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An introduction to the memristor – a valuable circuit element in bioelectricity and bioimpedance


The memristor (short for memory resistor) is a yet quite unknown circuit element, though equally fundamental as resistors, capacitors, and coils. It was predicted from theory arguments nearly 40 years ago, but not realized as a physical component until recently. The memristor shows many interesting features when describing electrical phenomena, especially at small (molecular or cellular) scales and can in particular be useful for bioimpedance and bioelectricity modeling. It can also give us a richer and much improved conceptual understanding of many such phenomena. Up until today the tools available for circuit modeling have been restricted to the three circuit elements (RLC) as well as the widely used constant phase element (CPE). However, as one element has been missing in our modeling toolbox, many bioelectrical phenomena may have been described incompletely as they are indeed memristive. Such memristive behavior is not possible to capture within a traditional RLC framework. In this paper we will introduce the memristor and look at bioelectrical memristive phenomena. The goal is to explain the new memristor’s properties in a simple manner as well as to highlight its importance and relevance. We conclude that memristors must be included as a readily used building block for bioimpedance and bioelectrical data analysis and modeling.

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Modelling the Ability of Rheoencephalography to Measure Cerebral Blood Flow

. Despite this fact, the method is frequently referred to as unreliable and controversial because the measurements are ambiguous with a high risk of clinical misinterpretation [ 1 ]. The most controversial characteristic of REG is its ability to evaluate correctly the CBF from the surface electrodes through the anatomical structures of the human head. The argument is that a weak alternating electrical current, which is used for the impedance measurements, is shunted by the scalp with its low electrical conductivity, and can not reach the brain [ 2 ]. Another delicate

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Frequency dependent rectifier memristor bridge used as a programmable synaptic membrane voltage generator

}}+\varepsilon \right\}}\,.$$ whereas k denotes the order of the iterative steps. In the case of the memristor bridge circuit, x ( t ) is the normalized extent of the space-charge region. The iteration is performed without considering the window function. The window function suppresses changes of the state equation within the marginal area of the memristor. Therefore the window function uses an argument of the same iteration step. This leads to a recursive mathematical expression and shows one weakness of the Picard Iteration. The aim is to perform the iteration

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Modeling and Simulation of Equivalent Circuits in Description of Biological Systems - A Fractional Calculus Approach

the form of a Nyquist plot (lines with circles), the plot obtained from the solution of the circuit of Fig. 7 ( line with +), and the plot obtained by applying the definition of fractional calculus (line with *). Nyquist diagrams are sensitive to changes in the spectra of similar samples but even in this representation we can see that the measurements on the same type of cell (erythrocytes) present a similar behavior: semi-circles with a diameter of around 150 kΩ. The description of the spectra for both leukocytes and plasma leads to a similar argument about the

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Magnetic induction pneumography: a planar coil system for continuous monitoring of lung function via contactless measurements

for a complete magnetic induction tomography system that the artifacts due to breathing usually spoil the images [ 6 ]. However, for the patient in a supine position, the chest motion due to respiration is assumed to take place only on the ventral surface and the dorsal movement artifacts are expected to be minimal for this position. This argument has been explored here and the artifacts due to breathing is found to be not as severe as in the complete tomography system. However, rotational and transversal displacements of the patient during data acquisition still

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The current-voltage relation of a pore and its asymptotic behavior in a Nernst-Planck model

physical meaning, the energy barrier height, w , and the relative size of the entrance region of the pore, r . This is an important advantage for fitting and interpreting experimental data. The low voltage domain of linear current shown by this model has not yet experimentally explored, despite the fact that it offers direct information about the energy barrier inside a membrane's pore. Additionally, the high voltage domain of linearity validates the values for w and r , when it is accessible. For all these arguments, we believe this simple model for the current

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Probing for stomach using the Focused Impedance Method (FIM)

sensitivity there. The logic for choosing a smaller separation for I 1 -V 1 compared to I 1 ’-V 1 ’ in TPIM1 is that one may expect a higher sensitivity near to I 1 -V 1 (around the stomach) compared to that near I 1 ’-V 1 ’ as mentioned before. The same arguments hold for the electrode separations in TPIM2. Fig 4 Cross sectional view showing the initial suggested positions of electrodes for the trunk and the embedded stomach model. The dashed straight lines represent the maximum current lines driven between the respective electrodes. The above logic

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Marking 100 years since Rudolf Höber’s discovery of the insulating envelope surrounding cells and of the β-dispersion exhibited by tissue

from 11 experiments was that the internal conductivity of red blood cells was equivalent to a 0.18% NaCl solution (minimum 0.11%, maximum 0.3%). He noted that this represented about 1/3 to 2/3 of that of the conductivity of blood serum or of Ringer’s solution. He reviewed the argument made by others that the reason why blood corpuscles, like many other cells, contain salts in other concentrations to those of their surroundings results from some of them being bound to organic components within the cell. He argues that the experiments he has presented provide proof

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Dielectrical properties of living epidermis and dermis in the frequency range from 1 kHz to 1 MHz

.00±0.13 20 15 - 76 US 20MHz B scanner [25] 1.02±0.21 17 16 - 50 Biopsy [26] 0.85±0.11 5 26 - 74 US 22 MHz B scanner [27] Mathematical Model We consider conservation of charge—ohmic and displacement currents—in the electrodes of the EIS probe and two layers—living epidermis and dermis—in the stripped skin as illustrated schematically in Fig. 1b and summarized in Appendix A. We further employ scaling arguments [ 10 ] to reduce the living epidermis and electrodes to boundary conditions, as illustrated in Fig. 1c , which yields a

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Transient bioimpedance monitoring of mechanotransduction in artificial tissue during indentation

the electrodes, the effective geometry can be found using a Schwartz-Christoffel transformation. The effective resistance due to the surrounding air is [ 34 , 35 ]: (19) R a i r = ρ a i r L K k h s K k ′ h s $${{R}_{air}}=\frac{{{\rho }_{air}}}{L}\frac{K\left( {{k}_{hs}} \right)}{K\left( {{{{k}'}}_{hs}} \right)}$$ where K(k) is the complete elliptical integral of the first kind with argument k and L is the length of the electrodes. Similarly, if there are any conduction paths below the sensor, the effective resistance of the substrate, which

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