Low-power integrated circuit for a wireless 100-electrode neural recording system

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Publication Type Journal Article
School or College College of Engineering
Department Electrical & Computer Engineering
Creator Harrison, Reid R.;Normann, Richard A.
Other Author Watkins, Paul; Kier, Ryan; Lovejoy, Robert; Black, Daniel; Solzbacher, Florian
Title Low-power integrated circuit for a wireless 100-electrode neural recording system
Date 2006-01-01
Description In the past decade, neuroscientists and clinicians have begun to use implantable MEMS multielectrode arrays (e.g., [1]) to observe the simultaneous activity of many neurons in the brain. By observing the action potentials, or "spikes," of many neurons in a localized region of the brain it is possible to gather enough information to predict hand trajectories in real time during reaching tasks [2]. Recent experiments have shown that it is possible to develop neuroprosthetic devices - machines controlled directly by thoughts - if the activity of multiple neurons can be observed.
Type Text
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Journal Title Digest of Technical Papers
First Page 554
Last Page 555
Subject Electrode; Multielectrode arrays (MEA); Neural recording; Low-power circuits; Wireless
Subject LCSH Integrated circuits; Microelectrodes; Implants, Artificial; Implants, Artificial -- Power supply; Biotelemetry; Metal oxide semiconductors
Dissertation Institution University of Utah
Language eng
Bibliographic Citation Harrison, R. R., Watkins, P., Kier, R., Lovejoy, R., Black, D., Normann, R., & Solzbacher, F. (2006). Low-power integrated circuit for a wireless 100-electrode neural recording system. IEEE International Solid-State Circuits Conference (ISSCC 2006) Digest of Technical Papers, 554-5.
Rights Management (c) 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Format Medium application/pdf
Format Extent 780,906 bytes
Identifier ir-main,14007
ARK ark:/87278/s69601mv
Setname ir_uspace
ID 702275
Reference URL https://collections.lib.utah.edu/ark:/87278/s69601mv
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