'Institute of Electrical and Electronics Engineers (IEEE)'
Doi
Abstract
This paper presents work on ultra-low-power circuits for brain–machine interfaces with applications for paralysis prosthetics, stroke, Parkinson’s disease, epilepsy, prosthetics for the blind, and experimental neuroscience systems. The circuits include a micropower neural amplifier with adaptive power biasing for use
in multi-electrode arrays; an analog linear decoding and learning
architecture for data compression; low-power radio-frequency
(RF) impedance-modulation circuits for data telemetry that
minimize power consumption of implanted systems in the body;
a wireless link for efficient power transfer; mixed-signal system
integration for efficiency, robustness, and programmability; and
circuits for wireless stimulation of neurons with power-conserving
sleep modes and awake modes. Experimental results from chips
that have stimulated and recorded from neurons in the zebra
finch brain and results from RF power-link, RF data-link, electrode-
recording and electrode-stimulating systems are presented.
Simulations of analog learning circuits that have successfully
decoded prerecorded neural signals from a monkey brain are also
presented
