Measuring and Interpreting Real-World Human Data: Insights from Brain Injury Research
Speaker: Dr. Lyndia Wu
Assistant Professor, UBC Mechanical Engineering, Sensing in Biomechanical Processes Lab
When: October 29, 2024 | 12-1 pm
Location: CEME 1203 (6250 Applied Science Lane), or on Zoom (https://ubc.zoom.us/j/62730824202?pwd=OUz7dghPMfxJw8A34BzF5WfbjbYKwi.1 | Meeting ID: 627 3082 4202 | Passcode: 528348)
The Department Research Seminar series shares our faculty expertise on a variety of topics with the UBC community.
Abstract:
For decades, injury biomechanics researchers have sought to establish a concussion risk curve—a model that predicts concussion risk based on biomechanical metrics. Such a curve would guide the design of helmets, improve car safety mechanisms, and enable objective, data-driven injury screening. However, unlike many other challenges in biomechanics, well-controlled laboratory experiments cannot provide the necessary human injury data to develop and validate this curve. Since the early 2000s, the emergence of wearable sensors equipped with inertial measurement units enabled the collection of real-world, six-degree-of-freedom head kinematics during potentially injurious impacts. But are we any closer to identifying the concussion risk curve? In this talk, I will highlight our work in optimizing wearable sensing of sports head impacts, share real-world injury and ‘non-injury’ data, and discuss how our findings are shaping an updated view of the injury risk curve. Our research tackles unique technical challenges in real-world data collection, including rare event detection, noisy kinematic measurements, and missing data. Additionally, we work towards increasing diversity in injury biomechanics data by targeting underrepresented sports populations, as well as tackling the complexities of the human brain by fusing multidomain data. Beyond concussion biomechanics, our work has broader implications for real-world sensor data collection and analyses across various fields. The development of noise-aware methodologies is essential for transforming complex, real-world data into actionable insights that can drive advancements in safety, healthcare, and beyond.
Biography:
Dr. Lyndia Wu is an Assistant Professor in Mechanical Engineering since August 2018. She is a recipient of the prestigious Michael Smith Health Research BC Scholar Award. Dr. Wu’s research focuses on the development and application of wearable sensing technologies and advanced data analytics to address significant health challenges, including concussion and sleep disorders. Her multidisciplinary collaborations spanning computational brain modeling, neuroimaging, sports medicine, and sleep medicine enable her team to generate both fundamental scientific insights and clinically translatable solutions. Dr. Wu completed her undergraduate studies in Engineering Science at the University of Toronto, majoring in Biomedical Engineering. She pursued her PhD studies in Bioengineering at Stanford University, and completed a postdoctoral fellowship in Electrical Engineering at Stanford University.