EquiMoves system

Applications

EquiMoves provides high-end tools that can be used by equine vets, equine trainers and breeders, and stud book associations in several application domains.

The interface is designed to show asymmetries in a variety of ways, ranging from an easy overview to in depth stride by stride information. This is paired with quick and easy comparisons of measurements and a report function, making it cutting edge technology for objective lameness assessment.

EquiMoves empowers equine clinicians, trainers and breeders to monitor and optimize performance.

Who can use EquiMoves

Equine vets

Our asymmetry analysis tool makes lameness exams quick and reliable.

  • Lameness exams
  • Pre-purchase exams
  • Sport horse monitoring

Equine trainers & breeders

Equine trainers are able to monitor objectively the training of horses.

  • Fit to compete
  • Monitoring training (trainers)
  • Selection of horses (breeders)

Stud book associations

During studbook inspections horses are evaluated for the primary traits of movement.

  • Fit to compete
  • Selection of horses
  • Tool in combination with genomic selection
Interested in an EquiMoves system?

Request more information

If you are interested in using EquiMoves in your activities please send us a message and we will be happy to give you more information.

Send a request
EquiMoves News

Learn more about EquiMoves at the Science of Equine Locomotion Symposium

EquiMoves will be presented by Filipe Bragança on 21st of October at 19:00 during the Science of Equine Locomotion Symposium. The symposium is an online event taking place on 30th of September and 21st of October 2020.  … Read more →

January 2020: EquiMoves trials in Florida

EquiMoves was used in trials, in january 2020, with Hillary Clayton, Sarah Jane Hobs, Marie Rhodin and Elin Hernlund for research purposes in Florida with high-level dressage horses. The goal of this research is to understand better the… Read more →

Research papers

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning

F. M. Serra Bragança, S. Broomé, M. Rhodin, S. Björnsdóttir, V. Gunnarsson, J. P. Voskamp, E. Persson-Sjodin, W. Back, G. Lindgren, M. Novoa-Bravo, C. Roepstorff, B. J. van der Zwaag, P. R. Van Weeren & E. Hernlund, 20… Read more →