Low power implantable neural recording front-end

Low power smart electronic designs for neural recording applications have recently become a major research topic in circuits and system society. Challenged by the complicated nature of the biology-electronic interface, implantable neural recording circuits must offer high quality signal acquisition...

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Main Authors: Do, Anh Tuan, Tan, Yung Sern, Lam, Chun Kit, Je, Minkyu, Yeo, Kiat Seng
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/100230
http://hdl.handle.net/10220/13599
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1002302020-03-07T13:24:49Z Low power implantable neural recording front-end Do, Anh Tuan Tan, Yung Sern Lam, Chun Kit Je, Minkyu Yeo, Kiat Seng School of Electrical and Electronic Engineering International SoC Design Conference (2012 : Jeju, Korea) DRNTU::Engineering::Electrical and electronic engineering Low power smart electronic designs for neural recording applications have recently become a major research topic in circuits and system society. Challenged by the complicated nature of the biology-electronic interface, implantable neural recording circuits must offer high quality signal acquisition while consuming as little power as possible. Furthermore, many applications demand on-chip smart features to maximize energy efficiency as well as to assist the subsequent software-based digital signal processing. This paper reviews the recent advancements in the field, followed by a proposed ultra low-power recording front-end. The proposed design consists of an adjustable gain and bandwidth low-noise amplifier, a bandpass filter, a unity gain buffer and a 9-bit ADC. When simulated using a 0.18 μm/1 V CMOS process, the whole channel consumes only 2.76 μW. 2013-09-23T07:38:41Z 2019-12-06T20:18:57Z 2013-09-23T07:38:41Z 2019-12-06T20:18:57Z 2012 2012 Conference Paper Do, A. T., Tan, Y. S., Lam, C. K., Je, M., & Yeo, K. S. (2012). Low power implantable neural recording front-end. 2012 International SoC Design Conference (ISOCC 2012). https://hdl.handle.net/10356/100230 http://hdl.handle.net/10220/13599 10.1109/ISOCC.2012.6407122 en
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Do, Anh Tuan
Tan, Yung Sern
Lam, Chun Kit
Je, Minkyu
Yeo, Kiat Seng
Low power implantable neural recording front-end
description Low power smart electronic designs for neural recording applications have recently become a major research topic in circuits and system society. Challenged by the complicated nature of the biology-electronic interface, implantable neural recording circuits must offer high quality signal acquisition while consuming as little power as possible. Furthermore, many applications demand on-chip smart features to maximize energy efficiency as well as to assist the subsequent software-based digital signal processing. This paper reviews the recent advancements in the field, followed by a proposed ultra low-power recording front-end. The proposed design consists of an adjustable gain and bandwidth low-noise amplifier, a bandpass filter, a unity gain buffer and a 9-bit ADC. When simulated using a 0.18 μm/1 V CMOS process, the whole channel consumes only 2.76 μW.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Do, Anh Tuan
Tan, Yung Sern
Lam, Chun Kit
Je, Minkyu
Yeo, Kiat Seng
format Conference or Workshop Item
author Do, Anh Tuan
Tan, Yung Sern
Lam, Chun Kit
Je, Minkyu
Yeo, Kiat Seng
author_sort Do, Anh Tuan
title Low power implantable neural recording front-end
title_short Low power implantable neural recording front-end
title_full Low power implantable neural recording front-end
title_fullStr Low power implantable neural recording front-end
title_full_unstemmed Low power implantable neural recording front-end
title_sort low power implantable neural recording front-end
publishDate 2013
url https://hdl.handle.net/10356/100230
http://hdl.handle.net/10220/13599
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