Electrochemical impedance spectroscopy for characterizing neural electrodes

Electrochemical impedance spectroscopy (EIS) has been extensively employed in the field of neural stimulation over the past 25 years. This review summarizes the early applications, major contributions, rudimentary use, and recent advances of EIS in neural applications. EIS is widely used in both research and clinical neurostimulation to monitor changes in electrode impedance due to foreign body response and glial encapsulation. The key parameters for in vitro and in vivo measurements are discussed along with the guidelines for data interpretation.

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Publication Details

Journal
Current Opinion in Electrochemistry
Published
2026-01-03
DOI
https://doi.org/10.1016/j.coelec.2025.101807
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00
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article

Electrochemical impedance spectroscopy for characterizing neural electrodes

Stuart F. Cogan, Bernard Wiafe Biney, Mark E. Orazem, Cynthia C. Eluagu et al.
Current Opinion in Electrochemistry
Neuroscience and Neural Engineering
article

Electrochemical impedance spectroscopy for characterizing neural electrodes

Stuart F. Cogan, Bernard Wiafe Biney, Mark E. Orazem, Cynthia C. Eluagu, Kevin J. Otto
article en

Abstract

Electrochemical impedance spectroscopy (EIS) has been extensively employed in the field of neural stimulation over the past 25 years. This review summarizes the early applications, major contributions, rudimentary use, and recent advances of EIS in neural applications. EIS is widely used in both research and clinical neurostimulation to monitor changes in electrode impedance due to foreign body response and glial encapsulation. The key parameters for in vitro and in vivo measurements are discussed along with the guidelines for data interpretation.

Current Opinion in ElectrochemistryVol. 56
The University of Texas at Dallas (US), Purdue University West Lafayette (US), University of Florida (US)
Openalex Percentile: Top 97%
Neuroscience and Neural Engineering
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