I was grateful to be able to watch the replay of the Saddle Research Trust 4th International Conference, which was presented online on 11th December 2021. Here I share with you some of my learnings from the conference. Find out more about the Saddle Research Trust, and see the proceedings from previous conferences, at www.saddleresearchtrust.com.
Dr Braganca started by discussion the history of gait analysis. Some of the first measurements were recorded in France (1873 and 1894) and the USA (Muybridge, 1887). Today, gait analysis includes kinetics (which measures forces related to movement), kinematics (which measures movement), electromyography (which measures electrical activity produced by skeletal muscles), and others (for example rein tension, and pressure mats).
Kinetics, the measure of the forces related to movement, is the gold standard way of measuring weight bearing lameness, because you can measure how much force is going through each leg. However, this generally uses a treadmill or other specialised technology (for example force plates, pressure places, and force shoes), and is difficult to use in general practice (i.e. outside of the lab). Kinetic techniques have been used, for example, to look at study surface properties, to understand the effect of different shoes, and to study compensatory adaptations to lameness.
Kinematics can be used to quantify speed, angle, and displacement. It uses 3D optical motion capture, and IMU sensors. The optical motion capture is very accurate but requires several cameras and so is quite expensive. The IMU sensors are less accurate but are portable, wireless, inexpensive, and can record for up to several hours at a time. Kinematics are used to measure horse rider interactions, sports performance, lameness, and breeding selection and phenotypic.
Looking more in depth at using kinematic gait analysis for lameness, we focus on symmetry. The theory is that a sound horse moves symmetrically, and a lame horse moves less symmetrically. Because of gait analysis, we can now measure asymmetry (differences between left and right) objectively, rather than subjectively. This means we can put accurate numbers on it, rather than describing what we can see.
We need to begin with understanding what is ‘normal’, in order to be able to recognise what is ‘abnormal’. The amount of variation between horses is huge, which means it’s very difficult to get what’s known as ‘population averages’. We could look at whether a horse is moving differently to how it moved before, but for most horses we don’t have a baseline reference to work from. Therefore we use the horse as it’s own reference, and we compared left to right.
Measuring symmetry in gait analysis using kinematics is done by measuring the up / down movement of the head, the withers, and the pelvis. We can use the head and the withers to recognise the lame leg, and the withers to decide whether the lameness is primary (the root cause) or secondary (compensatory movement). Research suggests that vets who use gait analysis have more positive views of it than vets who don’t.
A study following 12 horses over 42 days took reference values 5 times a day, to gather information on what level of variation might be considered as ‘normal’. This research showed that variation between horses is much bigger than variation within the measurements for each horse. The team were able to provide reference values that can be used to quantify lameness.
Research is ongoing using surface EMG, non-invasive technique to measuring the electrical activity of the superficial muscles. For example, researchers can measure the activity of the hamstring muscle (semitendinosus) on the circle. They are working to find out which muscles work at which part of the stride cycle. Surface EMG is commonly used in the human field. It can help us to understand adaptations to exercise and lameness, and in exercise physiology to quantify fatigue.
Gait analysis has many uses in the equine field. For example, a 2018 study looked at assessing horses as fit to compete or not fit to compete in FEI competition. Four judges visually assessed the horse as fit or not fit to compete, based on FEI guidelines. There were varied levels of agreement between the judges. Another study looks at lameness in the Icelandic horse, which is particularly difficult to measure (both with the eye, and using gait analysis) because of the small amount of up and down movement in the upper body, and the quick movement of the legs. An investigation into the ability of physiotherapists, veterinarians and students to score the movement of the back found that there was limited agreement between what the participants reported seeing, and what was measured by the gait analysis technology. A surface EMG study is looking at the adaptations to temporary lameness with was induced by a modified shoe. Another study is measuring the movement of a group of 12 horses on a water treadmill, compared to being on a dry treadmill. This could influence the use of the water treadmill in rehabilitation, for example. A team are investigating the feasibility of using 3D printed shoes, which are custom made to the individual hoof.
Machine learning is boosting our capacity to understand the information that we get from gait analysis. For example, a study is looking at using developing an IMU sensor to measure ground reaction forces. In another area, machine learning is being developed to calculate the speed of the horse indoors, where GPS can’t be used. Markerless gait analysis is in development using computer vision. Machine learning has great potential, but it works by following specific rules and does not have any deep understanding of the subject.
A short but poignant sentence in conclusion: “Technology won’t replace vets.. but bets who use technology logically and carefully will replace those who don’t”. Professor Derek Knottenbelt.
Find out more about the Saddle Research Trust, and see the proceedings from previous conferences, at www.saddleresearchtrust.com.
© Sue Palmer, The Horse Physio, 2021
Treating your horse with care, connection, curiosity and compassion
