Containing errors in computations for neural sensing: does a hierarchical-referencing strategy lead to energy savings?

Matthew Boring, Shawn Kelly, Jeffrey Weldon, Michael Tarr, Amanda Robinson, Marlene Behrmann, Pulkit Grover

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

1 Citation (Scopus)

Abstract

Recent experimental evidence and theoretical results challenge the belief that ultra high-density EEG sensing will not yield higher spatial resolutions. It raises the exciting possibility that source-localization accuracy can be improved substantially with ultra high-density systems; however, these systems are hindered by implementation constraints in circuit volume and energy consumption. Recently, an information-theoretic hierarchical referencing mechanism has been proposed to exploit the decay of high-spatial frequencies during volume conduction from source to scalp - and the induced high local spatial correlations - to reduce the required circuit power and volume. In this paper, human EEG data is used to experimentally test and validate theoretical inter-electrode correlations and bit savings when employing a hierarchical referencing strategy. Extrapolating from electrodes that are at least 2 cm apart, we observe that on average savings can exceed 3 bits per electrode at inter-electrode distances of 3 mm.

Original languageEnglish
Title of host publicationITA 2016
Subtitle of host publication2016 Information Theory and Applications Workshop
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages5
ISBN (Electronic)9781509025299
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event2016 Information Theory and Applications Workshop, ITA 2016 - La Jolla, United States
Duration: 31 Jan 20165 Feb 2016

Conference

Conference2016 Information Theory and Applications Workshop, ITA 2016
CountryUnited States
CityLa Jolla
Period31/01/165/02/16

Keywords

  • EEG
  • design and implementation of sensing systems
  • biopotentials
  • quantization
  • energy savings

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