Sensors for Sports Injury and Performance
We welcome you to join us in-person and on Zoom for our November Seminar hosted jointly with Wu Tsai Human Performance Alliance & eWEAR.
Date: Monday, November 7th from 12:30 pm to 1:30 pm PDT
Location: Stanford University (Y2E2 Building, Room 299) & on Zoom
Lunch will be provided at 12:00pm for in-person attendees & a chance to talk with the speakers after the seminar.
Registration: Please click here to register
Safety Protocol: For visitors coming to campus please review the Stanford University Covid-19 Policies. Face coverings are strongly recommended for everyone attending.
Enora Le Flao
12:30 pm to 1:00 pm
“Head impact monitoring to better understand injury risks in sports: challenges and opportunities”
1:00 pm to 1:30 pm
“Single-digit micron 3D Continuous Liquid Interface Production (CLIP) for lattice-based capacitive pressure sensor”
Enora Le Flao
Postdoctoral Scholar, Bioengineering, Stanford University
Enora has been involved in sports injury prevention research since the undergraduate level. After obtaining a Master in mechanical engineering and working with protective equipment manufacturers, she pursued a PhD focusing on head impact monitoring in sports, which allowed her to participate in solving the concussion puzzle by applying her knowledge of biomechanics. Her ambition is to make sports safer by preventing concussions from happening in the first place. She is currently a postdoc in the Camarillo Lab, working with instrumented mouthguard data and adding neuroimaging, eye-tracking, and machine learning to her toolbox.
There is growing evidence that concussions and repeated impacts to the head sustained during sports participation can lead to long-term deficits in neurocognitive and psychological health. In order to make sports safer, it is essential to understand the mechanisms of concussive injury, and how exposure to head impacts is detrimental to brain health. To answer those questions, head impact sensors were developed from the assumption that the motion of the head upon an impact could be associated with the diagnosis of injury. In this talk, Enora will present a general overview of the field of head impact monitoring, focusing on some of the challenges related to the current technology, and introduce some of the work conducted at the CamLab that will help advance our understanding of sports-related concussions.
Postdoctoral Scholar, Molecular Imaging, Stanford University
Kaiwen Hsiao a postdoctoral researcher at Stanford in the DeSimone lab. Her postdoctoral research focuses on developing high-resolution 3D CLIP printers and developing stereolithography computational models. Her research interests involve in fabricating micro-architectures for bio-oriented applications and microelectronic applications. Before she join Stanford, she worked on computational lithography as a design engineer at Intel and at Apple camera hardware. She did her PhD at University of Illinois at Urbana Champaign where she focused on understanding the intermolecular interactions of concentrated polymer solutions and ring polymers.
The ability to pattern freeform architectures in three-dimensions spanning the nanometer to meter scale is at the core of soft matter material engineering and applications. Processing of these architectures inevitably involves complex fluids exhibiting disparate behaviors across a broad range of length and time scales. The molecular properties of the fluid/material are intimately involved in determining the microstructure of the printed part via the non-equilibrium dynamics of the fluid. Thus, the flow typically can dictate a material’s macroscopic response and processing applicability. Innovations that integrate molecular interactions with scalable processing, such as additive manufacturing (AM), will accelerate the transition from current manufacturing methods to new paradigms for developing tunable, responsive, and functionally graded soft matter materials, with relevance in biomedical devices, micro-electromechanical systems (MEMS), and optoelectronic components.
While AM fabrication approaches provide unprecedented manufacturing customization and flexibility, a trade-off in print scalability and resolution still exists in most high-resolution AM technologies. Our recently developed high-resolution CLIP 3D printer overcomes these challenges with single-digit-micron features at a print speed 105 times faster than most high-resolution 3D printers1-2. Building upon a fundamental understanding of polymer physics and non-Newtonian fluid dynamics, including the co-design and optimization of projection optics, photopolymerization kinetics modeling, and software system integration, the high-resolution CLIP 3D printer has overcome the major technological challenges in scalability and print resolution2-3.
We have shown its potential in printing a broad range of various materials (including hydrogels and elastomeric materials). The capability to process and pattern elastomeric materials at the single-digit micron resolution has contributed to meeting the growing demand for specialized, high-performance wearable electronics. Specific efforts have focused on geometric micro-engineering to improve sensor performance and fabrication of low-profile 3D integration. Due to the limitations in lithography fabrication, most geometries adopted for pressure sensors are constrained to simple ridges and line structures. We demonstrate that the single-digit micron CLIP 3D printer can create elastomeric and conformable complex 3D micro-structures, representing a major step toward achieving specialized, high-performing capacitive pressure sensors. J. Lee*, K. Hsiao, G. Lipkowitz, T. Samuelsen, *J. M. DeSimone “Characterization of a 30-micron pixel size CLIP-based 3D printer and its enhancement through dynamic printing optimization”. Additive Manufacturing, 55, pp 102800 (2022)  K. Hsiao*, B. J. Lee, T. Samuelsen, G. Lipkowitz, D. Ilyn, A. Shih, M. T. Dulay, L. Tate, E. S. Shaqfeh, *Joseph M. DeSimone “Single Digit micron high-resolution CLIP”, (accepted Science Advances)  Lipkowitz, G.; Samuelsen, T.; Hsiao, K.; Lee, B.; Dulay, M. T.; Coates, I.; Lin, H.; Pan, W.; Toth, G.; Tate, L.; Shaqfeh, E. S. G.; DeSimone, J. M. Injection Continuous Liquid Interface Production of 3D Objects. Sci. Adv. 2022, 8 (39), eabq3917. https://doi.org/10.1126/sciadv.abq3917.