Brain Machine Interfaces: Concept to Clinic
Over the last two decades neural prostheses that aim to restore lost motor function have moved quickly from concept to laboratory development and clinical demonstration. In parallel, advances in neural interfacing technologies poised to broaden clinical application of these prostheses are actively in development in both academic and industry settings. In this talk, I will provide a broad overview of the technical history of these neural prostheses starting from enabling neurophysiology insights to work currently being conducted. Additionally, I will describe research within my own lab with the goal of augmenting neural prosthesis performance and expanding their potential application space. This work will highlight key enabling research collaborations in multiple clinical settings and the development of complementary animal models that accelerate development. We will take a few deep dives to describe the application of statistical signal processing, machine learning, and algorithm design to this research domain.
Access is free to subscribers of the IEEE Brain Community.
Dr. Vikash Gilja
Vikash Gilja is an associate professor in the Electrical and Computer Engineering Department and part of the Neuroscience Graduate Program at the University of California, San Diego (UCSD). He directs the Translational Neural Engineering Laboratory, which conducts experiments in multiple clinical settings and animal models to develop neural prosthetic systems. He also engages with the emerging neural prosthesis industry, previously working directly with the founding team of Neuralink Corp. and currently advising Paradromics, Inc. Prior to joining UCSD he was a research associate in the Neural Prosthetics Translational Laboratory at Stanford University, extending the BrainGate clinical trial to Stanford. He received the B.S. degree in Brain and Cognitive Sciences and the B.S./M.Eng. degrees in Electrical Engineering and Computer Science from MIT in 2003 and 2004. In 2010, he completed his Ph.D. in Computer Science at Stanford University with the thesis "Towards Clinically Viable Neural Prosthetic Systems."
Publication Year: 2020