A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ2 Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators

Gerard O'Leary, M. Reza Pazhouhandeh, Michael Chang, David Groppe, Taufik A. Valiante, Naveen Verma, Roman Genov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

The advancement of closed-loop neuromodulation for treating neurological disorders demands: (1) analog circuits monitoring the brain activity uninterruptedly even during neurostimulation, (2) energy-efficient high-efficacy processors for responsive, adaptive, personalized neurostimulation, and (3) safe neurostimulation paradigms with rich spatio-temporal stimuli for controlling the brain's complex dynamics. This paper presents an implantable neural interface processor (NURIP) that addresses these requirements - it performs brain state classification for reliable seizure prediction and contingent seizure abortion.

Original languageEnglish (US)
Title of host publication2018 IEEE International Solid-State Circuits Conference, ISSCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages296-298
Number of pages3
ISBN (Electronic)9781509049394
DOIs
StatePublished - Mar 8 2018
Event65th IEEE International Solid-State Circuits Conference, ISSCC 2018 - San Francisco, United States
Duration: Feb 11 2018Feb 15 2018

Publication series

NameDigest of Technical Papers - IEEE International Solid-State Circuits Conference
Volume61
ISSN (Print)0193-6530

Other

Other65th IEEE International Solid-State Circuits Conference, ISSCC 2018
CountryUnited States
CitySan Francisco
Period2/11/182/15/18

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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