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Simulation of impedance measurements at human forearm within 1 kHz to 2 MHz

.ejcn.1601384 Pietrobelli A Nu-ez C Zingaretti G Battistini N Morini P Wang ZM Yasumura S Heymsfield SB Assessment by bioimpedance of forearm cell mass: a new approach to calibration Eur J Clin Nutr 2002 56 8 723 8 14 Ohmine Y, Morimoto T, Kinouchi Y, Iritani T, Takeuchi M, Haku M, Nishitani H. Basic study of new diagnostic modality according to non-invasive measurement of the electrical conductivity of tissues. J Med Invest. 2004;51(3-4):218–25. 10.2152/jmi.51

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Monitoring thoracic fluid content using bioelectrical impedance spectroscopy and Cole modeling

Cole model and on geometrical properties of the impedance arc. Indicator dilution measurements obtained through cardiac magnetic resonance imaging were used as a reference for the changes in pulmonary fluid volume. Eight healthy subjects were included in the study. The Cole model parameters of the study group at baseline were: R 0 = 51.4 ± 6.7 Ω, R ∞ = 25.0 ± 7.0 Ω, f c = 49.0 ± 10.5 kHz, α = 0.687 ± 0.027, the resistances of individual fluid compartments were R E = 51.4 ± 6.7 Ω, R I = 50.5 ± 22.9 Ω, the fluid distribution ratio was K = 1.1 ± 0.3, and the

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Classification of different erythrocyte cells by using bioimpedance surface acoustic wave and their sedimentation rates

liquids will vary. The time rates of changing for these heights are related to the sedimentation velocity, where higher velocity means high rates of these lengths or heights. The sedimentation velocity of the RBCs as function of their radii and the volume fractions is given by [13]. (5) v = ρ R B C − ρ p l a s ∗ g ∗ d 2 / 18 μ 1 + 2.5 Φ $$v=\left( {{\rho }_{RBC}}-{{\rho }_{plas}} \right)*g*\,\,{{{d}^{2}}}/{18\mu \left( 1

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Parallel, multi frequency EIT measurement, suitable for recording impedance changes during epilepsy

Electrical impedance tomography of human brain function using reconstruction algorithms based on the finite element method Neuroimage 2003 20 2 752 – 764 10 Holder D. Electrical impedance tomography in epilepsy. Electron. Eng. Miller Freeman plc; 1998;70(859):69–70. Holder D Electrical impedance tomography in epilepsy Electron. Eng. Miller Freeman plc; 1998 70 859 69 – 70 11 Vongerichten A, Sato dos Santos G, Avery J, Walker M, Holder D. Electrical impedance tomography (EIT) of epileptic seizures in rat

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Narrowband array processing beamforming technique for electrical impedance tomography

. Technol., vol. 25, no. 5, p. 055303 (12 pp.), 2014. Lioumbas J. S. Chatzidafni A Karapantsios T. D. “Spatial considerations on electrical resistance tomography measurements,” Meas. Sci. Technol. 25 5 p. 055303 (12 pp.) 2014 12 G. J. Saulnier, R. S. Blue, J. C. Newell, D. Isaacson, and P. M. Edic, “Electrical impedance tomography,” IEEE Signal Process. Mag., vol. 18, no. 6, pp. 31–43, 2001. Saulnier G. J. Blue

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Compression-dependency of soft tissue bioimpedance for in-vivo and in-vitro tissue testing

averaged admittance Nyquist plots, resulted in the extracted Cole features ( G 0 , G ∞ , a and f yc ) within each pressure level. Cole circuit equivalent parameters ( R ext , R int and C m ) were then calculated from equations 3 to 5 . Thus for all twenty chicken samples, two rat samples and eleven human subjects, R ext , R int and C m were acquired at various pressure levels. Table 1 represents the average of the Cole parameters of all subjects and samples at the first pressure levels (2.5 N in human subjects and 2.2 N in chicken and rat samples) and

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Spatial resolution in electrical impedance tomography: A topical review

. Meas vol. 27 no. 5 S25 S42 2006 59 F. S. Lee, Optimum array processing, vol. 35, no. July. John Wiley and Sons, 2008. Lee F. S. Optimum array processing vol. 35 no. July John Wiley and Sons 2008 60 S. Manohar, A. Kharine, J. C. G. van Hespen, W. Steenbergen, and T. G. van Leeuwen, "The Twente Photoacoustic Mammoscope: system overview and performance.," Phys. Med. Biol., vol. 50, no. 11, pp. 2543–57, 2005. 10.1088/0031-9155/50/11/007 Manohar S. Kharine A

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Textrode-enabled transthoracic electrical bioimpedance measurements – towards wearable applications of impedance cardiography

textrode belts, Table I ICG PARAMETERS dZ/dt max (Ω/s 2 ) SV (ml) LVET (ms) R-Z Time (ms) avg std avg std avg std avg std S1 RedDot 1.03 0.05 71.52 3.94 336.99 17.34 149.78 3.87 Tex-Belt 0.94 0.03 69.15 3.63 341.07 18.41 145.60 3.54 S2 RedDot 0.71 0.07 70.04 4.88 328.58 16.92 164.20 6.54 Tex-Belt 0.61 0.05 78.64 5.28 349.51 17.77 173.14 5.04 S3 RedDot 0.74 0.05 76.03 4.62 391.11 22.36 159.33 7.73 Tex

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Development of a real-time, semi-capacitive impedance phlebography device

Since the device should measure through an isolating material, a capacitive measurement system was developed. The capacitive measuring was done by active electrodes as an impedance converter, which enables a low-impedance processing of the measured potential φ G . Figure 2 shows the measurement of a potential φ G with a capacitive electrode. The lower part of the Figure shows the corresponding equivalent circuit. Fig. 2 Measuring arrangement for impedance measurement with two or four electrodes and the corresponding equivalent electric circuit. The

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Comparison of cardiac time intervals between echocardiography and impedance cardiography at various heart rates

, various physiological models and algorithms were used, e.g. by Sramek et al. and Bernstein [ 2 , 3 , 4 ]. Most of the estimates of SV were essentially based on the assumptions that the C-wave originates from small fluctuations in a simply distributed electrical field caused by blood volume changes or velocity changes in the aorta. Meanwhile, several studies have shown that these assumptions are too simplistic [ 5 , 6 , 7 , 8 , 9 ]. Therefore, it appears to be futile to make an interpretation of the amplitude of the ICG-signal based on simplistic models. A

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