Detection of <12 µVRMS Extracellular Action Potential and Local Field Potential by Optimum Design of a Single Pixel Electrolyte-Oxide-MOSFET Interface in CMOS 28 nm

David Tomasella; Elia Vallicelli; Andrea Baschirotto; Marcello De Matteis

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Paper

Detection of <12 µVRMS Extracellular Action Potential and Local Field Potential by Optimum Design of a Single Pixel Electrolyte-Oxide-MOSFET Interface in CMOS 28 nm

Topics: Bioelectronics; Biomaterials; Biomedical Equipment & Instrumentation; Biomedical Sensors; Biosensors; Implantable Electronics

In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 1: BIOSTEC, 66-76, 2021

Authors: David Tomasella ; Elia Vallicelli ; Andrea Baschirotto and Marcello De Matteis

Affiliation: Department of Physics, University of Milano Bicocca, Piazza della Scienza 3, Milano, Italy

Keyword(s): Biological Neural Networks, Biosensors, Neural Engineering, Analog Integrated Circuits, Low-Noise Amplifier.

Abstract: Microelectrode-Arrays (MEAs) allow monitoring thousands of neurons/mm2 by sensing: extracellular Action Potentials and (in-vivo) Local Field Potentials. MEAs arrange several recording sites (or pixels) in a spatial grid, planarly and capacitively coupled with in-vitro cell cultures and/or integrated in electrocorticography grids. This paper focuses on Electrolyte-Oxide MOS Field-Effect-Transistors (EOMOSFET) MEAs for cell-level recording and presents a complete model of the neuron-electronics junction that reduces to a single electrical scheme all the biological (the neuron) and physical layers (the electrolyte, the Diffuse/Helmoltz capacitances, the oxide and the MOS transistor) composing the interface. This allows to predict the noise power coming from biological environment (electrolyte bath) and to optimize all electrical parameters with the main aim to minimize the final sensing Noise Figure and thus enhance the acquisition Signal-to-Noise-Ratio. Frequency domain simulations fro m the proposed model demonstrates that there is an optimum design point for all parameters involved in the building EOMOSFET pixel that allows to perform >9 dB Signal-to-Noise-Ratio at <12 µVRMS extracellular neuro-potentials power at the electrode node. This will finally enable high-resolution recording of ultra-weak neuro-potentials signals flowing by the electrolyte cleft that have not been never explored adopting planar capacitive coupling interfaces. (More)

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Paper citation in several formats:

Tomasella, D.; Vallicelli, E.; Baschirotto, A. and De Matteis, M. (2021). Detection of <12 µVRMS Extracellular Action Potential and Local Field Potential by Optimum Design of a Single Pixel Electrolyte-Oxide-MOSFET Interface in CMOS 28 nm. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES; ISBN 978-989-758-490-9; ISSN 2184-4305, SciTePress, pages 66-76. DOI: 10.5220/0010346300002865

@conference{biodevices21,
author={David Tomasella. and Elia Vallicelli. and Andrea Baschirotto. and Marcello {De Matteis}.},
title={Detection of <12 µVRMS Extracellular Action Potential and Local Field Potential by Optimum Design of a Single Pixel Electrolyte-Oxide-MOSFET Interface in CMOS 28 nm},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES},
year={2021},
pages={66-76},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010346300002865},
isbn={978-989-758-490-9},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - BIODEVICES
TI - Detection of <12 µVRMS Extracellular Action Potential and Local Field Potential by Optimum Design of a Single Pixel Electrolyte-Oxide-MOSFET Interface in CMOS 28 nm
SN - 978-989-758-490-9
IS - 2184-4305
AU - Tomasella, D.
AU - Vallicelli, E.
AU - Baschirotto, A.
AU - De Matteis, M.
PY - 2021
SP - 66
EP - 76
DO - 10.5220/0010346300002865
PB - SciTePress