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How can we measure walking gait?

In this video, Dr Claudia Mazza explains how we can analyse our walking gait.
Whenever we want to study human movement, normally we start by sending our patient to a gait lab, which is the place where we measure how the different parts of the body moves. And the way we do this is by using different kinds of sensors that we attach to the body of the person, like this little ball here that we call a marker. What happens though is that by doing this we can have some of the information we need, but not all of it. For example, we cannot put a sensor inside a muscle to know how much force a muscle is producing while a person is walking.
And for this reason, what we use are what we call the muscle skeletal models. So the most basic model is the one you see in this figure here, it’s made just of bones. The movement of these bones is driven by using the information coming from the gait lab. These little dots you see here represent the movement of these points that were attached to the subject’s skin, and this arrow here represents the forces that we measured while the person was walking. But of course, there is something missing here, which is the muscles.
And so for this reason, normally, what we try to do is to join the information that comes from the gait lab together with some information about the patient anatomy. And of course, if we want to know the anatomy of a specific subject, of a specific patient, what we need to do is to use either images coming from MRI scans or from CT scans. And then what we can do is build different kinds of models of these muscles and this anatomy that can be more sophisticated and more simple according to the applications. Once we have this representation in 3D of a subject’s anatomy we can then merge this information to the one that we obtained from the gait lab.
And what we finally can build is some simulation of our patient’s gait that can tell us how the different muscles behave while the person is walking. So in this video, for example, you see that some of these muscles are in red whereas other muscles are in blue. And this means that in this specific instant of time while the person is walking they’re actually using the muscles that are in red in the animation. Once we know how the different muscles are acting, and how the different bones are moving with respect to each other, we can also have an idea of how big are the forces that are being exchanged between the different bones.
So the forces that are internal to a joint, like the hip, the knee, or the ankle joint. And this is particularly important when we’re interested in knowing, for example, if there is any damage in the bone that is caused by repetitive movement or is there information that we can use to predict the effect of a joint replacement, like a knee replacement or a hip replacement. We can try to use the models to predict which could be the best implant to choose, and which could be the best way to actually put this implant into a person’s body.
Or we could use these models to answer some important clinical scientific questions that are still unknown, and this is what we are trying to do in our research projects at the moment. For example, these are pictures of the ankle joint of a child suffering from juvenile idiopathic arthritis. This is one of those pathologies where there is still so much to know and to find out about what is exactly happening when the child grows and when the pathology progresses, and how each different patient responds to a treatment. So having a way to quantify these changes could be extremely useful in order to try and test new interventions and new medicines.
So for example, here you see how we try to use images in order to quantify how much cartilage or bones are being affected by the JIA [juvenile idiopathic arthritis]. But again, by using simple images it’s already been shown that this might not be enough to explain why each different patient is responding in a different way to a treatment or an intervention. We then started using our models to these purposes. And we started looking at children at time zero when they’re referred to the patient in the baseline, what happens after six months when they get treated, and if the effects of the treatment stay and remain after 12 months.
And what we are looking at - and this is what you see in these graphs - is the amount of force that is produced inside each joint. So inside the hip, the knee, and the ankle at these three-time points. You can see, for example, if you look at the hip here when the child arrived at the first observation that there was a clear difference in terms of the amount of force that was acting inside the joint. And this was most likely due to the fact that the child was trying to protect the left hip by putting more weight on their right hip in order to avoid pain.
More than anything else, this was indeed a response to what was happening also at the knee level. Then after the treatment, this child started having a more symmetric pattern. You can see here that the two curves are kind of overlapping. But then, again, after 12 months when the treatment was gone we started observing and quantifying again some differences happening. This kind of information is what the clinician could use in order to decide when to intervene again. In this case, the treatment was an injection of steroids at the joint. Or to see whether the treatment has been effective or not.
So it’s really just by using this very sophisticated technology and approach that we can start answering questions that so far we couldn’t give an answer to.

Maintaining a healthy gait is an important part of ageing well, and our ability to measure and describe its characteristics can help us to better understand how to do this.

In the previous video, we saw that one way to study gait is to attach sensors to a person to measure how different parts of the body move. However, this information alone does not give a complete picture of what is happening to the musculoskeletal system.

In this video, Dr Claudia Mazzà from The University of Sheffield, explains her latest research which combines sensor measurements from the gait lab with information about an individual’s unique anatomy, allowing clinicians to see how patients are using their muscles and joints as they walk.

These models can be used to guide treatment, test how well treatments are working and find out more about how different conditions progress over time.

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The Musculoskeletal System: The Science of Staying Active into Old Age

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