UC Berkeley’s Rikky Muller (Ph.D.’13 EECS), associate professor of electrical engineering and computer sciences, can still recall her first glimpse into the world of neurotechnology. At a conference nearly two decades ago, she saw something that didn’t seem possible: chips recording neural signals from the brain, then using those signals to control robotic arms.
“I think my head just exploded. I couldn’t even believe it,” she said. “Very quickly, I realized its potential to treat neurological disease — and the impact it could have on patients.”
Today, she continues to embrace that passion through her work at the Muller Lab, a research group focused on developing low-power, wireless microelectronic and integrated systems for neurological applications.
It’s work she’s eager to share — and recently, she spoke with Berkeley Engineering about her newest projects and their potential to transform the way we manage many common health conditions.
What major challenges do you face designing these types of devices?
My group develops translational medical devices to monitor, diagnose and treat neurological disorders. We build complete end-to-end systems that interact with the brain and peripheral nervous systems, combining sensors, integrated circuits, wireless technology and machine learning. As a hardware group, we’re tasked with making devices that are minimally invasive, ultra-low power and safe to implant in or wear on the body.
One challenge that we’re focusing on right now is making devices that are more intelligent and individualized. There’s a huge degree of variability between people, both in terms of the signals that we record and in terms of the responses to therapy — such as neurostimulation or drug delivery — so we really want to close the loop. We want to build devices that can make continuous observations, that extract biomarkers of aberrant states and that can autonomously determine the best therapy for a patient. Hopefully, that’s going to lead to better outcomes, faster timeframes and lower costs.
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