title: Low-power circuits for brain-machine interfaces.
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.
authors.forename: Rahul
authors.initials: R
authors.lastname: Sarpeshkar
authors.forename: Woradorn
authors.initials: W
authors.lastname: Wattanapanitch
authors.forename: Scott K
authors.initials: SK
authors.lastname: Arfin
authors.forename: Benjamin I
authors.initials: BI
authors.lastname: Rapoport
authors.forename: Soumyajit
authors.initials: S
authors.lastname: Mandal
authors.forename: Michael W
authors.initials: MW
authors.lastname: Baker
authors.forename: Michale S
authors.initials: MS
authors.lastname: Fee
authors.forename: Sam
authors.initials: S
authors.lastname: Musallam
authors.forename: Richard A
authors.initials: RA
authors.lastname: Andersen