A nonlinear signal-specific ADC for efficient neural recording

Abstract

A bandwidth-efficient technique for nonlinearly converting analog neural signals into digital is presented to be used in implantable neural recording microsystems. It is shown that the choice of a proper nonlinear quantization function helps reduce the outgoing bit rate carrying the recorded neural data. Another major benefit of digitizing neural signals using a proper nonlinear analog-to-digital converter (ADC) is the improvement in the signal-to-noise ratio (SNR) of the signal. The 8-b nonlinear anti-logarithmic ADC reported in this paper digitizes large action potentials with 10b resolution, while quantizing the small background noise with a resolution of as low as 3b. The circuit was designed and simulated in a 0.18-um CMOS process. According to the experimental results, SNR of the neural signal increases from 5.11 before digitization to 22 after being digitized using the proposed ADC approach.