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A compact, low-power analog front-end with event-driven input biasing for high-density neural recording in 22-nm FDSOI

A compact, low-power analog front-end with event-driven input biasing for high-density neural recording in 22-nm FDSOI
A compact, low-power analog front-end with event-driven input biasing for high-density neural recording in 22-nm FDSOI
An ultra-small-area, low-power analog front-end (AFE) for high-density neural recording is presented in this paper. It features an 11-bit incremental delta-sigma analog-to-digital converter (σ 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 <0.001 mm2, 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).
1549-7747
Huang, Xiaohua
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Ballini, Marco
5ce563dd-6818-4688-b799-1df93ccf5df1
Wang, Shiwei
97433cb6-7752-4c68-89f8-933f233d8642
Micoli, Beatrice
c392d3b8-4cb7-4c79-aec3-5f6c499efdcd
Van Hoof, Chris
b0815a8d-91b8-4c1f-851c-6b71f5852ff7
Gielen, Georges
120dcd96-661f-46ce-a4b9-c31148befd31
Craninckx, Jan
93e0b054-bda0-4643-9849-f5df62d68af0
Van Helleputte, Nick
bad8e4b6-6d24-440f-97c3-e1ddeda371f1
Lopez, Carolina Mora
b7db9e25-fd8b-4d0e-8e91-2e201640a1eb
Huang, Xiaohua
2f291c9b-56b8-403f-b1e9-0d83a0f020ec
Ballini, Marco
5ce563dd-6818-4688-b799-1df93ccf5df1
Wang, Shiwei
97433cb6-7752-4c68-89f8-933f233d8642
Micoli, Beatrice
c392d3b8-4cb7-4c79-aec3-5f6c499efdcd
Van Hoof, Chris
b0815a8d-91b8-4c1f-851c-6b71f5852ff7
Gielen, Georges
120dcd96-661f-46ce-a4b9-c31148befd31
Craninckx, Jan
93e0b054-bda0-4643-9849-f5df62d68af0
Van Helleputte, Nick
bad8e4b6-6d24-440f-97c3-e1ddeda371f1
Lopez, Carolina Mora
b7db9e25-fd8b-4d0e-8e91-2e201640a1eb

Huang, Xiaohua, Ballini, Marco, Wang, Shiwei, Micoli, Beatrice, Van Hoof, Chris, Gielen, Georges, Craninckx, Jan, Van Helleputte, Nick and Lopez, Carolina Mora (2021) A compact, low-power analog front-end with event-driven input biasing for high-density neural recording in 22-nm FDSOI. IEEE Transactions on Circuits and Systems II: Express Briefs. (doi:10.1109/TCSII.2021.3111257).

Record type: Article

Abstract

An ultra-small-area, low-power analog front-end (AFE) for high-density neural recording is presented in this paper. It features an 11-bit incremental delta-sigma analog-to-digital converter (σ 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 <0.001 mm2, 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).

Text
A_Compact_Low-Power_Analog_Front-End_with_Event-Driven_Input_Biasing_for_High-Density_Neural_Recording_in_22-nm_FDSOI - Accepted Manuscript
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More information

Accepted/In Press date: 29 August 2021
e-pub ahead of print date: 9 September 2021

Identifiers

Local EPrints ID: 451603
URI: http://eprints.soton.ac.uk/id/eprint/451603
ISSN: 1549-7747
PURE UUID: ec58ac91-e530-499c-8bad-0240bf2e55f4
ORCID for Shiwei Wang: ORCID iD orcid.org/0000-0002-5450-2108

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Date deposited: 13 Oct 2021 16:31
Last modified: 14 Oct 2021 02:02

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Contributors

Author: Xiaohua Huang
Author: Marco Ballini
Author: Shiwei Wang ORCID iD
Author: Beatrice Micoli
Author: Chris Van Hoof
Author: Georges Gielen
Author: Jan Craninckx
Author: Nick Van Helleputte
Author: Carolina Mora Lopez

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