Tyndall researcher Liudmila Khokhlova is looking to discover new diagnostic methods using movement analysis and acoustic emission recordings.
Liudmila Khokhlova studied biomedical engineering at Tomsk Polytechnic University, before going on to work in industry as an electronic engineer. She then returned to academia, becoming an electronic and research engineer at Tomsk State University in 2014.
During this time, she worked on several projects such as developing a remote monitoring system for high-risk pregnancies and a device for CPR procedure assistance and patient monitoring, as well as anthropomorphic robot modelling.
Since 2019, Khokhlova has been working on her PhD at Tyndall National Institute, the ICT research centre based at University College Cork. She is also a researcher with Insight, the Science Foundation Ireland research centre for data analytics.
‘Evaluation of knee friction using sound can add to traditional methods – and together they have a potential to allow earlier detection of arthritis and other conditions’
– LIUDMILA KHOKHLOVA
Tell us about the research you’re currently working on.
Currently I am working on my PhD thesis and the project is focused on alternative ways to diagnose knee conditions. We use movement analysis and acoustic emission recordings, or basically sound from the knee, to see if the joint is okay.
Intuitively, we all know that if your knees start to creak or squeak or make some other unusual noises, something other than the normal clicks, that might be worrying. Our goal is to take this notion to the next level, record the sound that cannot yet be heard by the naked ear, and see if this can be advanced into a new diagnostic method.
In your opinion, why is your research important?
Why do you need another method to assess someone’s joints? We have MRI and x-rays, and they are great. However, there are two main issues: high cost and complicated technology.
Those scans can only be done in a hospital. For example, if a person is going through rehabilitation after surgery or undergoing treatment, it could be quite costly to check up on them. There’s simply not enough personnel and machines.
With the rise of telemedicine, cheaper and simpler technologies such as acoustic emission can be used in home monitoring devices, allowing the same standard of care without the need for frequent appointments.
Moreover, evaluation of knee friction using sound can add some information to the traditional methods – and together they have a potential to allow earlier detection or even prediction of arthritis and other conditions.
What inspired you to become a researcher?
As long as I can remember, even as a small child, I was fascinated with technology and science. I was a huge fan of science fiction and read every sci-fi book available in the local children’s library.
My parents, especially my father, encouraged my curiosity. Once he brought me a microscope, which resulting in me investigating just about everything I could fit under the lens. I always had help with my small DIY projects such as wind-up boats and simple chemical experiments.
Simple things grew, and in high school I had an opportunity to carry out a few bigger projects and participate in scientific conferences for school students. I guess some natural curiosity and a supportive environment ultimately lead me to my current career.
What are some of the biggest challenges or misconceptions you face as a researcher in your field?
Currently in the area of biomechanics and wearable devices in general, we can collect a lot of data. The issue, however, arises from what you do with this data. What does this data mean?
So multidisciplinary teams are irreplaceable – clinical specialists or sportspeople and coaches, engineers and scientists can achieve greater understanding of the data and figure out what needs to be measured, leading to the great results that would also be useful in real life.
Another challenge would be the accessibility of the data. In biomechanics and human health research in general, collecting data takes a lot of time and resources. Thankfully, open science and the open data movement is something gaining momentum right now.
Making the data you collect freely available has a great potential to improve the quality of research. The work can be checked and repeated. Moreover, the next person working on a similar topic can use your data to build additional knowledge. It can be augmented with additional data, which is ultimately a more effective way of research than collecting similar data, wasting time and resources.
Do you think public engagement with science has changed in recent years?
The pandemic had a huge influence on every aspect of our lives. Obviously, there were no hands-on and in-person activities for a while. At the same time, remote communication technologies became more widespread than ever. Necessity made people learn how to use and be comfortable with online learning and remote working.
Utilising the power of online, now we can reach much wider audiences with our public engagement events. There can be easy access, no matter how far you are, as long as you have internet. And as we go back to normal, we can combine both and use the positive sides of different approaches.
For example, during the pandemic I ran a simple online workshop for kids, explaining the principles of locomotion while making a simple ramp-walking toy using kits that we posted to them in advance. This activity goes well in person, but is also suited to be done remotely for those who cannot join for whatever reason.
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