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The electric characteristics of electric-double layer capacitors (EDLCs) are determined by their capacitance which is usually measured in the time domain from constant-current charging/discharging and cyclic voltammetry tests, and from the frequency domain using nonlinear least-squares fitting of spectral impedance. The time-voltage and current-voltage profiles from the first two techniques are commonly treated by assuming ideal S s C behavior in spite of the nonlinear response of the device, which in turn provides inaccurate values for its characteristic metrics. In this paper we revisit the calculation of capacitance, power and energy of EDLCs from the time domain constant-current step response and linear voltage waveform, under the assumption that the device behaves as an equivalent fractional-order circuit consisting of a resistance R s in series with a constant phase element (CPE( Q, α ), with Q being a pseudocapacitance and α a dispersion coefficient). In particular, we show with the derived ( R s , Q, α )-based expressions, that the corresponding nonlinear effects in voltage-time and current-voltage can be encompassed through nonlinear terms function of the coefficient α , which is not possible with the classical R s C model. We validate our formulae with the experimental measurements of different EDLCs.

The commercial availability of integrated circuits with bioimpedance sensing functionality is advancing the opportunity for practical wearable systems that monitor the electrical impedance properties of tissues to identify physiological features in support of health-focused applications. This technical note characterizes the performance of the MAX3000x (resistance/reactance accuracy, power modes, filtering, gains) and is available for on-board processing (electrode detection) for localized bioimpedance measurements. Measurements of discrete impedances that are representative of localized tissue bioimpedance support that this IC has a relative error of <10% for the resistance component of complex impedance measurements, but can also measure relative alterations in the 250 mΩ range. The application of the MAX3000x for monitoring localized bicep tissues during activity is presented to highlight its functionality, as well as its limitations, for multi-frequency measurements. This device is a very-small-form-factor single-chip solution for measuring multi-frequency bioimpedance with significant on-board processing with potential for wearable applications.

(1) Background: One effect of microgravity on the human body is fluid redistribution due to the removal of the hydrostatic gravitational gradient. These fluid shifts are expected to be the source of severe medical risks and it is critical to advance methods to monitor them in real-time. One technique to monitor fluid shifts captures the electrical impedance of segmental tissues, but limited research is available to evaluate if fluid shifts in response to microgravity are symmetrical due to the bilateral symmetry of the body. This study aims to evaluate this fluid shift symmetry. (2) Methods: Segmental tissue resistance at 10 kHz and 100 kHz was collected at 30 min intervals from the left/right arm, leg, and trunk of 12 healthy adults over 4 h of 6° head-down-tilt body positioning. (3) Results: Statistically significant increases were observed in the segmental leg resistances, first observed at 120 min and 90 min for 10 kHz and 100 kHz measurements, respectively. Median increases were approximately 11% to 12% for the 10 kHz resistance and 9% for the 100 kHz resistance. No statistically significant changes in the segmental arm or trunk resistance. Comparing the left and right segmental leg resistance, there were no statistically significant differences in the resistance changes based on the side of the body. (4) Conclusions: The fluid shifts induced by the 6° body position resulted in similar changes in both left and right body segments (that had statistically significant changes in this work). These findings support that future wearable systems to monitor microgravity-induced fluid shifts may only require monitoring of one side of body segments (reducing the hardware needed for the system).

The article presents a synthesis method to design electrical circuit elements with fractional-order impedance, referred to as a Fractional-Order Element (FOE) or Fractor, that can be implemented by Metal–Oxide–Semiconductor (MOS) transistors. This provides an approach to realize this class of device using current integrated circuit manufacturing technologies. For this synthesis MOS transistors are treated as uniform distributed resistive-capacitive layer structures. The synthesis approach adopts a genetic algorithm to generate the MOS structures interconnections and dimensions to realize an FOE with user-defined constant input admittance phase, allowed ripple deviations, and target frequency range. A graphical user interface for the synthesis process is presented to support its wider adoption. We synthetized and present FOEs with admittance phase from 5 to 85 degrees. The design approach is validated using Cadence post-layout simulations of an FOE design with admittance phase of 74  ± 1 degrees realized using native n-channel MOS devices in TSMC 65 nm technology. Overall, the post-layout simulations demonstrate magnitude and phase errors less than 0.5% and 0.1 degrees, respectively, compared to the synthesis expected values in the frequency band from 1 kHz to 10 MHz. This supports that the design approach is appropriate for the future fabrication and validation of FOEs using this process technology.

A novel method for embedded hardware-based parameter estimation of the Cole model of bioimpedance is developed and presented. The model parameters R ∞ , R 1 and C are estimated using the derived set of equations based on measured values of real ( R ) and imaginary part ( X ) of bioimpedance, as well as the numerical approximation of the first derivative of quotient R / X with respect to angular frequency. The optimal value for parameter α is estimated using a brute force method. The estimation accuracy of the proposed method is very similar with the relevant work from the existing literature. Moreover, performance evaluation was performed using the MATLAB software installed on a laptop, as well as on the three embedded-hardware platforms (Arduino Mega2560, Raspberry Pi Pico and XIAO SAMD21). Obtained results showed that the used platforms can perform reliable bioimpedance processing with the same accuracy, while Raspberry Pi Pico is the fastest solution with the smallest energy consumption.

PurposeThe primary purpose of this study was to determine the accuracy of the standard deviation of normal-to-normal intervals (SDNN) to root mean square of successive normal-to-normal interval differences (RMSSD) ratio from 1-min recordings (SDNN:RMSSD1−min) compared to criterion recordings, as well as its relationship to low-frequency-to-high-frequency ratio (LF:HF) at rest and following maximal exercise in a group of collegiate athletes.MethodTwenty athletes participated in the study. Heart rate variability (HRV) data were measured for 5 min before and at 5–10 and 25–30 min following a maximal exercise test. From each 5-min segment, the frequency-domain measures of HF, LF, and LF:HF ratio were analyzed. Time-domain measures of SDNN, RMSSD, and SDNN:RMSSD ratio were also analyzed from each 5-min segment, as well as from randomly selected 1-min recordings.ResultThe 1-min values of SDNN, RMSSD, and SDNN:RMSSD provided no significant differences and nearly perfect intra-class correlations (ICCs ranged from 0.97 to 1.00, p < 0.001 for all) to the criterion measures from 5-min recordings. In addition, SDNN, RMSSD, and SDNN:RMSSD from the 1-min segments provided very large to nearly perfect correlations (r values ranged from 0.71 to 0.97, p < 0.001 for all) to LF, HF, and LF:HF, respectively, at each time point.ConclusionThe findings of the study suggest that ultra-shortened time-domain markers may be useful surrogates of the frequency-domain parameters for tracking changes in sympathovagal activity in athletes.

Background: Electrical impedance spectroscopy (EIS) is a fast, non-invasive, and safe approach for electrical impedance measurement of biomedical tissues. Applied to dental research, EIS has been used to detect tooth cracks and caries with higher accuracy than visual or radiographic methods. Recent studies have reported age-related differences in human dental tissue impedance and utilized fractional-order equivalent circuit model parameters to represent these measurements. Objective: We aimed to highlight that fractional-order equivalent circuit models with different topologies (but same number of components) can equally well model the electrical impedance of dental tissues. Additionally, this work presents an equivalent circuit network that can be realized using Electronic Industries Alliance (EIA) standard compliant RC component values to emulate the electrical impedance characteristics of dental tissues. Results: To validate the results, the goodness of fits of electrical impedance models were evaluated visually and statistically in terms of relative error, mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2), Nash–Sutcliffe’s efficiency (NSE), Willmott’s index of agreement (WIA), or Legates’s coefficient of efficiency (LCE). The fit accuracy of proposed recurrent electrical impedance models for data representative of different age groups teeth dentin supports that both models can represent the same impedance data near perfectly. Significance: With the continued exploration of fractional-order equivalent circuit models to represent biological tissue data, it is important to investigate which models and model parameters are most closely associated with clinically relevant markers and physiological structures of the tissues/materials being measured and not just “fit” with experimental data. This exploration highlights that two different fractional-order models can fit experimental dental tissue data equally well, which should be considered during studies aimed at investigating different topologies to represent biological tissue impedance and their interpretation.

Bioimpedance, or the electrical impedance of biological tissues, describes the passive electrical properties of these materials. To simplify bioimpedance datasets, fractional-order equivalent circuit presentations are often used, with the Cole-impedance model being one of the most widely used fractional-order circuits for this purpose. In this work, bioimpedance measurements from 10 kHz to 100 kHz were collected from participants biceps tissues immediately prior and immediately post completion of a fatiguing exercise protocol. The Cole-impedance parameters that best fit these datasets were determined using numerical optimization procedures, with relative errors of within approximately ± 0.5 % and ± 2 % for the simulated resistance and reactance compared to the experimental data. Comparison between the pre and post fatigue Cole-impedance parameters shows that the R ∞ , R 1 , and f p components exhibited statistically significant mean differences as a result of the fatigue induced changes in the study participants.

In this paper, fractional-order transfer functions to approximate the passband and stopband ripple characteristics of a second-order elliptic lowpass filter are designed and validated. The necessary coefficients for these transfer functions are determined through the application of a least squares fitting process. These fittings are applied to symmetrical and asymmetrical frequency ranges to evaluate how the selected approximated frequency band impacts the determined coefficients using this process and the transfer function magnitude characteristics. MATLAB simulations of ( 1 + α ) order lowpass magnitude responses are given as examples with fractional steps from α = 0.1 to α = 0.9 and compared to the second-order elliptic response. Further, MATLAB simulations of the ( 1 + α ) = 1.25 and 1.75 using all sets of coefficients are given as examples to highlight their differences. Finally, the fractional-order filter responses were validated using both SPICE simulations and experimental results using two operational amplifier topologies realized with approximated fractional-order capacitors for ( 1 + α ) = 1.2 and 1.8 order filters.

Three fractional-order transfer functions are analyzed for differences in realizing ( 1 + α ) order lowpass filters approximating a traditional Butterworth magnitude response. These transfer functions are realized by replacing traditional capacitors with fractional-order capacitors ( Z = 1 / s α C where 0 ≤ α ≤ 1 ) in biquadratic filter topologies. This analysis examines the differences in least squares error, stability, - 3 dB frequency, higher-order implementations, and parameter sensitivity to determine the most suitable ( 1 + α ) order transfer function for the approximated Butterworth magnitude responses. Each fractional-order transfer function for ( 1 + α ) = 1.5 is realized using a Tow–Thomas biquad a verified using SPICE simulations.