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

doi:10.1109/ISSCC.2018.8310301

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 proceeding › Conference contribution

34 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 language	English (US)
Title of host publication	2018 IEEE International Solid-State Circuits Conference, ISSCC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	296-298
Number of pages	3
ISBN (Electronic)	9781509049394
DOIs	https://doi.org/10.1109/ISSCC.2018.8310301
State	Published - Mar 8 2018
Event	65th IEEE International Solid-State Circuits Conference, ISSCC 2018 - San Francisco, United States Duration: Feb 11 2018 → Feb 15 2018

Publication series

Name	Digest of Technical Papers - IEEE International Solid-State Circuits Conference
Volume	61
ISSN (Print)	0193-6530

Other

Other	65th IEEE International Solid-State Circuits Conference, ISSCC 2018
Country/Territory	United States
City	San Francisco
Period	2/11/18 → 2/15/18

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

Access to Document

10.1109/ISSCC.2018.8310301

Cite this

O'Leary, G., Pazhouhandeh, M. R., Chang, M., Groppe, D., Valiante, T. A., Verma, N., & Genov, R. (2018). A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ² Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. In 2018 IEEE International Solid-State Circuits Conference, ISSCC 2018 (pp. 296-298). (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; Vol. 61). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSCC.2018.8310301

O'Leary, Gerard ; Pazhouhandeh, M. Reza ; Chang, Michael et al. / A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ² Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. 2018 IEEE International Solid-State Circuits Conference, ISSCC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 296-298 (Digest of Technical Papers - IEEE International Solid-State Circuits Conference).

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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.",

author = "Gerard O'Leary and Pazhouhandeh, {M. Reza} and Michael Chang and David Groppe and Valiante, {Taufik A.} and Naveen Verma and Roman Genov",

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O'Leary, G, Pazhouhandeh, MR, Chang, M, Groppe, D, Valiante, TA, Verma, N & Genov, R 2018, A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ² Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. in 2018 IEEE International Solid-State Circuits Conference, ISSCC 2018. Digest of Technical Papers - IEEE International Solid-State Circuits Conference, vol. 61, Institute of Electrical and Electronics Engineers Inc., pp. 296-298, 65th IEEE International Solid-State Circuits Conference, ISSCC 2018, San Francisco, United States, 2/11/18. https://doi.org/10.1109/ISSCC.2018.8310301

A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ² Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. / O'Leary, Gerard; Pazhouhandeh, M. Reza; Chang, Michael et al.
2018 IEEE International Solid-State Circuits Conference, ISSCC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 296-298 (Digest of Technical Papers - IEEE International Solid-State Circuits Conference; Vol. 61).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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O'Leary G, Pazhouhandeh MR, Chang M, Groppe D, Valiante TA, Verma N et al. A recursive-memory brain-state classifier with 32-channel track-and-zoom Δ² Σ ADCs and Charge-Balanced Programmable Waveform Neurostimulators. In 2018 IEEE International Solid-State Circuits Conference, ISSCC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 296-298. (Digest of Technical Papers - IEEE International Solid-State Circuits Conference). doi: 10.1109/ISSCC.2018.8310301