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Skin and Artificial Skin Models in Electrical Sensing Applications
Koosha Ehtiati1, Johannes Eiler1, Agnieszka Bochynska2
1Department of Chemistry, Technical University of Denmark, 2800 Kgs. Lyngby, Denmark.
ACS Applied Bio Materials
|August 8, 2023
Summary
This review explores how skin
Area of Science:
- Electrophysiology
- Biomaterials Science
- Skin Biophysics
Background:
- Skin electrical properties are crucial for biopotential recording using electrophysiological sensors.
- Testing sensor systems on living tissues presents challenges, necessitating the use of artificial skin models.
- Understanding the skin's electrochemical behavior is vital for developing effective sensing technologies.
Purpose of the Study:
- To systematically link skin structure to its electrochemical behavior for electrophysiological sensing.
- To review existing artificial skin models that mimic skin's electrochemical properties.
- To provide guidance for future development of artificial skin models based on comparative analysis.
Main Methods:
- Literature review focusing on skin structure, electrochemical properties, and equivalent circuit models.
- Comparative analysis of electrochemical behavior between biological skin and artificial models.
- Evaluation of theoretical models representing skin's electrical impedance.
Main Results:
- Established a clear relationship between skin's structural components and its electrochemical response.
- Identified key characteristics of artificial skin models in mimicking biological skin's impedance.
- Highlighted discrepancies and similarities between skin and artificial skin model behaviors.
Conclusions:
- A comprehensive understanding of skin's electrochemical properties is essential for designing accurate electrophysiological sensors.
- Artificial skin models offer a viable alternative for sensor evaluation, but further refinement is needed to fully replicate skin's complexity.
- Future research should focus on developing advanced artificial skin models with improved electrochemical mimicry for robust sensor testing.

