Equine locomotion analysis

Our research enables veterinarians to measure what we can’t see, such as movement and muscle activity

Equine lameness potentially affects all horses and their owners and is the costliest health problem in the equine industry. Not only in terms of economical loss but also in terms of loss of quality of life raising an important welfare question. Appropriate treatment depends on accurate diagnosis. However, diagnosis of lameness is often subjective, based on visual examination, often leading to contradictory opinions among different equine professionals, physiotherapists and veterinarians. With quantitative gait analysis, we aim at supporting the equine community to objectively evaluate the locomotion of horses, hence detecting lameness earlier and more accurately. We explore many techniques to achieve this including optical motion capture, inertial measurement unit sensors (IMUs), force-/pressure plates and surface electromyography (sEMG). We combine these techniques with advanced data analysis and processing techniques such as machine learning in order to achieve our goals of improving animal welfare and increase the sustainability of the horses carer as an athlete.

EquiMoves
In the EPHOR project researchers will lay the groundwork for evidence-based and cost-effective prevention for improving health at work, by developing a working life exposome toolbox. This consortium consists of 19 exposure, health, and data technology scientists and technology partners from 12 different countries. EPHOR is one of the nine projects of the European Human Exposome Network.
Duration: 2018 - Ongoing
Project members UU: Filipe Serra Bragança, René van Weeren
Collaborators: UU, Inertia Technology, Rosmark Consultancy, UZH, SLU
Lameness in gaited horses
This project aimed at investigation of gait changes due to lameness in gaited animals, mainly the Icelandic horses. Lameness assessment in the Icelandic horse is challenging, and very little objective information exists – we want to investigate why is lameness difficult to see in these horses and to provide new objective methods to improve lameness detection.
Duration: 2017 - Ongoing
Contact: Filipe Serra Bragança, Ineke Smit
Collaborators: UU, SLU, Holar University
Assessment of Equine Muscle Activity Patterns
The goal is to explore how surface electromyography (sEMG) can be used as a tool to investigate the equine neuromuscular system under different circumstances. As such, sEMG can be applied in healthy populations to assess the roles and interactions of muscles during exercise, but also in clinical lameness cases to understand the roles muscles play when horses adapt to musculoskeletal injury, pain or pathology.
Duration: 2018 – 2023
Contact: Ineke H. Smit
Collaborators: SLU
Machine learning techniques for supporting equine lameness diagnosis
In this project we use inertial units (IMU) combined with advanced computing methods to provide previously unavailable information, such as kinetic parameters or environmental information, to clinicians and other relevant stakeholders. Based on data collection campaigns both within clinical and field setups, we develop classification methods and investigate what information is most important in recognising specific gait abnormalities.
Duration: 2019-2023
Contact: Jeanne I.M. Parmentier
Collaborators: University of Twente, SLU, KTH
The Equine Back
Historically the equine back has been researched extensively, which resuled in multiple scientific publications. Also clinically, the back receives a lot of attention on a daily basis by the equine veterinarian. Unfortunately, this goes with a high amount of subjectivity and there is a poor connection between scientific research and the daily equine patient. The goal is to implement science in the clinical practice and increase the level of objectivity in the evaluation of the equine back patient.
Duration: 2017-2025
Contact: Tijn J.P. Spoormakers, Harold Brommer
Collaborators: UU
Longitudinal monitoring
The goal is to collect kinematic and physiological data from equine athletes of different disciplines (dressage, show-jumping, eventing, endurance), both during exercise and clinical lameness exams. Using machine learning techniques, we develop models that can be used to discriminate between a sound/fit-to-compete and abnormal/lame horse. With that, we aim to improve early detection of lameness and thereby reduce injuries and withdrawal from sport activities.
Duration: 2019 - ongoing
Contact: Jeanne I.M. Parmentier, Rhana Aarts
Collaborators: Carolien Munsters (UU, Equine Innovation), Esther Siegers (UU), Hamed Darbandi (University of Twente)
Lameness perception
One of the most important aspects of veterinary education is the ability to correctly assess the movements of any type of animal. In horses specifically, lameness assessment is something that most clinicians do regularly. Recent studies show that most lame horses are recognized as being lame, but that is difficult to determine the correct limb(s). This study investigates what veterinarians (novice to experts) look at and how they interpretate their findings during a lameness assessment.
Duration: 2020 - ongoing
Contact: Sanne van Zalen
Varenne – a monitoring tool for gait analysis during traning
This project aims at the development of a system for collecting and analysing data of horses training for harness racing. This project wants to bring more evidence to the planning of training protocols in harness-racing, resulting in a better and more sustainable career of horses. In this project we develop integrated hardware and software platform that can be used to collect and analyse data from training horses. In this project we are combining movement sciences with sports physiology, integrating some important physiological parameters.
Duration: 2019 - ongoing
Contact: Rhana Aarts
Collaborators: SLU, Inertia Technology, Rosmark Consultancy, Menhammar Stud farm