Abstract:

Mild traumatic brain injury (mTBI) affects 45 million people worldwide each year and can lead to neurodegenerative tauopathys such as Alzheimer’s and Chronic Traumatic Encephalopathy. My goal is to enable early detection and prevention of mTBI.  My laboratory has pioneered instrumented mouthguard technologies that precisely measure the acceleration of the head during impact, which we use to drive finite element (FE) models of the brain and calculate injury location and severity. In this talk, I will describe the instrumented mouthguard technology development and validation, as well as initial clinical results of FE computed brain strain compared to novel highly sensitive neuroimaging data. This preliminary data suggests that blood brain barrier disruption, a potential initiator of neurodegeneration, may be very common in contact sports and is detectable in real-time with the mouthguard.  Finally, I will present data on early prototypes of an optimal shock absorber that has the potential to prevent mTBI in helmets for football and other high-risk activities. 

Bio:

David B. Camarillo is Assistant Professor of Bioengineering, (by courtesy) Mechanical Engineering and Neurosurgery at Stanford University. Dr. Camarillo holds a B.S.E in Mechanical and Aerospace Engineering from Princeton University, a Ph.D. in Mechanical Engineering from Stanford University and completed postdoctoral fellowships in Biophysics at the UCSF and Biodesign Innovation at Stanford. Dr. Camarillo worked in the surgical robotics industry at Intuitive Surgical and Hansen Medical, before launching his laboratory at Stanford in 2012. His current research focuses on precision human measurement for multiple clinical and physiological areas including the brain, heart, lungs, and reproductive system. Dr. Camarillo has been awarded the Hellman Fellowship, the Office of Naval Research Young Investigator Program award, among other honors including multiple best paper awards in brain injury and robotic surgery. His research has been funded by the NIH, NSF, DoD, as well as corporations and private philanthropy. His lab’s research has been featured on NPR, the New York Times, The Washington Post, Science News, ESPN, and TED.com as well as other media outlets aimed at education of the public.

Abstract:

The tight description of many physical phenomena relies on mathematical models in which variables that depend simultaneously on space and time are related each other through differential relationships. This leads to systems modeled via partial differential equations (PDEs). Systems modeled via PDEs are omnipresent in physical sciences and this has a dramatic impact on the relevance of PDE models in engineering applications.

In this talk, we will consider a special class of hyperbolic PDEs, i.e., the class of 1-D linear hyperbolic conservation laws. The main interest in linear hyperbolic conservation laws is that such equations are ubiquitous in physical applications. Transport of electrical energy, the flow of fluids in open channels, the motion of chemicals in flow reactors; just to mention some, are typical examples of processes that can be mathematically described by 1-D linear conservation laws.

The main focus of this talk is on boundary feedback control design for 1-D linear hyperbolic conservation laws. Sufficient conditions in the form of Lyapunov-like functional inequalities are given to certify the existence of a bound on the $\mathcal{L}_2$ (spatial) norm of the state with respect to energy bounded measurement noise. Semidefinite programming techniques are adopted to devise a systematic design algorithm. The effectiveness of the approach is shown in a numerical example.  

Bio:

Francesco Ferrante is an assistant professor of Automatic Control (maître de conférences) at the University of Grenoble Alpes and member of the Grenoble Images Speech Signal and Control Laboratory.

He received in 2010 a “Laurea degree” (BSc) in Control Engineering from University “Sapienza” in Rome, Italy and in 2012 a “Laurea Magistrale” degree (MSc) cum laude in Control Engineering from University “Tor Vergata” in Rome, Italy. During 2014, he held a visiting scholar position at the Department of Computer Engineering, University of California Santa Cruz. In 2015, he received a PhD degree in control theory from “Institut supérieur de l'aéronautique et de l’espace” (SUPAERO) Toulouse, France. From November 2015 to August 2016, he was a postdoctoral fellow at the Department of Electrical and Computer Engineering, Clemson University. From August 2015 to September 2016, he held a position as postdoctoral scientist at the Hybrid Systems Laboratory (HSL) at the University of California at Santa Cruz.

His research interests are in the general area of systems and control with a special focus on hybrid systems, observer design, application of convex optimization in systems and control.