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Noise Power Minimization in CMOS Brain-Chip Interfaces

This paper presents specific noise minimization strategies to be adopted in silicon–cell interfaces. For this objective, a complete and general model for the analog processing of the signal coming from cell–silicon junctions is presented. This model will then be described at the level of the single...

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Autores principales: Stevenazzi, Lorenzo, Baschirotto, Andrea, Zanotto, Giorgio, Vallicelli, Elia Arturo, De Matteis, Marcello
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869152/
https://www.ncbi.nlm.nih.gov/pubmed/35200396
http://dx.doi.org/10.3390/bioengineering9020042
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author Stevenazzi, Lorenzo
Baschirotto, Andrea
Zanotto, Giorgio
Vallicelli, Elia Arturo
De Matteis, Marcello
author_facet Stevenazzi, Lorenzo
Baschirotto, Andrea
Zanotto, Giorgio
Vallicelli, Elia Arturo
De Matteis, Marcello
author_sort Stevenazzi, Lorenzo
collection PubMed
description This paper presents specific noise minimization strategies to be adopted in silicon–cell interfaces. For this objective, a complete and general model for the analog processing of the signal coming from cell–silicon junctions is presented. This model will then be described at the level of the single stages and of the fundamental parameters that characterize them (bandwidth, gain and noise). Thanks to a few design equations, it will therefore be possible to simulate the behavior of a time-division multiplexed acquisition channel, including the most relevant parameters for signal processing, such as amplification (or power of the analog signal) and noise. This model has the undoubted advantage of being particularly simple to simulate and implement, while maintaining high accuracy in estimating the signal quality (i.e., the signal-to-noise ratio, SNR). Thanks to the simulation results of the model, it will be possible to set an optimal operating point for the front-end to minimize the artifacts introduced by the time-division multiplexing (TDM) scheme and to maximize the SNR at the a-to-d converter input. The proposed results provide an SNR of 12 dB at 10 µV(RMS) of noise power and 50 µV(RMS) of signal power (both evaluated at input of the analog front-end, AFE). This is particularly relevant for cell–silicon junctions because it demonstrates that it is possible to detect weak extracellular events (of the order of few µV(RMS)) without necessarily increasing the total amplification of the front-end (and, therefore, as a first approximation, the dissipated electrical power), while adopting a specific gain distribution through the acquisition chain.
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spelling pubmed-88691522022-02-25 Noise Power Minimization in CMOS Brain-Chip Interfaces Stevenazzi, Lorenzo Baschirotto, Andrea Zanotto, Giorgio Vallicelli, Elia Arturo De Matteis, Marcello Bioengineering (Basel) Article This paper presents specific noise minimization strategies to be adopted in silicon–cell interfaces. For this objective, a complete and general model for the analog processing of the signal coming from cell–silicon junctions is presented. This model will then be described at the level of the single stages and of the fundamental parameters that characterize them (bandwidth, gain and noise). Thanks to a few design equations, it will therefore be possible to simulate the behavior of a time-division multiplexed acquisition channel, including the most relevant parameters for signal processing, such as amplification (or power of the analog signal) and noise. This model has the undoubted advantage of being particularly simple to simulate and implement, while maintaining high accuracy in estimating the signal quality (i.e., the signal-to-noise ratio, SNR). Thanks to the simulation results of the model, it will be possible to set an optimal operating point for the front-end to minimize the artifacts introduced by the time-division multiplexing (TDM) scheme and to maximize the SNR at the a-to-d converter input. The proposed results provide an SNR of 12 dB at 10 µV(RMS) of noise power and 50 µV(RMS) of signal power (both evaluated at input of the analog front-end, AFE). This is particularly relevant for cell–silicon junctions because it demonstrates that it is possible to detect weak extracellular events (of the order of few µV(RMS)) without necessarily increasing the total amplification of the front-end (and, therefore, as a first approximation, the dissipated electrical power), while adopting a specific gain distribution through the acquisition chain. MDPI 2022-01-18 /pmc/articles/PMC8869152/ /pubmed/35200396 http://dx.doi.org/10.3390/bioengineering9020042 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Stevenazzi, Lorenzo
Baschirotto, Andrea
Zanotto, Giorgio
Vallicelli, Elia Arturo
De Matteis, Marcello
Noise Power Minimization in CMOS Brain-Chip Interfaces
title Noise Power Minimization in CMOS Brain-Chip Interfaces
title_full Noise Power Minimization in CMOS Brain-Chip Interfaces
title_fullStr Noise Power Minimization in CMOS Brain-Chip Interfaces
title_full_unstemmed Noise Power Minimization in CMOS Brain-Chip Interfaces
title_short Noise Power Minimization in CMOS Brain-Chip Interfaces
title_sort noise power minimization in cmos brain-chip interfaces
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8869152/
https://www.ncbi.nlm.nih.gov/pubmed/35200396
http://dx.doi.org/10.3390/bioengineering9020042
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