“…Many equivalent circuit models have been proposed for the skin tissue complex impedance [31][32][33]. Among those, we have selected the simplified Cole model [31] to implement in an ASIC form.…”
Section: The Skin Modelmentioning
confidence: 99%
“…Many equivalent circuit models have been proposed for the skin tissue complex impedance [31][32][33]. Among those, we have selected the simplified Cole model [31] to implement in an ASIC form. This is because the Cole model captures tissue behavior with electrodes placed in relatively short distance (usually 2-4 centimeters), and, within a wide frequency range (e.g., 1 Hz-10 kHz) covering multiple bio-signal types.…”
Section: The Skin Modelmentioning
confidence: 99%
“…where R ∞,s is the contact (gap) resistor and such that z skin (∞) = R ∞,s , R o,s is the low frequency resistor, i.e., z skin (0) = R o,s , a s is the fractional CPE order and C s is the pseudo-capacitance of the CPE. The skin Cole model is shown in the left side of Figure 2, where the CPE's complex impedance is defined as [31][32][33]…”
Section: The Skin Modelmentioning
confidence: 99%
“…Finally, a useful characteristic of the Cole model is its time constant τ s defined as For a frequency range of 1 Hz to 10 kHz, typical upper-arm Cole skin model parameters are shown in Table 1, [31]. Table 2 indicates the range of R o,s , a s , and C s of the Cole skin model for a variety of human body tissues [31][32][33].…”
Section: The Skin Modelmentioning
confidence: 99%
“…Finally, a useful characteristic of the Cole model is its time constant τ s defined as For a frequency range of 1 Hz to 10 kHz, typical upper-arm Cole skin model parameters are shown in Table 1, [31]. Table 2 indicates the range of R o,s , a s , and C s of the Cole skin model for a variety of human body tissues [31][32][33]. As mentioned, the presented models and parameters target the frequency range 1 Hz and 10 kHz covering HR, PPT, BR, neuroimaging, and skin impedance measurement applications [4,35].…”
This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite.
“…Many equivalent circuit models have been proposed for the skin tissue complex impedance [31][32][33]. Among those, we have selected the simplified Cole model [31] to implement in an ASIC form.…”
Section: The Skin Modelmentioning
confidence: 99%
“…Many equivalent circuit models have been proposed for the skin tissue complex impedance [31][32][33]. Among those, we have selected the simplified Cole model [31] to implement in an ASIC form. This is because the Cole model captures tissue behavior with electrodes placed in relatively short distance (usually 2-4 centimeters), and, within a wide frequency range (e.g., 1 Hz-10 kHz) covering multiple bio-signal types.…”
Section: The Skin Modelmentioning
confidence: 99%
“…where R ∞,s is the contact (gap) resistor and such that z skin (∞) = R ∞,s , R o,s is the low frequency resistor, i.e., z skin (0) = R o,s , a s is the fractional CPE order and C s is the pseudo-capacitance of the CPE. The skin Cole model is shown in the left side of Figure 2, where the CPE's complex impedance is defined as [31][32][33]…”
Section: The Skin Modelmentioning
confidence: 99%
“…Finally, a useful characteristic of the Cole model is its time constant τ s defined as For a frequency range of 1 Hz to 10 kHz, typical upper-arm Cole skin model parameters are shown in Table 1, [31]. Table 2 indicates the range of R o,s , a s , and C s of the Cole skin model for a variety of human body tissues [31][32][33].…”
Section: The Skin Modelmentioning
confidence: 99%
“…Finally, a useful characteristic of the Cole model is its time constant τ s defined as For a frequency range of 1 Hz to 10 kHz, typical upper-arm Cole skin model parameters are shown in Table 1, [31]. Table 2 indicates the range of R o,s , a s , and C s of the Cole skin model for a variety of human body tissues [31][32][33]. As mentioned, the presented models and parameters target the frequency range 1 Hz and 10 kHz covering HR, PPT, BR, neuroimaging, and skin impedance measurement applications [4,35].…”
This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite.
We evaluated the elasticity of live tissues of zebrafish embryos using label‐free optical elastography. We employed a pair of custom‐built elastic microcantilevers to gently compress a zebrafish embryo and used optical‐tracking analysis to obtain the induced internal strain. We then built a finite element method (FEM) model and matched the strain with the optical analysis. The elastic moduli were found by minimizing the root‐mean‐square errors between the optical and FEM analyses. We evaluated the average elastic moduli of a developing somite, the overlying ectoderm, and the underlying yolk of seven zebrafish embryos during the early somitogenesis stages. The estimation results showed that the average elastic modulus of the somite increased from 150 to 700 Pa between 4‐ and 8‐somite stages, while those of the ectoderm and the yolk stayed between 100 and 200 Pa, and they did not show significant changes. The result matches well with the developmental process of somitogenesis reported in the literature. This is among the first attempts to quantify spatially‐resolved elasticity of embryonic tissues from optical elastography.
In this paper, a numerical method is presented to obtain and analyze the behavior of numerical solutions of distributed order fractional differential equations of the general form in the time domain with the Caputo fractional derivative. The suggested method is based on the Müntz-Legendre wavelet approximation. We derive a new operational vector for the Riemann-Liouville fractional integral of the Müntz-Legendre wavelets by using the Laplace transform method. Applying this operational vector and collocation method in our approach, the problem can be reduced to a system of linear and nonlinear algebraic equations. The arising system can be solved by the Newton method. Discussion on the error bound and convergence analysis for the proposed method is presented. Finally, seven test problems are considered to compare our results with other well-known methods used for solving these problems. The results in the tabulated tables highlighted that the proposed method is an efficient mathematical tool for analyzing distributed order fractional differential equations of the general form.
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