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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Roadmap for Electrical Impedance Spectroscopy for Sensing: A Tutorial

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Author(s):
Buscaglia, Lorenzo A. [1] ; Oliveira, Osvaldo N. [1] ; Carmo, Joao Paulo [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Inst Phys, Dept Phys & Mat Sci, Bernhard Gross Polymers Grp, BR-13560970 Sao Carlos - Brazil
[2] Univ Sao Paulo, Sao Carlos Sch Engn, Dept Elect Engn, BR-13560970 Sao Carlos - Brazil
Total Affiliations: 2
Document type: Journal article
Source: IEEE SENSORS JOURNAL; v. 21, n. 20, p. 22246-22257, OCT 15 2021.
Web of Science Citations: 1
Abstract

Electrical impedance spectroscopy has been used extensively for sensing and biosensing due to the multiple electrical properties that can be interrogated through varying the frequency of the electrical excitation. In this paper, we review the basic concepts and key issues for applying impedance spectroscopy in sensing and biosensing, with emphasis on the development of precise, low-cost and portable instruments. An impedance spectroscopy system can be divided into three parts: the signal processing unit, the sensing unit and the data analysis unit. Herein, we focus on the signal processing unit, responsible for generating the excitation signal and performing the impedance readout. Special attention is given to small and low-cost signal processing circuits, which are essential for portability and point-of-care diagnosis. We also elaborate upon the various methods to fabricate the sensing units, including the choice of nanomaterials and biomolecules in controlled molecular architectures. From an instrumentation perspective, we discuss possible sources of interference in the measurement protocols. When impedance spectroscopy measurements are performed with arrays of sensing units, as with electronic tongues, large amounts of data are generated. This has motivated an increasing use of statistical and computational methods for data analysis. We present some of these methods, with examples of information visualization and machine learning techniques, which have been employed in analyzing impedance spectroscopy data in recent years. (AU)

FAPESP's process: 19/00101-8 - Development of a portable impedance analyzer
Grantee:Lorenzo Antonio Buscaglia
Support Opportunities: Scholarships in Brazil - Master
FAPESP's process: 18/22214-6 - Towards a convergence of technologies: from sensing and biosensing to information visualization and machine learning for data analysis in clinical diagnosis
Grantee:Osvaldo Novais de Oliveira Junior
Support Opportunities: Research Projects - Thematic Grants