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 Lopez

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

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 ( ΔΣ 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 <0.001mm2, the smallest obtained to this date for a neural AFE, and consumes <3 μW from a 0.8-V supply. It achieves an input-referred noise of 11.3 μVrms in the action potential band (300 Hz – 10 kHz) and 10 μVrms in the local field potential band (1 Hz – 300 Hz).
Original languageUndefined/Unknown
Pages (from-to)804-808
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Issue number3
Early online date9 Sept 2021
Publication statusPublished - 1 Mar 2022

Keywords / Materials (for Non-textual outputs)

  • AC-coupling
  • ADC
  • AFE
  • Small area
  • direct data conversion
  • event driven
  • incremental
  • low power
  • multi-channel neural recording
  • reconstruction
  • reset alignment

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