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64 results for “impedance measurement”
In Silico Local Electrical Impedance Measurements in the Atria
<div>This document describes a dataset provided in the context of the manuscript “In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human” [1].</div> <div> </div> <div>Authors: Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dössel O, Luik A</div> <div> </div> <div>The dataset contains in silico simulation setups and results from forward electrical impedance simulations with EIDORS. Geometrical models include the commercially available ablation catheters IntellaNav MiFi and IntellaNav StPt catheter measuring local impedance (LI). </div> <div>Catheter geometries were embedded in different surrounding conditions of clinical importance. Catheter tissue interaction with and without scar, the insertion of the catheter into a pulmonary vein (PV), the withdrawal into a transeptal sheath, and catheter irrigation were modeled to quantify the respective effect on LI measurements. In vitro and clinical data used for validation purposes are included in the dataset as well.</div> <div> </div> <div>Abbreviations: </div> <div>LI: local impedance, all numbers are given in Ohms</div> <div>MiFi: IntellaNav MiFi catheter</div> <div>PV: pulmonary vein</div> <div>StPt: IntellaNav StPt catheter</div> <div> </div> <div> </div> <div>Simulation results, in vitro measurements and clinically measured traces are provided in the following MATLAB files in the subdirectory „results_LI“:</div> <div> </div> <div>• impConductivities.mat</div> <div>In vitro measurements and simulation results for MiFi and StPt in NaCl solutions of different concentrations as described in section III A of the related publication [1]. The struct "impedance" includes the following fields:</div> <div>⁃ conc: concentration of NaCl solutions from in vitro measurements in weight percentages</div> <div>⁃ cond: conductivities of the NaCl solutions from in vitro measurements in S/m</div> <div>⁃ temp: interpolated temperature curves from in vitro measurements in °C</div> <div>⁃ condSim: different conductivities of the NaCl solutions from in silicon experiments in S/m</div> <div>⁃ LI_MiFi_iV: 41x9 matrix with interpolated in vitro LI measurements with the MiFi catheter in 9 different NaCl solutions and at 41 interpolated temperature values</div> <div>⁃ LI_StPt_iV: 41x9 matrix with interpolated in vitro LI measurements with the StPt catheter in 9 different NaCl solutions and at 41 interpolated temperatures values</div> <div>⁃ LI_MiFi_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_MiFi_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro MiFi measurements</div> <div>⁃ LI_StPt_iV_RT: LI values for different NaCl solutions at room temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_StPt_iV_BT: LI values for different NaCl solutions at body temperature interpolated from in vitro StPt measurements</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different NaCl solutions</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different NaCl solutions</div> <div> </div> <div>• impSheath.mat</div> <div>Simulation results and clinical measurements of LI with MiFi and StPt for different overlaps with a transeptal sheath as described in section III B of the related publication [1]. The struct „impSheath“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and distal edge of the sheath in mm. Negative distances describe an insertion of the catheter into the sheath</div> <div>⁃ LI_MiFi_sim: LI extracted from simulations with the MiFi catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_StPt_sim: LI extracted from simulations with the StPt catheter for different vertical distances between catheter tip and distal edge of the sheath corresponding to the field distance</div> <div>⁃ LI_MiFi_cd: 281x2 matrix containing clinical LI measurements with the MiFi catheter in the second column and corresponding time steps in the first column</div> <div>⁃ LI_StPt_cd: 301x2 matrix containing clinical LI measurements with the StPt catheter in the second column and corresponding time steps in the first column</div> <div> </div> <div>• impTissue.mat</div> <div>Simulation results for MiFi and StPt with variable distance and angle between catheter and tissue as described in section III C of the related publication [1]. The struct „impTissue“ contains the following fields:</div> <div>⁃ distance: 25 different distances between catheter tip and endocardial surface in mm</div> <div>⁃ distanceSel: 5 selected distances between catheter tip and endocardial surface in mm</div> <div>⁃ angle: 13 different angles between catheter and endocardial tissue surface in degrees</div> <div>⁃ LI_MiFi_d_alpha: 5x13 matrix with simulated LI values for the MiFi catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_MiFi_d_90: 25 simulated LI values for the MiFi catheter for different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div>⁃ LI_StPt_d_alpha: 5x13 matrix with simulated LI values for the StPt catheter at 5 selected distances (distanceSel) and 13 angles between catheter and tissue.</div> <div>⁃ LI_StPt_d_90: 25 simulated LI values for the StPt catheter different distances between catheter tip and endocardial surface corresponding to the field “distance” for orthogonal catheter placement</div> <div> </div> <div>• impTissueScar.mat</div> <div>Simulation results for MiFi and StPt interacting with tissue in the presence of scar as described in section III C of the related publication [1]. The struct „impTissueScar“ contains the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and endocardial surface for all simulation setups in mm</div> <div>⁃ centerX: horizontal distance between the catheter tip and the center of the line of scar for all simulation setups in mm</div> <div>⁃ LI_MiFi3mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_StPt3mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 3mm width</div> <div>⁃ LI_MiFi6mm: simulated LI for the MiFi catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div>⁃ LI_StPt6mm: simulated LI for the StPt catheter for all combinations of horizontal and vertical distances with a central line of scar of 6mm width</div> <div> </div> <div>• impPV.mat</div> <div>Simulation results for MiFi and StPt insertion into a pulmonary vein (PV) as described in section III D of the related publication [1]. The struct „impPV“ includes the following fields:</div> <div>⁃ distance: vertical distance between catheter tip and tissue surface in mm. Negative distances describe an insertion of the catheter into the vein.</div> <div>⁃ radius: inner radius of the PV in mm</div> <div>⁃ thickness: thickness of the PV tissue in mm</div> <div>⁃ LI_MiFi_d_r_th: 31x4x4 matrix containing the LI simulation results for the MiFi catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div>⁃ LI_StPt_d_r_th: 31x4x4 matrix containing the LI simulation results for the StPt catheter for all combinations of 31 distances, 4 radii, and 4 thicknesses.</div> <div> </div> <div>• impFlush.mat</div> <div>Simulation results for MiFi and StPt flush with NaCl at different flow rates as described in section III E of the related publication [1]. The struct „impFlush“ includes the following fields:</div> <div>⁃ radius: radius of the NaCl spheres at the irrigation holes in mm</div> <div>⁃ LI_MiFi_NaCl: LI extracted from simulations with MiFi catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div>⁃ LI_StPt_NaCl: LI extracted from simulations with StPt catheter for NaCl irrigation spheres of different sizes corresponding to the respective radius</div> <div> </div> <div>Additionally, exemplary geometrical setups and results are provided as VTK files in the subdirectory „selectedGeometriesAndSimResults“:</div> <div> </div> <div>Each VTK file contains the following data fields:</div> <div>⁃ Ids (point data): integer specifying the Id of the respective vertex</div> <div>⁃ Voltage (point data): electric potential of the respective vertex with respect to a reference potential in mV</div> <div>⁃ Conductivity (cell data): conductivity of the material of the respective cell in S/mm</div> <div>⁃ Current (cell data): current density of the respective cell in nA/mm^2</div> <div>⁃ Ids (cell data): integer specifying the Id of the respective cell</div> <div>⁃ Material (cell data): integer specifying the material of the respective cell (for MiFi setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: mini electrode 1, 8: insulator mini electrode 1, 9: mini electrode 2, 10: insulator mini electrode 2, 11: mini electrode 3, 12: insulator mini electrode 3, 13: tissue, 14: blood, 15: sheath, 16:NaCl, 17: scar tissue; for StPt setups: 1: distal ring electrode, 2: middle ring electrode, 3: proximal ring electrode, 4: tip electrode, 5: outer insulator, 6: inner insulator, 7: tissue, 8: blood, 9: NaCl, 10: scar tissue)</div> <div> </div> <div>• mifi.vtk: MiFi catheter in blood </div> <div>• stpt.vtk: StPt catheter in blood</div> <div>• mifiTissue_dist000_angle0000.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 0°</div> <div>• mifiTissue_dist000_angle0450.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 45°</div> <div>• mifiTissue_dist000_angle0900.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 90°</div> <div>• mifiTissue_dist000_angle1350.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 135°</div> <div>• mifiTissue_dist000_angle1800.vtk: MiFi catheter positioned in 0mm distance to the endocardial tissue at an angle of 180°</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line3mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 3mm width</div> <div>• mifiTissueScar_dist0000_angle0900_centerX0000_line6mm.vtk: MiFi catheter positioned centrally and orthogonally at a line of scar tissue of 6mm width</div> <div>• mifi_PV_d0060_r030_th20.vtk: MiFi catheter 6mm above the endocardial surface with a PV of 3 mm radius and 2mm PV tissue thickness</div> <div>• mifi_PV_d-070_r030_th20.vtk: MiFi catheter inserted into a PV of 3 mm radius and 2mm PV tissue thickness; insertion depth = 7mm</div> <div>• mifi_flush_050-0.50.vtk: MiFi catheter within blood with NaCl spheres of 0.5mm radius at irrigation holes</div> <div>• mifi_sheath_0100.vtk: MiFi catheter within transeptal sheath extracted by 10mm</div> <div> </div> <div>[1] Unger LA, Anton CM, Stritt M, Wakili R, Haas A, Kircher M, Dossel O, Luik A. In Silico Study of Local Electrical Impedance Measurements in the Atria - Towards Understanding and Quantifying Dependencies in Human. IEEE Trans Biomed Eng. 2023 Feb;70(2):533-543. doi: 10.1109/TBME.2022.3196545. Epub 2023 Jan 19. PMID: 35925848.</div> <p> </p>
FOAM 02: Impedance tube measurements of two porous materials with diameter variation
<p>This dataset provides the data for Reference:</p> <p>[1] Alfonso Caiazzo, Florian Kraxberger, Christian Adams, Andreas Wurzinger, Jan Boysen, Giuseppe Petrone, Stefan Schoder, Sergio De Rosa, Manfred Kaltenbacher, and Christian Adams: FOAM 02: A dataset of impedance tube measurements with different materials and diameter variations. Acta Acustica 9 (50), 2025. <a href="https://doi.org/10.1051/aacus/2025033" target="_blank" rel="noopener noreferrer">https://doi.org/10.1051/aacus/2025033</a></p> <p> </p> <p>This dataset consists of three .csv files: </p> <ul> <li>alphas.csv: absorption coefficients vs. frequencies (comma-separated), 864 rows according <br>to 864 measurements </li> <li>targets.csv: one-hot encoded, i.e., binary, vectors of the parameter combinations), 864 rows <br>according to 864 measurements. The Read_Me.pdf gives further information on the one-hot <br>encoded vectors. </li> <li>diameter.csv: calliper diametric measurement in millimetres [mm]. This file contains <br>864 rows according to 864 measurements and 6 columns that, in order, represent: top <br>diameter at 0°, top diameter at 90°, bottom diameter at 0°, bottom diameter at 90°, <br>mean diameter, and standard deviation. </li> </ul> <p><br>The frequencies range from 150 Hz to 1600 Hz with resolution of 2 Hz. Note that these limits are <br>not strictly equal to the frequency limits of the impedance tube, see ISO 10534-2. </p> <p><br>The data and code are licensed under Apache License, Version 2.0 <br>https://opensource.org/licenses/Apache-2.0 </p> <p><br>Any reuse of the data must properly cite the dataset and its authors. </p> <p> </p> <p>Contact:<br>Univ.-Prof. Dr. Christian Adams<br>Graz University of Technology<br>Inffeldgasse 16c<br>8010 Graz, Austria<br>christian.adams@tugraz.at</p>
Figure 4: The estimated impedance within the measured frequency range for the symmetric (*) and the asymmetric (o) case against averaged data from healthy subjects-THE RESPIRATORY IMPEDANCE IN AN ASYMMETRIC MODEL OF THE LUNG STRUCTURE
<p>It is significant to observe that in the frequency interval of clinical interest,<br> ! 2 [25; 300] rad/s, the two impedances tend to behave similarly. For the<br> asymmetric case, we have a decrease of about -10dB/dec and a phase of ap-<br> proximately ¡50o, resulting in a fractional order of n »=</p> <p>This observation suggests that a combined efect of more than one fractal order is present in the<br> lungs and that it leads naturally to values closer to measured data in the low<br> frequency range. In other words, the symmetric tree representation does not<br> suffice to obtain a good fit between the model and the measured impedance<br> data. Another observation is that the constant-phase behavior is emphasized<br> at frequencies below those evaluated standardly in clinical practice, i.e. below<br> 5Hz. However, in the standard clinical range of frequencies for the forced oscil-<br> lation technique, namely 4-48Hz, both symmetric and asymmetric tree models<br> give similar results, as depicted in ¯gure 4</p>
Figure 4: The estimated impedance within the measured frequency range for the symmetric (*) and the asymmetric (o) case against averaged data from healthy subjects
<p>Another observation is that the constant-phase behavior is emphasized<br> at frequencies below those evaluated standardly in clinical practice, i.e. below<br> 5Hz. However, in the standard clinical range of frequencies for the forced oscil-<br> lation technique, namely 4-48Hz, both symmetric and asymmetric tree models<br> give similar results, as depicted in ¯gure 4 and ¯gure 5.</p>
Figure 5: The estimated impedance within the measured frequency range for the symmetric (*) and the asymmetric (o) case, polar plot representation.
<p>In other words, the symmetric tree representation does not<br> su±ce to obtain a good ¯t between the model and the measured impedance<br> data. Another observation is that the constant-phase behavior is emphasized<br> at frequencies below those evaluated standardly in clinical practice, i.e. below<br> 5Hz. However, in the standard clinical range of frequencies for the forced oscil-<br> lation technique, namely 4-48Hz, both symmetric and asymmetric tree models<br> give similar results, as depicted in ¯gure 4 and ¯gure 5.</p>
Data and results for manuscript: "Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurements"
<p>This package contains measured raw EIT data, electrical imaging results, spectral results from the Debye decomposition, and the Python scripts used to generate the plots in the manuscript titled:<br> <br> Imaging and functional characterization of crop root systems using spectroscopic electrical impedance measurement</p>
Assessment of the Effect of a Test Setup on the Input Impedance Measurement of Cables (Dataset)
<p>The dataset includes the source of all measured and simulated data utilized in the paper titled<i> "Assessment of the Effect of a Test Setup on the Input Impedance Measurement of Cables".</i><br>Simulation data is available in ".xlsx" format, whereas measurement data is provided in ".s1p" format. </p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset – version 2: result data]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains data from 228 commercial NMC/C+SiO lithium-ion cells aged for almost 600 days under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells.<br>This dataset is an update to the dataset previously published under the DOI 10.35097/1947 and described in the publication with the DOI 10.1038/s41597-024-03831-x. This dataset only includes result data (capacity, impedance, and pulse resistance measurements). The log data is published under the DOI 10.35097/kww7jv8ajuvchcah.</p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset – version 2: log data]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for almost 600 days under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells.<br>This dataset is an update to the dataset previously published under the DOI 10.35097/1947 and described in the publication with the DOI 10.1038/s41597-024-03831-x. This dataset only includes log data. The result data is published under the DOI 10.35097/1969.</p>
Electrical Impedance Tomography (EIT) measurement monitoring the respiratory status
<p>This dataset was used in a study titled "Structural priors represented by discrete cosine transform improve EIT functional imaging" which is currently pending publication. The dataset consists of Electrical Impedance Tomography (EIT) measurements that were collected during the monitoring of respiratory status in tested subjects. The data is stored as .get files, which can be imported into the Matlab® workspace using the codes provided on GitHub at https://github.com/rongqing-chen/DCT-EIT.</p> <p>Using the dataset requires the citation of the following publication:</p> <ul> <li>Lovas A, Chen R, Molnár T, Benyó B, Szlávecz Á, Hawchar F, et al. Differentiating Phenotypes of Coronavirus Disease-2019 Pneumonia by Electric Impedance Tomography. Frontiers in Medicine. 2022;9. doi: 10.3389/fmed.2022.747570</li> <li>R. Chen, S. Krueger-Ziolek, A. Lovas, B. Benyó, S.J. Rupitsch, K. Moeller (2023) Structural priors represented by discrete cosine transform improve EIT functional imaging. PLoS ONE 18(5): e0285619. 10.1371/journal.pone.0285619</li> </ul>
Electrical Impedance Myography as an Outcome Measure in Amyotrophic Lateral Sclerosis Clinical Trials
ClinicalTrials.gov study NCT00620698. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Measurement and modeling of the radio frequency sheath impedance in a large magnetized plasma
<p>The accompanying files contain digital data for figures in the article "Measurement and modeling of the radio frequency sheath impedance in a large magnetized plasma" by J. R. Myra, C. Lau, B. Van Compernolle, S. Vincena and J. Wright, submitted to the journal Physics of Plasmas.</p> <p><strong>Abstract</strong><br> The DC and RF properties of radio frequency (RF) driven sheaths were studied in the Large Plasma Device (LAPD) at the University of California, Los Angeles. The experiments diagnosed RF sheaths on field lines connected to a grounded plate at one end and an ion cyclotron range of frequencies (ICRF) antenna at the other end. The experimental setup permitted measurement of the RF sheath impedance at the plate as a function of DC sheath voltage, with the latter controlled by varying the RF current applied to the antenna. The DC current-voltage characteristics of these sheaths and the RF sheath impedance measurements were compared with modeling. Hot electrons, present in the LAPD plasma, were inferred to contribute significantly to both the DC and RF currents and hence the RF impedance. It was postulated that at very low power hot electrons could not access the region of the plasma subject to RF waves, resulting in an increased RF impedance. Within some experimental limitations and significant assumptions, an RF sheath impedance model was verified by the experimental data.</p>
Addendum to "Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]"
<p>This is an addendum to the previously published dataset with the title "Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]" (DOI: 10.35097/1947).<br>In the previous publication, the "cell_eisv2.zip" file was incomplete and only contained data for cells P001_1 to P044_2.<br>The fixed "cell_eisv2_fixed.zip" file of this addendum contains data for all 228 cells P001_1 to P076_3.</p>
Comprehensive battery aging dataset: capacity and impedance fade measurements of a lithium-ion NMC/C-SiO cell [dataset]
<p>Battery degradation is critical to the cost-effectiveness and usability of battery-powered products. Aging studies can help to better understand and model degradation and to optimize the operation strategy. Nevertheless, there are only a few comprehensive and freely available aging datasets for these applications.<br>To our knowledge, the dataset presented in the following is one of the largest published to date. It contains over 3 billion data points from 228 commercial NMC/C+SiO lithium-ion cells aged for more than a year under a wide range of operating conditions. We investigate calendar and cyclic aging and also apply different driving cycles to some of the cells. The dataset includes result data (such as the remaining usable capacity or impedance measured in check-ups) and raw data (i.e., measurement logs with two-second resolution).<br>The data can be used in a wide range of applications, for example, to model battery degradation, gain insight into lithium plating, optimize operation strategies, or test battery impedance or state estimation algorithms using machine learning or Kalman filtering.</p>
ESM of determination of transdermal rate of metallic microneedle array through impedance measurements-based numerical check screening algorithm
<p>Microneedle systems have been widely used in health monitoring, painless drug delivery, and medical cosmetology. Although many studies on microneedle materials, structures, and applications have been conducted, the applications of microneedles often suffered from issues of inconsistent penetration rates due to the complication of skin-microneedle interface. In this study, we demonstrated a methodology of determination of transdermal rate of metallic microneedle array through impedance measurements-based numerical check screening algorithm. Metallic sheet microneedle array sensors with different sizes were fabricated to evaluate different transdermal rates. In vitro sensing of hydrogen peroxide confirmed the effect of transdermal rate on the sensing outcomes. A FEM simulation model of a microneedle array revealed the monotonous relation between the transdermal state and test current. Accordingly, two methods were first derived to calculate the transdermal rate from the test current. First, an exact logic method provided the number of unpenetrated tips per sheet, but it required more rigorous testing results. Second, a fuzzy logic method provided an approximate transdermal rate on adjacent areas, being more applicable and robust to errors. Real-time transdermal rate estimation may be essential for improving the performance of microneedle systems, and this study provides various fundaments toward that goal.</p>
Dataset from the study: "Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames"
<p>This repository contains the scripts and other resources used in:</p> <p>“Brain Haemorrhage Detection using a SVM Classifier with Electrical Impedance Tomography Measurement Frames”, McDermott B et al. 10.1371/journal.pone.0200469</p> <p> </p> <p>>> THIS DATA IS FREE FOR USE IN ANY SCIENTIFIC RESEARCH WITH CITATION (PLEASE USE THE DOI FOR PRECISE CITATION): DOI 10.1371/journal.pone.0200469</p> <p> </p> <p>>> IF YOU USE THESE RESOURCES, CITE!!!</p> <p> </p> <p>The repository contains the code and resources to generate the EIT Measurement Frames used in Numerical Models (STL models, code to mesh, code to generate frames)</p> <p> </p> <p>Also included are the Measurement Frames generated from the Phantom Studies.</p> <p> </p> <p><strong>=> This is all the data (how to replicate it for numerical studies and the actual data for the phantom part) used in the study</strong></p> <p> </p> <p>Classifier generation, training, testing, cross validation etc uses standard MATLAB methods and resources: fitcsvm() etc.</p> <p> </p> <p>The subfolders are ordered numerically in the logical order of use</p> <p>The subfolders contain text files with more details and description relevant to the contents of the respective subfolder.</p> <p> </p> <p>Note:</p> <p> </p> <p>Software used in this study:</p> <p>At a minimum the first 2 will be needed to be installed on your computer</p> <p>(other methods etc needed are detailed within the folders)</p> <p> </p> <p><strong>MATLAB 2017B</strong> (<a href="https://uk.mathworks.com/products/matlab.html">https://uk.mathworks.com/products/matlab.html</a>):</p> <p>The primary software tool used throughout</p> <p> </p> <p><strong>EIDORS </strong>(<a href="http://eidors3d.sourceforge.net/index.shtml">http://eidors3d.sourceforge.net/index.shtml</a>)<strong>: </strong></p> <p>Open Source software package, compatible with MATLAB, with tools for use in Electrical Impedance Tomography studies.</p> <p> </p> <p><strong>Autodesk Fusion 360</strong> (<a href="https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc%7Cpcrid%7C209188650131%7Cpkw%7Cfusion%20360%7Cpmt%7Ce%7Cpdv%7Cc%7Cslid%7C%7Cpgrid%7C34851227038%7Cptaid%7Ckwd-11029869505%7C&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB">https://www.autodesk.com/products/fusion-360/overview?mktvar002=685209&mkwid=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&intent=&utm_medium=cpc&utm_source=google&utm_campaign=GGL_Fusion+360_IE_BR_SEM&utm_term=fusion%20360&utm_content=sMHGuhLcc|pcrid|209188650131|pkw|fusion%20360|pmt|e|pdv|c|slid||pgrid|34851227038|ptaid|kwd-11029869505|&gclid=Cj0KCQjw1NzZBRCoARIsAIaMwut5zqUE_d7oieOvw6H3SpU45Jw7vwL5KAKqyRYW20Be6QWE-V3HaB0aAnW0EALw_wcB</a>):</p> <p>Used to generate the head, brain and lesion STL files. These final STL files are provided in this repository.</p>
New high time resolution mutual impedance measurements
<p>=====================================================================================================<br> Author : L. Bucciantini<br> Date : 03/11/2022<br> Laboratory : CNRS-LPC2E, Orléans (France)<br> =====================================================================================================</p> <p>Dear reader, we thank you for your interest in our dataset. In this document, we describe what you will<br> find in it.</p> <p>In case you need help with using the dataset, or if you are interested in mutual impedance experiments,<br> do not hesitate to contact our team in Orléans (pierre.henri@cnrs-orleans.fr, pierre.henri@oca.eu)</p> <p>=====================================================================================================<br> Topic:<br> This dataset contains the outputs of numerical simulations and experimental tests performed<br> to test and validate two new mutual impedance instrumental modes: the chirp mode and the<br> multi-spectral mode. These modes have the objective of improving the time resolution of<br> mutual impedance measurements.</p> <p>These new instrumental modes are validated by comparing their measurements to the classic<br> instrumental mode of mutual impedance measuremetns, the so-called frequency sweep mode.</p> <p><br> Numerical model:<br> The numerical outputs are obtained from a numerical model based on the solution of the 1D-1V Vlasov-Poisson<br> system of equations. The scheme used to solve the model is the one developed<br> by Mangeney et al. (2002), A Numerical Scheme for the Integration of the Vlasov-Maxwell System of Equations. Journal of Computational Physics, (doi: https://doi.org/10.1006/jcph.2002.7071).<br> The 1D-1V Vlasov-Poisson version of this model is described in Henri, et al. (2010), Vlasov-Poisson<br> simulations of electrostatic parametric instability for localized Langmuir wave packets in the solar wind,<br> Journal of Geophysical Research (Space Physics), 115, 6106 (2010)</p> <p>Experimental testing facility:<br> The experimental outputs are obtained using the testing facility of CNRS-LPC2E space laboratory. It is<br> composed of a vacuum chamber, a pumping system and a plasma source. The pumps make vacuum in the<br> chamber (p=1e-5mbar). The plasma source generates a plasma flow that we use to test mutual impedance<br> instruments in a medium which is representative of Earth's ionosphere (100-2000 km of altitude).</p> <p>-----------------------------------------------------------------------------------------------------<br> Instrumental modes of interest</p> <p>frequency sweep (FS) mode : typical mode. Implemented for DFP-COMPLIMENT onboard Comet Interceptor</p> <p>chirp (CH) mode : new fast mode. It is based on the emission of only one period per frequency.</p> <p>multi-spectral (MS) mode : new fast mode. It is based on the simultaneous emission of multiple frequencies.</p> <p>-----------------------------------------------------------------------------------------------------<br> What is inside the dataset:</p> <p>The dataset is composed of 3 numerical and 6 experimental mutual impedance measurements.<br> The numerical measurements are obtained for the same plasma box but for different instrumental modes.<br> The experimental measurements are obtained for two different plasmas, monitored using the three different<br> instrumental modes.</p> <p>-----------------------------------------------------------------------------------------------------<br> List of directories:</p> <p><br> Numerical_CH, Numerical_MS: Each of these outputs corresponds to a mutual impedance measurement<br> Numerical_FS performed using a different instrumental mode.<br> For MS and FS, inside the directory each folder corresponds to the<br> emission of a different frequency.</p> <p><br> Experimental : It contains a txt file with inside the mutual impedance spectra obtained<br> for two different plasmas</p> <p><br> -----------------------------------------------------------------------------------------------------<br> List of folders inside the directories:</p> <p>In the case of the numerical measurements, folders begin with the name "000" and have increasing index.</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders for the numerical measurements:</p> <p>density_e.npz : electron density inside the box, in function of time (tempo)</p> <p>density_p.npz : ion density inside the box, in function of time (tempo)</p> <p>E.npz : electric field in the box, in function of time (tempo)</p> <p>qrho.npz : electric potential in the box, in function of time (tempo)</p> <p>qrho_imposed.npz : electric charge imposed at the emitting antennas, in function of time (tempo)</p> <p>tempo.npz : time-vector for density, electric field, electric potential and charge vectors</p> <p>TEST_Luca.dat : parameters describing the characteristics of the simulated plasma box</p> <p><br> [<br> Note : the previous files can be opened as follows</p> <p>import numpy as np</p> <p>vector_file_name = np.load('file_name.npz') # Use these for the .npz files<br> characteristics_of_the_box = np.genfromtxt('TEST_Luca.dat',skip_header=1)</p> <p>]</p> <p>------------------------------------------------------------------------------------------------------<br> List of files inside the folders for the experimental measurements:</p> <p>data.txt : frequencies and amplitudes associated to the measurements.</p> <p>[<br> Note : the previous file can be directly included into a python script</p> <p>]</p> <p>-------------------------------------------------------------------------------------------------------<br> Characteristics of the simulated plasma box (TEST_Luca.dat)</p> <p>nx : amount of spatial grid points</p> <p>xl : physical size of the spatial box, expressed in Debye length</p> <p>tt_w : time resolution for ion and electron density, electric field, electric potential and charge</p> <p>rap_m : ion-to-electron mass ratio</p> <p>R_p : ion-to-electron temperature ratio</p> <p>dt : time step used to evolve in time the numerical simulation</p> <p>emission : emission frequency</p> <p>power : amplitude of the electric charge imposed at the emitting antennas</p> <p><br> (Note : all parameters not listed here but present inside the TEST_Luca.dat file correspond to additional<br> functionalities of the model. For the use of this dataset, they can be discarded.)</p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p>
Synthesized Impedance Spectra Measurements of Epithelial Tissue
<p>This dataset consists of synthetic impedance measurements on modeled epithelial tissue as described in [1]. Based on previous work, physiological tissue properties were estimated for the `HT29/B6`, `IPECJ 2`, and `MDCK I` cell lines [2]. In this way, appropriate ranges of cell model parameters could be determined both for physiological control conditions and after apical addition of the substance Nystatin. For each cell line and condition, 150,000 values were randomly selected within their ranges. For each sample, a spectral impedance measurement was synthesized for 42 frequencies between 1.3 Hz and 16.35 kHz. Furthermore, the measurements were scattered to account for deviations from the theoretical impedance value due to the experimental setup. For more details see [1].</p> <p><strong>Important</strong>: You are cordially invited to use this dataset for your research or teaching purposes. For example, to compare your impedance analysis approach with ours or to develop new machine learning methods. <strong>If you use this dataset for a scientific publication, please cite [1]</strong>, where the synthesis and original application of this dataset are described in detail. If you have any questions or remarks, please do not hesitate to contact me via email (bschindler at informatik.uni-leipzig.de).</p> <p>### Changelog ###</p> <p>version 1.2 -> statistical features recalculated (for incorrect variance and median-mean) and added (pairwise differences and ratios)</p> <p>version 1.1 -> clean impedance spectra without error modeling were added.</p> <p>version 1.0 -> initial upload</p> <p>### Sources ###<br> [1] B. Schindler, D. Günzel, and T. Schmid, “Transcending Two-Path Impedance Spectroscopy with Machine Learning:<br> A Computational Study on Modeling and Quantifying Electric Bipolarity of Epithelia,“ International Journal On Advances in Life Sciences 13(1-2), 2021 <br> [2] T. Schmid, “Automatisierte Analyse von Impedanzspektren mittels konstruktivistischen maschinellen Lernens,” Ph.D. dissertation, Universität Leipzig, Germany, 2018. </p>
Optimal Frequency of Total Body Water Measurements by Bioelectrical Impedance Analysis to Prevent Intradialytic Hypotension
ClinicalTrials.gov study NCT06279156. IPD Sharing: NO. Countries: 1. Publications: 8.
Monitoring of Fluid Status in Heart Failure Patients by Intrathoracic Impedance Measurement in Japan (J-HomeCARE II)
ClinicalTrials.gov study NCT01221649. IPD Sharing: Not stated. Countries: 1. Publications: 1.
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