Fast Sub-Hz potentiostatic/galvanostatic bio-impedance measurements using chaotic oscillators.

The measurement of bio-impedance spectra at ultra low frequencies (sub-Hz) is known to require a considerably long time with the classical frequency-sweep method or other narrow-band periodic excitation signals. In this work, an impedance measurement technique based on using wide-band chaotic signals is proposed and experimentally validated over the frequency range [Formula: see text]. The technique was tested in both potentiostatic and galvanostatic modes, first using commercial components and then using an enhanced Howland current pump designed and fabricated in a 65nm CMOS technology. The accuracy of the proposed technique was assessed on fruit samples compared to measurements conducted using a research-grade Biologic VSP-300 electro-chemical station.

Extending the double-dispersion Cole-Cole, Cole-Davidson and Havriliak-Negami electrochemical impedance spectroscopy models.

Double-dispersion impedance models are important for the accurate fitting of spectral impedance measurements in Electrical Impedance Spectroscopy (EIS). While the Cole-Cole model is the most widely known, it is possible to define double-dispersion Cole-Davidson and Havriliak-Negami models as well. In this work, we show that more freedom can be exercised when these three models are combined together and that this combination can be done in various forms. Experimental results using a two-stage optimization algorithm applied on the suggested models are provided.

Extraction of bioimpedance phase information from its magnitude using a non-uniform Kramers-Kronig transform.

A novel non-uniform Kramers-Kronig Transform algorithm for bioimpedance phase extraction is proposed and tested in this work. The algorithm error is studied and compared with a previously proposed phase extraction technique, also based on the Kramers-Kronig transform. Results using simulated datasets and experimental datasets confirm the excellent performance of the algorithm.

Corrigendum: Reevaluation of Performance of Electric Double-layer Capacitors from Constant-current Charge/Discharge and Cyclic Voltammetry.

This corrects the article DOI: 10.1038/srep38568.

Reevaluation of Performance of Electric Double-layer Capacitors from Constant-current Charge/Discharge and Cyclic Voltammetry.

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 RsC behavior in spite of the nonlinear response of the device, which in turn provides inaccurate values for its characteristic metrics [corrected]. 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 Rs 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 (Rs, 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 RsC model. We validate our formulae with the experimental measurements of different EDLCs.

Extracting the parameters of the double-dispersion Cole bioimpedance model from magnitude response measurements.

In the field of bioimpedance measurements, the Cole impedance model is widely used for characterizing biological tissues and biochemical materials. In this work, a nonlinear least squares fitting is applied to extract the double-dispersion Cole impedance parameters from simulated magnitude response datasets without requiring the direct impedance data or phase information. The technique is applied to extract the impedance parameters from MATLAB simulated noisy magnitude datasets showing less than 1.2 % relative error when 60 dB SNR Gaussian white noise is present. This extraction is verified experimentally using apples as the Cole impedances showing less than 3 % relative error between simulated responses (using the extracted impedance parameters) and the experimental results over the entire dataset.