CMU Neural Engineering Virtual Seminars
Seminar Title: Unobtrusive In-Ear Electrophysiology for Integrative Brain-Body Health and Wellness
Speaker: Gert Cauwenberghs, PhD, Professor of Bioengineering and Co-Director of the Institute for Neural Computation at University of California San Diego
Abstract: 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 sensitivity at microwatt power, with a focus on unobtrusive wearable systems for probing and controlling whole-brain neural activity with minimal contact and discomfort to the body. The human ear in particular harbors a rich variety of biosignals indicative of brain cognitive activity as well as body metabolic state for unobtrusive continuous health and wellness monitoring. These biosignals include electroencephalography (EEG) and electrodermal activity (EDA) directly accessible through non-invasive electrophysiological sensing on the skin surface inside the ear canal, through dry electrodes screen-printed onto a flexible substrate mounted on a user-generic earbud. Furthermore, the relative proximity of the ear canal to brain stem and auditory cortex allows for auditory EEG closed-loop neurofeedback to provide powerful and potentially far-reaching new therapeutic advances in the active remediation of debilitating neurological disorders, such as tinnitus for which currently no effective treatment is available.
About the Speaker: Dr. 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).