Development and Characterization of PEDOT:PSS/Alginate Soft Microelectrodes for Application in Neuroprosthetics
Reducing the mechanical mismatch between the stiffness of a neural implant and the softness of the neural tissue is still an open challenge in neuroprosthetics. The emergence of conductive hydrogels in the last few years has considerably widened the spectrum of possibilities to tackle this issue. Ne...
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Published in: | Frontiers in neuroscience Vol. 12; p. 648 |
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Main Authors: | , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Switzerland
Frontiers Research Foundation
19-09-2018
Frontiers Media S.A |
Subjects: | |
Online Access: | Get full text |
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Summary: | Reducing the mechanical mismatch between the stiffness of a neural implant and the softness of the neural tissue is still an open challenge in neuroprosthetics. The emergence of conductive hydrogels in the last few years has considerably widened the spectrum of possibilities to tackle this issue. Nevertheless, despite the advancements in this field, further improvements in the fabrication of conductive hydrogel-based electrodes are still required. In this work, we report the fabrication of a conductive hydrogel-based microelectrode array for neural recording using a hybrid material composed of poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate), and alginate. The mechanical properties of the conductive hydrogel have been investigated using imaging techniques, while the electrode arrays have been electrochemically characterized at each fabrication step, and successfully validated both
and
. The presence of the conductive hydrogel, selectively electrodeposited onto the platinum microelectrodes, allowed achieving superior electrochemical characteristics, leading to a lower electrical noise during recordings. These findings represent an advancement in the design of soft conductive electrodes for neuroprosthetic applications. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This article was submitted to Neural Technology, a section of the journal Frontiers in Neuroscience Edited by: Jeffrey R. Capadona, Case Western Reserve University, United States Reviewed by: David Martin, University of Delaware, United States; Jit Muthuswamy, Arizona State University, United States |
ISSN: | 1662-4548 1662-453X 1662-453X |
DOI: | 10.3389/fnins.2018.00648 |