Methods Med. Res. 2016;25:2939–2958.
    doi: 10.1177/0962280214534651pubmed: 24831133google scholar: lookup
  88. Bland J.M., Altman D.G.. Agreement Between Methods of Measurement with Multiple Observations Per Individual. J. Biopharm. Stat. 2007;17:571–582.
    doi: 10.1080/10543400701329422pubmed: 17613642google scholar: lookup
  89. Schamhardt H.C., van den Bogert A.J., Hartman W.. Measurement Techniques in Animal Locomotion Analysis. Cells Tissues Organs 1993;146:123–129.
    doi: 10.1159/000147433pubmed: 8470454google scholar: lookup
  90. Clayton H.M., Schamhardt H.C., Willemen M.A., Lanovaz J.L., Colborne G.R.. Kinematics and ground reaction forces in horses with superficial digital flexor tendinitis. Am. J. Vet. Res. 2000;61:191–196.
    doi: 10.2460/ajvr.2000.61.191pubmed: 10685692google scholar: lookup
  91. Buchner H.H.F., Savelberg H.H.C.M., Schamhardt H.C., Barneveld A.. Limb movement adaptations in horses with experimentally induced fore- or hindlimb lameness. Equine Vet. J. 1996;28:63–70.
    doi: 10.1111/j.2042-3306.1996.tb01591.xpubmed: 8565956google scholar: lookup
  92. Starke S.D., Witte T.H., May S.A., Pfau T.. Accuracy and precision of hind limb foot contact timings of horses determined using a pelvis-mounted inertial measurement unit. J. Biomech. 2012;45:1522–1528.
    doi: 10.1016/j.jbiomech.2012.03.014pubmed: 22483227google scholar: lookup
  93. Dyson S.. Recognition of lameness: Man versus machine. Vet. J. 2014;201:245–248.
    doi: 10.1016/j.tvjl.2014.05.018pubmed: 24923757google scholar: lookup
  94. Clayton H.M., Hobbs S.J.. The role of biomechanical analysis of horse and rider in equitation science. Appl. Anim. Behav. Sci. 2017;190:123–132.
    doi: 10.1016/j.applanim.2017.02.011google scholar: lookup

Citations

This article has been cited 49 times.
  1. Korac L, St George L, MacNicol J, McCrae P, Jung L, Golestani N, Karrow N, Cánovas A, Pearson W. Functional and biochemical inflammatory responses to low-dose intra-articular recombinant equine IL-1β: a pilot study. Front Vet Sci 2025;12:1746738.
    doi: 10.3389/fvets.2025.1746738pubmed: 41624292google scholar: lookup
  2. Key K, Berg K, Kirkegaard J, Andresen KR, Hansen SS. Evaluating the Accuracy of a Vision-Based Algorithm for Groundline Estimation in Trotting Horses Using Multiple Camera Angles. Vet Med Sci 2026 Jan;12(1):e70739.
    doi: 10.1002/vms3.70739pubmed: 41467589google 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. Zupan Šemrov M, Přibylová L, Gobbo E. Task-specific morphological and kinematic differences in Lipizzan horses. Front Vet Sci 2025;12:1569067.
    doi: 10.3389/fvets.2025.1569067pubmed: 40599329google scholar: lookup
  5. Schampheleer J, Eerdekens A, Joseph W, Martens L, Deruyck M. Detecting Equine Gaits Through Rider-Worn Accelerometers. Animals (Basel) 2025 Apr 8;15(8).
    doi: 10.3390/ani15081080pubmed: 40281916google scholar: lookup
  6. Siegers EW, Parmentier JIM, Sloet van Oldruitenborgh-Oosterbaan MM, Munsters CCBM, Serra Bragança FM. Gait kinematics at trot before and after repeated ridden exercise tests in young Friesian stallions during a fatiguing 10-week training program. Front Vet Sci 2025;12:1456424.
    doi: 10.3389/fvets.2025.1456424pubmed: 39995550google scholar: lookup
  7. O'Connell E, Dyson S, McLean A, McGreevy P. No More Evasion: Redefining Conflict Behaviour in Human-Horse Interactions. Animals (Basel) 2025 Jan 31;15(3).
    doi: 10.3390/ani15030399pubmed: 39943169google scholar: lookup
  8. Byström A, Egenvall A, Eisersiö M, Engell MT, Lykken S, Lundesjö Kvart S. The impact of teaching approach on horse and rider biomechanics during riding lessons. Heliyon 2025 Jan 30;11(2):e41947.
    doi: 10.1016/j.heliyon.2025.e41947pubmed: 39906839google scholar: lookup
  9. Fercher C, Bartsch J, Kluge S, Schneider F, Liedtke AM, Schleichardt A, Ueberschär O. Applying Multi-Purpose Commercial Inertial Sensors for Monitoring Equine Locomotion in Equestrian Training. Sensors (Basel) 2024 Dec 21;24(24).
    doi: 10.3390/s24248170pubmed: 39771905google scholar: lookup
  10. Crecan CM, Ciulu-Angelescu V, Morar IA, Lupșan AF, Tripon MA, Tripon MA, Bungărdean D, Daradics Z, Peștean CP. Quantitative lameness assessment in horses by using an accelerometer-based simple device: A preliminary study. Open Vet J 2024 Nov;14(11):3089-3099.
    doi: 10.5455/OVJ.2024.v14.i11.38pubmed: 39737023google scholar: lookup
  11. Asti V, Ablondi M, Molle A, Zanotti A, Vasini M, Sabbioni A. Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds. Front Vet Sci 2024;11:1459553.
    doi: 10.3389/fvets.2024.1459553pubmed: 39479203google scholar: lookup
  12. Gmel AI, Haraldsdóttir EH, Serra-Bragança F, Lamas LP, Rosa TV, Stefaniuk-Szmukier M, Klecel W, Neuditschko M, Weishaupt MA. Inertial sensor data of horses from four breeds at walk and trot in hand on a straight line. Data Brief 2024 Aug;55:110764.
    doi: 10.1016/j.dib.2024.110764pubmed: 39183964google scholar: lookup
  13. de Carvalho JRG, Del Puppo D, Littiere TO, de Sales NAA, Silva ACY, Ribeiro G, de Almeida FN, Alves BG, Gatto IRH, Ramos GV, Ferraz GC. Functional infrared thermography imaging can be used to assess the effectiveness of Maxicam Gel(®) in pre-emptively treating transient synovitis and lameness in horses. Front Vet Sci 2024;11:1399815.
    doi: 10.3389/fvets.2024.1399815pubmed: 38919154google scholar: lookup
  14. Li C, Mellbin Y, Krogager J, Polikovsky S, Holmberg M, Ghorbani N, Black MJ, Kjellström H, Zuffi S, Hernlund E. The Poses for Equine Research Dataset (PFERD). Sci Data 2024 May 15;11(1):497.
    doi: 10.1038/s41597-024-03312-1pubmed: 38750064google scholar: lookup
  15. Kallerud AS, Marques-Smith P, Bendiksen HK, Fjordbakk CT. Objective movement asymmetry in horses is comparable between markerless technology and sensor-based systems. Equine Vet J 2025 Jan;57(1):115-125.
    doi: 10.1111/evj.14089pubmed: 38566453google scholar: lookup
  16. Calle-González N, Lo Feudo CM, Ferrucci F, Requena F, Stucchi L, Muñoz A. Objective Assessment of Equine Locomotor Symmetry Using an Inertial Sensor System and Artificial Intelligence: A Comparative Study. Animals (Basel) 2024 Mar 16;14(6).
    doi: 10.3390/ani14060921pubmed: 38540019google scholar: lookup
  17. Hatrisse C, Macaire C, Hebert C, Hanne-Poujade S, De Azevedo E, Audigié F, Ben Mansour K, Marin F, Martin P, Mezghani N, Chateau H, Chèze L. A Method for Quantifying Back Flexion/Extension from Three Inertial Measurement Units Mounted on a Horse's Withers, Thoracolumbar Region, and Pelvis. Sensors (Basel) 2023 Dec 5;23(24).
    doi: 10.3390/s23249625pubmed: 38139471google scholar: lookup
  18. Pfau T, Landsbergen K, Davis BL, Kenny O, Kernot N, Rochard N, Porte-Proust M, Sparks H, Takahashi Y, Toth K, Scott WM. Comparing Inertial Measurement Units to Markerless Video Analysis for Movement Symmetry in Quarter Horses. Sensors (Basel) 2023 Oct 12;23(20).
    doi: 10.3390/s23208414pubmed: 37896509google scholar: lookup
  19. Anderson KA, Morrice-West AV, Wong ASM, Walmsley EA, Fisher AD, Whitton RC, Hitchens PL. Poor Association between Facial Expression and Mild Lameness in Thoroughbred Trot-Up Examinations. Animals (Basel) 2023 May 23;13(11).
    doi: 10.3390/ani13111727pubmed: 37889660google scholar: lookup
  20. Hobbs SJ, Serra Braganca FM, Rhodin M, Hernlund E, Peterson M, Clayton HM. Evaluating Overall Performance in High-Level Dressage Horse-Rider Combinations by Comparing Measurements from Inertial Sensors with General Impression Scores Awarded by Judges. Animals (Basel) 2023 Aug 2;13(15).
    doi: 10.3390/ani13152496pubmed: 37570304google scholar: lookup
  21. Crecan CM, Peștean CP. Inertial Sensor Technologies-Their Role in Equine Gait Analysis, a Review. Sensors (Basel) 2023 Jul 11;23(14).
    doi: 10.3390/s23146301pubmed: 37514599google scholar: lookup
  22. Guyard KC, Montavon S, Bertolaccini J, Deriaz M. Validation of Alogo Move Pro: A GPS-Based Inertial Measurement Unit for the Objective Examination of Gait and Jumping in Horses. Sensors (Basel) 2023 Apr 22;23(9).
    doi: 10.3390/s23094196pubmed: 37177397google scholar: lookup
  23. Egenvall A, Engström H, Byström A. Back motion in unridden horses in walk, trot and canter on a circle. Vet Res Commun 2023 Dec;47(4):1831-1843.
    doi: 10.1007/s11259-023-10132-ypubmed: 37127806google scholar: lookup
  24. Darbandi H, Munsters C, Parmentier J, Havinga P. Detecting fatigue of sport horses with biomechanical gait features using inertial sensors. PLoS One 2023;18(4):e0284554.
    doi: 10.1371/journal.pone.0284554pubmed: 37058516google scholar: lookup
  25. Lawin FJ, Byström A, Roepstorff C, Rhodin M, Almlöf M, Silva M, Andersen PH, Kjellström H, Hernlund E. Is Markerless More or Less? Comparing a Smartphone Computer Vision Method for Equine Lameness Assessment to Multi-Camera Motion Capture. Animals (Basel) 2023 Jan 24;13(3).
    doi: 10.3390/ani13030390pubmed: 36766279google scholar: lookup
  26. 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
  27. Davíðsson HB, Rees T, Ólafsdóttir MR, Einarsson H. Efficient Development of Gait Classification Models for Five-Gaited Horses Based on Mobile Phone Sensors. Animals (Basel) 2023 Jan 3;13(1).
    doi: 10.3390/ani13010183pubmed: 36611791google scholar: lookup
  28. Tian W, Zhang J, Zhou K, Wang Z, Dang R, Jiang L, Wang J, Cong Q. The Limb Kinetics of Goat Walking on the Slope with Different Angles. Biomimetics (Basel) 2022 Nov 30;7(4).
    doi: 10.3390/biomimetics7040220pubmed: 36546920google scholar: lookup
  29. Timmerman I, Macaire C, Hanne-Poujade S, Bertoni L, Martin P, Marin F, Chateau H. A Pilot Study on the Inter-Operator Reproducibility of a Wireless Sensors-Based System for Quantifying Gait Asymmetries in Horses. Sensors (Basel) 2022 Dec 6;22(23).
    doi: 10.3390/s22239533pubmed: 36502233google scholar: lookup
  30. Rhodin M, Smit IH, Persson-Sjodin E, Pfau T, Gunnarsson V, Björnsdóttir S, Zetterberg E, Clayton HM, Hobbs SJ, Serra Bragança F, Hernlund E. Timing of Vertical Head, Withers and Pelvis Movements Relative to the Footfalls in Different Equine Gaits and Breeds. Animals (Basel) 2022 Nov 7;12(21).
    doi: 10.3390/ani12213053pubmed: 36359178google scholar: lookup
  31. Feuser AK, Gesell-May S, Müller T, May A. Artificial Intelligence for Lameness Detection in Horses-A Preliminary Study. Animals (Basel) 2022 Oct 17;12(20).
    doi: 10.3390/ani12202804pubmed: 36290189google scholar: lookup
  32. Crecan CM, Morar IA, Lupsan AF, Repciuc CC, Rus MA, Pestean CP. Development of a Novel Approach for Detection of Equine Lameness Based on Inertial Sensors: A Preliminary Study. Sensors (Basel) 2022 Sep 19;22(18).
    doi: 10.3390/s22187082pubmed: 36146429google scholar: lookup
  33. Hoffmann JR, Geburek F, Hagen J, Büttner K, Cruz AM, Röcken M. Bilateral Change in Vertical Hoof Force Distribution in Horses with Unilateral Forelimb Lameness before and after Successful Diagnostic Anaesthesia. Animals (Basel) 2022 Sep 19;12(18).
    doi: 10.3390/ani12182485pubmed: 36139345google scholar: lookup
  34. Pagliara E, Marenchino M, Antenucci L, Costantini M, Zoppi G, Giacobini MDL, Bullone M, Riccio B, Bertuglia A. Fetlock Joint Angle Pattern and Range of Motion Quantification Using Two Synchronized Wearable Inertial Sensors per Limb in Sound Horses and Horses with Single Limb Naturally Occurring Lameness. Vet Sci 2022 Aug 25;9(9).
    doi: 10.3390/vetsci9090456pubmed: 36136672google scholar: lookup
  35. Pasquiet B, Biau S, Trébot Q, Debril JF, Durand F, Fradet L. Detection of Horse Locomotion Modifications Due to Training with Inertial Measurement Units: A Proof-of-Concept. Sensors (Basel) 2022 Jul 1;22(13).
    doi: 10.3390/s22134981pubmed: 35808476google scholar: lookup
  36. Pfau T, Scott WM, Sternberg Allen T. Upper Body Movement Symmetry in Reining Quarter Horses during Trot In-Hand, on the Lunge and during Ridden Exercise. Animals (Basel) 2022 Feb 27;12(5).
    doi: 10.3390/ani12050596pubmed: 35268165google scholar: lookup
  37. Hatrisse C, Macaire C, Sapone M, Hebert C, Hanne-Poujade S, De Azevedo E, Marin F, Martin P, Chateau H. Stance Phase Detection by Inertial Measurement Unit Placed on the Metacarpus of Horses Trotting on Hard and Soft Straight Lines and Circles. Sensors (Basel) 2022 Jan 18;22(3).
    doi: 10.3390/s22030703pubmed: 35161452google scholar: lookup
  38. Mao A, Huang E, Gan H, Parkes RSV, Xu W, Liu K. Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data. Sensors (Basel) 2021 Aug 29;21(17).
    doi: 10.3390/s21175818pubmed: 34502709google scholar: lookup
  39. Tijssen M, Serra Braganςa FM, Ask K, Rhodin M, Andersen PH, Telezhenko E, Bergsten C, Nielen M, Hernlund E. Kinematic gait characteristics of straight line walk in clinically sound dairy cows. PLoS One 2021;16(7):e0253479.
    doi: 10.1371/journal.pone.0253479pubmed: 34288912google scholar: lookup
  40. Sapone M, Martin P, Ben Mansour K, Chateau H, Marin F. The Protraction and Retraction Angles of Horse Limbs: An Estimation during Trotting Using Inertial Sensors. Sensors (Basel) 2021 May 30;21(11).
    doi: 10.3390/s21113792pubmed: 34070859google scholar: lookup
  41. Darbandi H, Serra Bragança F, van der Zwaag BJ, Voskamp J, Gmel AI, Haraldsdóttir EH, Havinga P. Using Different Combinations of Body-Mounted IMU Sensors to Estimate Speed of Horses-A Machine Learning Approach. Sensors (Basel) 2021 Jan 26;21(3).
    doi: 10.3390/s21030798pubmed: 33530288google scholar: lookup
  42. 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
  43. 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
  44. Tijssen M, Hernlund E, Rhodin M, Bosch S, Voskamp JP, Nielen M, Serra Braganςa FM. Automatic detection of break-over phase onset in horses using hoof-mounted inertial measurement unit sensors. PLoS One 2020;15(5):e0233649.
    doi: 10.1371/journal.pone.0233649pubmed: 32469939google scholar: lookup
  45. Sapone M, Martin P, Ben Mansour K, Château H, Marin F. Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse's Limb. Sensors (Basel) 2020 May 25;20(10).
    doi: 10.3390/s20102983pubmed: 32466104google scholar: lookup
  46. Bouwman A, Savchuk A, Abbaspourghomi A, Visser B. Automated Step Detection in Inertial Measurement Unit Data From Turkeys. Front Genet 2020;11:207.
    doi: 10.3389/fgene.2020.00207pubmed: 32265981google scholar: lookup
  47. Schmutz A, Chèze L, Jacques J, Martin P. A Method to Estimate Horse Speed per Stride from One IMU with a Machine Learning Method. Sensors (Basel) 2020 Jan 17;20(2).
    doi: 10.3390/s20020518pubmed: 31963422google scholar: lookup
  48. 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).
    doi: 10.3390/ani9080539pubmed: 31398822google scholar: lookup
  49. Hardeman AM, Serra Bragança FM, Swagemakers JH, van Weeren PR, Roepstorff L. Variation in gait parameters used for objective lameness assessment in sound horses at the trot on the straight line and the lunge. Equine Vet J 2019 Nov;51(6):831-839.
    doi: 10.1111/evj.13075pubmed: 30648286google scholar: lookup
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