A Compact, Low-Power Analog Front-End With Event-Driven Input Biasing for High-Density Neural Recording in 22-nm FDSOI
Xiaohua Huang, Marco Ballini, Shiwei Wang, Beatrice Miccoli, Chris Van Hoof, Georges Gielen, Jan Craninckx, Nick Van Helleputte, Carolina Mora López
Abstract
An ultra-small-area, low-power analog front-end (AFE) for high-density neural recording is presented in this brief. It features an 11-bit incremental delta-sigma analog-to-digital converter (<inline-formula> <tex-math notation="LaTeX">$\Delta \Sigma $ </tex-math></inline-formula> ADC) enhanced with an offset-rejecting event-driven input biasing network. This network avoids saturation of the ADC input caused by leakage of the input-coupling capacitor implemented in an advanced technology node. Combining AC-coupling with direct data conversion, the proposed AFE can tolerate a rail-to-rail electrode offset and achieves a good trade-off between power, noise, bandwidth, input impedance, and area. Fabricated in a 22-nm fully-depleted silicon on insulator (FDSOI) process, the design occupies an active area of <0.001mm<sup>2</sup>, the smallest obtained to this date for a neural AFE, and consumes <inline-formula> <tex-math notation="LaTeX">$\mathbf { < }3~\mu \text{W}$ </tex-math></inline-formula> from a 0.8-V supply. It achieves an input-referred noise of <inline-formula> <tex-math notation="LaTeX">$11.3~\mu \text{V}_{\mathrm{ rms}}$ </tex-math></inline-formula> in the action potential band (300 Hz – 10 kHz) and 10 <inline-formula> <tex-math notation="LaTeX">$\mu \text{V}_{\mathrm{ rms}}$ </tex-math></inline-formula> in the local field potential band (1 Hz – 300 Hz).