Using digital twin to explore walking ability post-spinal cord injury

Hi Minh Truong. Could you tell us about your licentiate thesis?

My thesis explores walking ability post-spinal cord injury. Such Injuries usually disrupt brain-body connections, impairing sensorimotor functions. However, the impacts of the injury vary greatly among persons affected. My first study clustered the walking patterns among those having incomplete injury. This analysis then told me which body movements best separate the clusters from people without injuries. My second study related factors such as strength, aids, and cardiovascular fitness to how far and easily people with spinal cord injury could walk. Both studies used explainable AI techniques to extract insights from machine learning models. I expect this technique to offer additional perspectives complementing standard assessments.

Link to thesis

What benefits and contributions to health, healthcare, and people with motor disability could your research add to?

I believe the findings from my thesis have some potential to advance rehabilitation programs for people with motor disabilities. By gaining deeper insights into walking patterns and how various factors impact functional ability, This could be a first step toward facilitating personalized treatment approaches tailored to each individual's distinct capacities and circumstances.

Could you tell us a bit about your background?

I obtained a Bachelor's in Automation and Control Engineering from Ho Chi Minh City University of Technology in 2017, graduating as the university’s valedictorian. My thesis involved building and controlling a remote-controlled submarine that could dive 1.5m for 30 min. From 2018-2020, I studied for a master’s at Tohoku University in Japan as a MEXT scholar. My thesis focused on real-time estimations of knee and ankle angles and torques based on features extracted from electromyography, EMG, signals. From 2020-2021, I was a visiting researcher at Chalmers University. I was a project leader in developing an open-source platform for EMG-based rehabilitation of sensorimotor impairments. I was also responsible for firmware and software work on a device providing multi-modal sensations to promote motor/sensory improvements for amputees experiencing Phantom Limb Pain. I also assisted the technical team in the firmware and hardware development of the powered arm prosthesis in their participation in CYBATHLON 2020.

When do you plan to defend your PhD thesis and the next step after that?

In my previous research, I was unable to fully explain the causes underlying changes in movement. For the second half of my PhD, I'm taking a different simulation-based approach called predictive modeling. The idea is to digitally recreate each person I study as an animated virtual model based on their body measurements. I can then manipulate these virtual individuals to predict how their walking might change under different conditions. This technique then allows me to test causal factors in a way that wasn't possible with just machine learning alone. Ultimately, I hope to bridge the gap between model-based simulation and model-free machine learning in biomechanics. I am open to any future opportunities, whether in academia or industry, to pursue that goal.

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