An Artifact-Resilient Neural Recording Front-end with Rail-to-Rail DM and CM Offset Correction

Mehdi Bandali, Benjamin C. Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

We present a small area (0.006mm2) recording front-end for concurrent neural sensing and stimulation with rail-to-rail offset correction. To mitigate crosstalk from volt-level neural stimulation, the low-noise front-end uses an IΣΔ ADC topology with memoryless, charge-based sampling. The front-end uses auto-zeroing to cancel differential and common-mode DC offsets originating from neural electrodes. Since many neural stimulation paradigms have a low-duty cycle but very large amplitudes, we introduce a coordinated timing (CO-T) scheme that dynamically resets the front-end during narrow stimulation pulses. CO-T minimizes samples lost due to stimulation artifacts and enables high-fidelity neural signal reconstruction. We im-plemented the circuit in a 180nm CMOS process and measured a noise density of 74.88nV/√Hz at a sample rate of 15.56kHz and power consumption of 16.95 μW We demonstrate effective cancellation of 1.7Vpp stimulation artifacts and differential and common-mode DC offsets up to 1.2V. To the best of our knowledge, this is the first spike-rate recording system with instant stimulation artifact recovery.

Original languageEnglish
Title of host publicationISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665451093
DOIs
StatePublished - 2023
Event56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 - Monterey, United States
Duration: 21 May 202325 May 2023

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2023-May
ISSN (Print)0271-4310

Conference

Conference56th IEEE International Symposium on Circuits and Systems, ISCAS 2023
Country/TerritoryUnited States
CityMonterey
Period21/05/2325/05/23

Keywords

  • Closed-loop Neuromodulation
  • Electrode Offset
  • Memo-ryless Sampling
  • Neural Recording
  • Stimulation Artifact

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