Toward energy efficient neural interfaces.
This letter presents progress toward an energy efficient neural data acquisition transponder for brain-computer interfaces. The transponder utilizes a four-channel time-multiplexed analog front-end and an energy efficient short-range backscattering RF link to transmit digitized wireless data. In addition, a low-complexity autonomous and adaptive digital neural signal processor is proposed to minimize wireless bandwidth and overall power dissipation.
Peng
Chung-Ching
CC
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL 32611, USA.
Xiao
Zhiming
Z
Bashirullah
Rizwan
R
D000200:Action Potentials / Q000502:physiology*; D000703:Analog-Digital Conversion; D003143:Communication Devices for People with Disabilities; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation*; D013686:Telemetry / Q000295:instrumentation*