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A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording

A time-domain analog spatial compressed sensing encoder for neural recording applications is proposed. Owing to the advantage of MEMS technologies, the number of channels on a silicon neural probe array has doubled in 7.4 years, and therefore, a greater number of recording channels and higher densit...

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Detalles Bibliográficos
Autores principales: Okazawa, Takayuki, Akita, Ippei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795473/
https://www.ncbi.nlm.nih.gov/pubmed/29324675
http://dx.doi.org/10.3390/s18010184
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author Okazawa, Takayuki
Akita, Ippei
author_facet Okazawa, Takayuki
Akita, Ippei
author_sort Okazawa, Takayuki
collection PubMed
description A time-domain analog spatial compressed sensing encoder for neural recording applications is proposed. Owing to the advantage of MEMS technologies, the number of channels on a silicon neural probe array has doubled in 7.4 years, and therefore, a greater number of recording channels and higher density of front-end circuitry is required. Since neural signals such as action potential (AP) have wider signal bandwidth than that of an image sensor, a data compression technique is essentially required for arrayed neural recording systems. In this paper, compressed sensing (CS) is employed for data reduction, and a novel time-domain analog CS encoder is proposed. A simpler and lower power circuit than conventional analog or digital CS encoders can be realized by using the proposed CS encoder. A prototype of the proposed encoder was fabricated in a 180 nm 1P6M CMOS process, and it achieved an active area of 0.0342 [Formula: see text] and an energy efficiency of 25.0 [Formula: see text]
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spelling pubmed-57954732018-02-13 A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording Okazawa, Takayuki Akita, Ippei Sensors (Basel) Article A time-domain analog spatial compressed sensing encoder for neural recording applications is proposed. Owing to the advantage of MEMS technologies, the number of channels on a silicon neural probe array has doubled in 7.4 years, and therefore, a greater number of recording channels and higher density of front-end circuitry is required. Since neural signals such as action potential (AP) have wider signal bandwidth than that of an image sensor, a data compression technique is essentially required for arrayed neural recording systems. In this paper, compressed sensing (CS) is employed for data reduction, and a novel time-domain analog CS encoder is proposed. A simpler and lower power circuit than conventional analog or digital CS encoders can be realized by using the proposed CS encoder. A prototype of the proposed encoder was fabricated in a 180 nm 1P6M CMOS process, and it achieved an active area of 0.0342 [Formula: see text] and an energy efficiency of 25.0 [Formula: see text] MDPI 2018-01-11 /pmc/articles/PMC5795473/ /pubmed/29324675 http://dx.doi.org/10.3390/s18010184 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Okazawa, Takayuki
Akita, Ippei
A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title_full A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title_fullStr A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title_full_unstemmed A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title_short A Time-Domain Analog Spatial Compressed Sensing Encoder for Multi-Channel Neural Recording
title_sort time-domain analog spatial compressed sensing encoder for multi-channel neural recording
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5795473/
https://www.ncbi.nlm.nih.gov/pubmed/29324675
http://dx.doi.org/10.3390/s18010184
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