An Accessible AI Solution for Equine Health

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Why one company believes its AI, app-based solution will improve gait analysis by complementing traditional evaluations. 

If the Sleip leadership team had any initial reservations traveling from their Swedish company headquarters to the United States late in 2022 to talk about their AI, app-based solution with equine health stakeholders, those fears were quickly allayed.

Indeed, Sleip’s team at the AAEP Convention in San Antonio, including co-founder Elin Hernlund – a veterinarian and renowned researcher within equine biomechanics – was busy throughout the conference. “We were even approached on the dance floor at the closing event, where we happily got our iPhones out to demo Sleip to curious vets,” Dr. Hernlund said. “The AAEP was a great experience with many rewarding conversations and meetings with U.S. equine veterinarians. We look forward to catching up with many of them at the AAEP in San Diego this year.”


How it works

Sleip’s AI algorithms detect and track multiple anatomical landmarks on a horse’s body from a simple smartphone recording. By analyzing the vertical displacement of the head and pelvis, the system identifies the asymmetries in the horse’s gait with a 2 mm precision. These asymmetries indicate unequal loading of the limbs during different phases of the stride, a key sign of lameness.

These measurements have been used in clinical practice for over a decade, Dr. Hernlund said, but have required costly multi-camera motion capture systems or IMU sensors. “Sleip’s AI and computer vision technology offer a more accessible solution that does not involve markers on the horse or any other physical equipment.”

Whether it’s identifying early signs of single-limb lameness or differentiating between lameness and other asymmetries, objective gait analysis provides veterinary professionals with insights that surpass the capabilities of the human eye, “and Sleip’s AI technology makes those insights accessible for daily clinical use.”

Sleip developers believe the AI solution complements traditional evaluations in several ways. “A quantified measurement is a valuable decision support and provides documentation, for comparisons, before and after a nerve block for instance, as well as for monitoring horses over time,” Dr. Hernlund said. “Quantified measurements and documentation make it easier to consult with colleagues and communicate with clients.”

Looking at the physical limitations of the human eye, there are also some arguments on why quantitative gait analysis is of added value. The time resolution of the human eye is limited to about 10-15 samples per second, which makes the stride frequency at trot quite challenging for our biological image processing system, Dr. Hernlund said.

Even for the very trained eye, visual lameness assessments are difficult. And what one veterinarian sees another one may not. A lot of research has been done to investigate the agreement between veterinarians during the clinical orthopaedic examination. This agreement, on the primary lame limb as well as on lameness grade, is frequently shown to be moderate or poor.1,2,3,4,5

“Sleip’s AI technology detects even subtle irregularities in the horse’s gait and can also be put to educational use,” Dr. Hernlund said. “We hear customers also use the app to train their eyes, using the slow-motion video with data overlay. In that sense, Sleip also sharpens subjective assessment capabilities. It is also nice to see that we have several veterinary schools and universities among our users, training students in gait analysis and lameness assessment.”

Dr. Hernlund said the app is user-friendly, easy to understand and easy to use – “as easy as filming with the camera on your phone.”

Features include:

  • Synchronized video and asymmetry data for straight-line and longeing
  • Historical analyses and comparison functions
  • Sharing functionality: export PDF to clients, invite
    clients to record for remote support
  • Documentation: horse profiles with historical analyses, annotation function for diagnostic analgesia

 

Improving horse welfare

Veterinarians can use Sleip to help in the diagnostic process, but also in evaluating treatments and monitoring rehabilitation in collaboration with clients, as a remote service. “It’s valuable for clients and represents a commercial opportunity for the clinics,” Dr. Hernlund said.

Apart from powering up orthopaedic assessments and rehabilitation, the developers emphasize that Sleip provides the vet community with the opportunity to work on prevention of lameness. “The strongest use cases we see are regular gait monitoring for early signs of subclinical lameness,” she said. “This type of preventive work is highly appreciated by some of the world’s leading professional riders, but could be a valuable service provided to many more working horses out there. It is about finding orthopaedic issues while they are still treatable. The collaborative function that allows for remote recordings is also valuable for prepurchase exams and for consultations with colleagues when in the field.”

Sleip developers believe the technology improves horse welfare by providing access to insights into how the horse moves and why. Gait analysis gives an unbiased and objective voice to the horses. Debates about a horse’s well-being in the equine sport industry, for instance, have often been influenced by the emotions and feelings of riders, trainers, and spectators, Dr. Hernlund said. “We hope to change that so that decisions about a horse’s welfare are made based on precise data.”

By continuously monitoring horses at home, during training, and just before competitions, this technology can more accurately determine whether a horse is fit to compete. It also provides insights into the impact that specific training and activities have on a horse. The objective measurements allow for more standardized assessments, reducing subjectivity and bias.

Growth plans

The U.S. is one of Sleip’s largest markets, with a diverse customer base ranging from large clinics to solo ambulatory vets. “Our ambition in the U.S., as in the rest of the world, is high adoption of Sleip and objective gait analysis because we believe that will make a difference for horses’ health and performance,” said Per Hassbring, Sleip head of growth & partnerships. “We want to empower vets with a tool for objective health data, but also for documentation and collaboration, and envision a future where regular measurements and monitoring of how the horse moves are standard practice.”

Sleip has introduced a horse-sharing option in the Sleip application, which allows veterinarians to invite clients to record their horses at home with the analysis data uploaded to the vet’s account automatically. This enables a form of telemedicine that adds value to the clinic, but also benefits the horse owner and the horse.

“There are several trials now underway by competition organizers and regulatory authorities in different markets and across different disciplines to evaluate the use of Sleip to support the work of riders, trainers, and competition vets in ensuring horses are fit to compete.”

 

1 Fuller CJ, Bladon BM, Driver AJ, Barr AR. The intra- and inter-assessor reliability of measurement of functional outcome by lameness scoring in horses. Vet J. 2006;171(2):281-286. doi:10.1016/j.tvjl.2004.10.012

2 Hammarberg M, Egenvall A, Pfau T, Rhodin M. Rater agreement of visual lameness assessment in horses during lungeing. Equine Vet J. 2016;48(1):78-82. doi:10.1111/evj.12385

3 Hewetson M, Christley RM, Hunt ID, Voute LC. Investigations of the reliability of observational gait analysis for the assessment of lameness in horses. Vet Rec. 2006;158(25):852-857. doi:10.1136/vr.158.25.852

4 Keegan KG, Wilson DA, Wilson DJ, et al. Evaluation of mild lameness in horses trotting on a treadmill by clinicians and interns or residents and correlation of their assessments with kinematic gait analysis. Am J Vet Res. 1998;59(11):1370-1377.

5 Keegan KG, Dent EV, Wilson DA, et al. Repeatability of subjective evaluation of lameness in horses. Equine Vet J. 2010;42(2):92-97. doi:10.2746/042516409X479568

 

Photo credit: Photography courtesy of SLEIP

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