Data Compression versus Signal Fidelity Trade-off in Wired-OR ADC Arrays for Neural Recording

Pumiao Yan, Nishal P. Shah, Dante Muratore, Pulkit Tandon, E.J. Chichilnisky, Boris Murmann

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)
16 Downloads (Pure)

Abstract

This paper investigates the efficacy of a wired-OR compressive readout architecture for neural recording, which enables simultaneous data compression of action potential signals for high channel count electrode arrays. We consider a range of wiring configurations to assess the trade-offs between compression ratio and various task-specific signal fidelity metrics. We consider the fidelity in threshold crossing detection, spike assignment, and waveform estimation, and find that for an event SNR of 7-10 the readout captures at least 80% of the spike waveforms at ∼150x data compression.
Original languageEnglish
Title of host publicationProceedings of the 2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)
PublisherIEEE
Pages80-84
Number of pages5
ISBN (Electronic)978-1-6654-6917-3
ISBN (Print)978-1-6654-6918-0
DOIs
Publication statusPublished - 2022
Event2022 IEEE Biomedical Circuits and Systems Conference (BioCAS) - Taipei, Taiwan
Duration: 13 Oct 202215 Oct 2022

Conference

Conference2022 IEEE Biomedical Circuits and Systems Conference (BioCAS)
Country/TerritoryTaiwan
CityTaipei
Period13/10/2215/10/22

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care

Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • A/D conversion
  • brain-machine interfaces
  • compression algorithm
  • neural interfaces

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