Image: Kieran Moran
DCU’s Prof Kieran Moran gives us a rundown on the fascinating science of running.
It was Prof Kieran Moran’s almost too intense love of sport in his younger years which led him to a career focused on the science of movement. He’s a professor of biomechanics in the School of Health and Human Performance at Dublin City University and a principal investigator at the Insight SFI Research Centre for Data Analytics. Here, he explains how he uses AI, gait analysis and other techniques to help runners avoid injuries and boost performance.
Tell us about your current research.
I am a biomechanist; I study how humans (and elephants and monkeys) move. This interest includes how do we help recreational runners stay injury free, how do children learn to cycle, how do we help older people stay functionally independent in their home, how do we use technology to help older people rehabilitate from cardiovascular disease, and how do we help tennis players (camogie players, hurlers, golfers) ‘self-learn’ to strike the ball harder?
Running holds a particular fascination for me. We have certainly evolved to run, and it is something we do a lot of as children, albeit a little less as adults. It is one of the most popular forms of physical fitness, is extremely cheap (if you avoid the excessive ‘marketeering’ running shoe manufacturers), can be done individually or as part of a social group, and has major physical and mental health benefits.
However, the style of running that humans (and animals) have evolved reflects a survival strategy. It is an evolutionary battle for humans between efficient running, to allow us to be effective persistent hunters, and the challenge of staying injury free, that would prevent us from hunting and escaping those animals chasing us.
When we run, we basically collide with the ground like a pogo-stick, bounding forward on each foot strike. This provides us with a very energy efficient style of running; we store elastic energy in our muscles and tendons when we strike the ground, and reuse this (this is where the efficiency dimension comes in to play) to propel ourselves forward.
However, this technique of running also contributes to injury. It results in us striking the ground very hard (to store the energy). Given that all injuries are caused by high loading relative to tissue strength, this hard striking of the ground places higher loading on our bodies, which contributes to injury.
We can also see how animals make use of this action to move efficiently, be it kangaroos hopping or horses galloping. However, we can also see how some animals, such as elephants and arboreal (tree living) monkeys, have evolved to utilise a running technique to reduce loading on their body, thereby reducing the likelihood of injury.
An excited baby African elephant running to a waterhole. Image: © Duncan Noakes/Stock.adobe.com
Elephants are a great example – they are very heavy and need to run more softly than lighter animals, while arboreal monkeys need to run softly through branches so that they don’t spring up and down too much on the branch and get sprung off. They both achieve this by using a form of ‘cushioned running’ where they flex their hips and knees and keep their main body mass and feet closer to the floor.
It used to be thought that we cannot change the way we run, because it is so engrained and ‘natural’ to us. This is not the case. Clearly, runners can adopt this more injury resistant cushioned running style. Simply watch older runners who have a significant knee or hip injury and who need to reduce the load on their body to decrease the instantaneous pain they are feeling. Or similarly, watch people running with a heavy backpack, they also adopt this cushioned running style to reduce the higher stress they would feel on their back.
We have developed an app which can be used in combination with a wearable inertial sensor. It measures how hard the runner strikes the ground. The runner can then set a threshold by which they want to reduce the ground-striking load by, say, 10pc, then the app sends an audible ‘beep’ via a wireless headphone to the runner indicating when they have not adopted an appropriate cushioned running technique. In our testing of the system, runners could appropriately change their running technique to reduce how hard they strike the ground by up to 40pc.
In other research we completed in 2023, we undertook what we think is the largest ever prospective-based biomechanical study of running related injuries. We brought 320 runners into our lab and measured their running technique when unfatigued and fatigued using 3D motion analysis (to an accuracy of 2mm) and inertial sensors, and a whole host of traditional clinical assessments including strength, flexibility and foot posture. We also recorded their injury history, training programme, warm-up and injury management strategies, and running goals. We subsequently tracked them for one year to identify who became injured to try to identify ‘why’. Just over 50pc of all the runners reported an injury within that time.
We learnt which of these factors also cause injury. We used AI to be able to predict someone’s likelihood of injury with an accuracy of 26pc. This, however, is not accurate enough for us, pointing to a significant challenge of research into running injuries. The study, completed over a period of three years pointed us to some factors that we (and other researchers) have not considered properly in their research. Firstly, runners define injury very differently, not only from each other, but also from many clinicians and researchers. Over the last year, we have completed focus groups to determine a new injury continuum which has the potential to revolutionise what we even consider an injury and how ‘lower-level’ injuries (eg niggles) may be the missing link.
In addition, it became clear that undertaking one-off assessments of running technique and runners’ perceptions of their injuries, how they feel and factors of internal loading (eg sleep, menstrual cycle, readiness to train) was not sufficient. We have since developed an app that will assess all of these on a run-by-run basis for every run they undertake. We believe that using this high-resolution, accurate, self-tracked data, combined with advanced AI, will allow us to develop personalised recommender systems to help runners stay injury free and make the most of their training.
In your opinion, why is your research important?
Given the health and personal benefits of running, we need to find a way of helping the current 50pc of runners who become injured every year. Many runners continuously cycle through periods of being injured and injury free, often resulting in them going long periods without running or finally giving up running altogether.
If we can produce individualised AI-based algorithms that will provide personalised recommendations to help runners stay injury free and make the most of their training, they will be able to avail of the significant health and personal benefits of running.
Runners are amongst the highest adopters of wearable and app-based technologies. To date, current wearable and app-based systems are invariably only performance-based; our research has shown that runners are longing for an effective injury prevention system.
What inspired you to become a researcher?
Unfortunately perhaps, my love of sport dominated too much as a youngster, and I left secondary school in England with just one O-level. Even when I went on to sixth-form college, after four years (of excelling in sport) I only left with one A-level, at grade E (the lowest pass).
At that point I never really believed that I was good academically, and hence I never devoted any real time to it. I thought I was below average, and I used sport as a means of showing myself and others that I was good at something.
It took me a while to merge an innate, but unexplored, interest in maths with my love of sport, and to realise that there was a career out there for me in sports science, specifically in biomechanics. I started to read around how aspects of sport could be better understood through applying mathematical principles (including Newton’s laws of motion) and I was somewhat hooked.
With this focus, I successfully studied for three A-levels part-time (maths, pure maths, statistics) while working in the office of a transport company, and ultimately went to the University of Ulster with a vigour for studying sport science. Ultimately, it was an exposure to research papers addressing real-world issues of human motion (biomechanics) that created my endless passion for research.
Specifically, what fascinates me in sport and human movement is a desire to understand the complexity of how movement is learned and optimised, within the constraints of our body design and our environment. I see far more fascinating questions to be answered than I can explore, and the accelerated growth of wearable sensors and AI provides ideal tools for exploring some of these questions.
What are some of the biggest challenges or misconceptions you face as a researcher in your field?
The wonderful thing about studying sport and human movement is that it touches so many peoples’ lives and their own personal interest. I can talk for hours –perhaps to some peoples’ annoyance – about the complexity of movement, performance and injury.
The challenge, however, facing sports scientists is that everyone then has an ‘expert’ opinion based on their own experience. The challenge of the ‘experience of one person’ is that it can be heavily biased by what they think is important or what they have been told from uninformed sources. In many cases, those uninformed sources have very loud voices. The sporting goods and fitness industries are worth billions. The mark-up costs on products is extraordinary, providing them with large budgets for marketing, not only via traditional TV and magazine adverts, but perhaps more challengingly, via social media marketing, whereby they are presenting views as being based on science.
For the last 30 years for example, every running shoe manufacturer points to how their shoe has the potential to reduce injury (they are careful not to say they do actually reduce injury) by helping to ‘control the foot’ or increasing the ‘potential to reduce loading’ etc. The truth is, if they could actually reduce the likelihood of injury compared to a ‘standard’ running shoe, they would publish the research and use it is a strong marketing tool. Instead, they rely on pseudo-science or creating secondary links to science to fuel an impression of injury prevention. Interestingly, our own recent research showed that changing your running shoes too often actually increased the risk of a running injury.
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