Electrical Impedance Spectroscopy for Electro-Mechanical Characterization of Conductive Fabrics

Bera, Tushar Kanti; Mohamadou, Youssoufa; Lee, Kyounghun; Wi, Hun; Oh, Tong In; Woo, Eung Je; Soleimani, Masoud; Seo, Jin Keun

doi:10.3390/s140609738

Cited by 33 publications

(16 citation statements)

References 31 publications

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“…Recently, Bera et al [4] investigated the electromechanical properties of different conductive fabrics through electrical impedance spectroscopy. Because fabrics are flexible, durable, and washable, EIT-based fabric pressure sensors should be widely applicable as, for example, wearable sensors.…”

Section: Discussionmentioning

confidence: 99%

A Pressure Distribution Imaging Technique with a Conductive Membrane using Electrical Impedance Tomography

Ammari

Kang²,

Lee

et al. 2015

SIAM J. Appl. Math.

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This paper presents a mathematical framework for a flexible pressure sensor model using electrical impedance tomography (EIT). When pressure is applied to a conductive membrane patch with clamped boundary, the pressure-induced surface deformation results in a change in the conductivity distribution. This change can be detected in the current-voltage data (i.e., EIT data) measured on the boundary of the membrane patch. Hence, the corresponding inverse problem is to reconstruct the pressure distribution from the data. Assuming that the material's conductivity distribution is constant, we derive a two-dimensional (2D) apparent conductivity (in terms of EIT data) corresponding to the surface deformation. Since the 2D apparent conductivity is found to be anisotropic, we consider a constrained inverse problem by restricting the coefficient tensor to the range of the map from pressure to the 2D apparent conductivity. This paper provides theoretical grounds for mathematically modeling the inverse problem. We develop a reconstruction algorithm based on a careful sensitivity analysis. We demonstrate the performance of the reconstruction algorithm through numerical simulations to validate its feasibility for future experimental studies. Introduction.There is a growing demand for cost-effective flexible pressure sensors. These devices have wide potential applicability, including in smart textiles [7,26,27], touch screens [18], artificial skins [35], and wearable health monitoring technologies [25,29]. Electrical measurements have recently been used to monitor the pressure-induced surface deformation of conductive membranes. In particular, electrical impedance tomography (EIT) has been used to develop flexible pressure sensors [31,37,38], because it allows the electromechanical behavior of an electrically conducting film to be monitored. When a pressure-sensitive conductive sheet is exposed to pressure, the deformation of the surface alters the conductivity distribution, which can be detected by an EIT system. However, rigorous studies employing mathematical modeling and reconstruction methods have not yet been conducted. The purpose of this paper is to provide a systematic mathematical framework for an EIT-based flexible pressure sensor.Our rigorous mathematical analysis is based on the consideration of a simple model of an EIT-based pressure sensor using a thin, flexible conductive membrane

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Section: Discussionmentioning

confidence: 99%

A Pressure Distribution Imaging Technique with a Conductive Membrane using Electrical Impedance Tomography

Ammari

Kang²,

Lee

et al. 2015

SIAM J. Appl. Math.

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“…A number of RCMs were developed with parallel and series-parallel combinations by high-precision resistors (1% tolerance) and capacitors (1% tolerance). EIS studies were conducted with a QuadTech7600 (QuadTech Inc., USA) impedance analyzer [88] using the four-probe technique [89][90][91][92][93][94]. The EIS study was conducted with circuit combinations by injecting a 1 mA constant sinusoidal current at different frequencies and the impedances and phase angles were measured at 100 discrete frequency points within a frequency band of 10 Hz to 2 MHz.…”

Section: Eis Data Collection From Real Electronic Circuits With An Immentioning

confidence: 99%

A LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) for biological tissue impedance analysis and equivalent circuit modelling

Bera

Nagaraju

Lubineau

2016

Journal of Electrical Bioimpedance

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Under an alternating electrical signal, biological tissues produce a complex electrical bioimpedance that is a function of tissue composition and applied signal frequencies. By studying the bioimpedance spectra of biological tissues over a wide range of frequencies, we can noninvasively probe the physiological properties of these tissues to detect possible pathological conditions. Electrical impedance spectroscopy (EIS) can provide the spectra that are needed to calculate impedance parameters within a wide range of frequencies. Before impedance parameters can be calculated and tissue information extracted, impedance spectra should be processed and analyzed by a dedicated software program. National Instruments (NI) Inc. offers LabVIEW, a fast, portable, robust, user-friendly platform for designing data-analyzing software. We developed a LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) to analyze the electrical impedance spectra for tissue characterization in medical, biomedical and biological applications. Here, we test, calibrate and evaluate the performance of LEBISDI on the impedance data obtained from simulation studies as well as the practical EIS experimentations conducted on electronic circuit element combinations and the biological tissue samples. We analyze the Nyquist plots obtained from the EIS measurements and compare the equivalent circuit parameters calculated by LEBISDI with the corresponding original circuit parameters to assess the accuracy of the program developed. Calibration studies show that LEBISDI not only interpreted the simulated and circuit-element data accurately, but also successfully interpreted tissues impedance data and estimated the capacitive and resistive components produced by the compositions biological cells. Finally, LEBISDI efficiently calculated and analyzed variation in bioimpedance parameters of different tissue compositions, health and temperatures. LEBISDI can also be used for human tissue impedance analysis for electrical impedance-based tissue characterization, health analysis and disease diagnosis.

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“…In recent years, electrically conductive polymer fibers have been extensively investigated due to their promising applications in a wide range of areas, such as static charge dissipation and dust‐free clothing, sensors, actuators, fiber‐based wearable electronics, energy storage, drug release, tissue engineering, and electromagnetic interference shielding …”

Section: Introductionmentioning

confidence: 99%

Fluid‐Induced Alignment of Carbon Nanofibers in Polymer Fibers

Sharifi

Hashemi

et al. 2017

Macro Materials & Eng

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Carbon nanofiber/polycaprolactone (CNF/PCL) composite fibers are fabricated using a microfluidic approach. The fibers are made with different content levels of CNFs and flow rate ratios between the core and sheath fluids. The electrical conductivity and tensile properties of these fibers are then investigated. It is found that at a CNF concentration of 3 wt%, the electrical conductivity of the composite fiber significantly increases to 1.11 S m −1 . The yield strength, Young's modulus, and ultimate strength of the 3 wt% CNF increase relative to the pure PCL by factors of 1.72, 2.88, and 1.23, respectively. Additionally, the results show that a microfluidic approach can be considered as an effective method to align CNFs along the fibers in the longitudinal direction.

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Electrical Impedance Spectroscopy for Electro-Mechanical Characterization of Conductive Fabrics

Cited by 33 publications

References 31 publications

A Pressure Distribution Imaging Technique with a Conductive Membrane using Electrical Impedance Tomography

A Pressure Distribution Imaging Technique with a Conductive Membrane using Electrical Impedance Tomography

A LabVIEW-based electrical bioimpedance spectroscopic data interpreter (LEBISDI) for biological tissue impedance analysis and equivalent circuit modelling

Fluid‐Induced Alignment of Carbon Nanofibers in Polymer Fibers

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