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High-Efficiency Integrated Bioelectronics and Unobtrusive Neural Interfaces

ECE Colloquia ECE Seminar

Location: EER 1.518
Gert Cauwenberghs
Institute for Neural Computation at University of California San Diego

The convergence of neurotechnology and adaptive machine intelligence onto low-power silicon integrated systems offers opportunities to advance the effectiveness, efficiency, affordability, and comfort of mobile brain-computer and human-machine interfaces for applications ranging from hands-free voiceless communication to continuous health monitoring and biofeedback electroceutical therapy.  I will highlight advances and current trends in the miniaturization and integration of neural interfaces with embedded active electronics operating at record levels of noise-energy efficiency providing microvolt and femtoampere sensitivity at microwatt power, with a focus on unobtrusive wearable systems for probing and controlling brain activity with minimal contact and discomfort to the body.  These include flexible in-ear sensors mounted on a user-generic earbud recording electrophysiological and electrochemical signals indicative of brain cognitive activity as well as body metabolic state for unobtrusive continuous health and wellness monitoring.  I will also discuss implications of these advances and related developments in body area networks to new and emerging applications of pervasive neural interfaces for closed-loop neurological monitoring and neurofeedback therapy.


Gert Cauwenberghs is Professor of Bioengineering and Co-Director of the Institute for Neural Computation at University of California San Diego.  Over the last 35 years, he has pioneered the engineering of silicon integrated circuits that emulate the fundamental physical principles, structural organization, and cognitive function of the computational brain.  Operating at extreme levels of energy efficiency and noise resilience, these integrated circuits have shown great use for ubiquitous deployment of engineered natural intelligence for applications ranging from human-computer interaction to wearable health monitoring.  He is a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) and the American Institute for Medical and Biological Engineering (AIMBE).

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