40 resultados para HARMONIC IMPEDANCE
Resumo:
A new mutual impedance - the receiving mutual impedance - between two normal-mode helical antennas is defined, measured, and theoretically calculated. The variations of the receiving mutual impedance with antenna separation, with frequency, and with excitation source direction are critically investigated. An application of the receiving mutual impedance in direction finding demonstrates its more accurate description of the mutual coupling effect than that using the conventional mutual impedance.
Resumo:
Multiple frequency bio-electrical impedance analysis (MFBIA) may be useful for monitoring fluid balance in newborn infants or to provide early prediction of the outcome following perinatal asphyxia. A reference range of data is needed for identification of babies with abnormal impedance values. This was a cross-sectional observational study in 84 term and near-term healthy neonates less than 12 h postpartum. Whole body and cerebral MFBIA measurements were performed at the bedside in the post-natal ward. Gestational age, post-natal age, gender, birthweight, head circumference and foot length measures were recorded. Reference values for impedance at the characteristic frequency (Z(C)) and resistance at zero frequency (R-0) are reported for whole body and cerebral impedance. Significant correlations (p < 0.05) were observed between whole body impedance and birthweight, footlength and head circumference. Females had a significantly higher whole body R0 than males. Cerebral impedance did not correlate significantly with any of the demographic measures and therewere no gender differences observed for cerebral impedance. The reference range for whole body multi-frequency bio-impedance values in term and near-term infants within the first 12 h postpartum can be calculated from the footlength (FL) using the following equations: Z(C) = (942.9 - 4.818* FL) +/- 124.6 Omega; R-0 = (1042 - 4.520(*)FL) +/- 135.5 Omega. For cerebral impedance the reference range is 29.5-48.7 Omega for Z(C) and 33.7-58.0 Omega for R-0.
Resumo:
We thank Hilberts and Troch [2006] for their comment on our paper [Cartwright et al, 2005]. Before proceeding with our specific replies to the comments we would first like to clarify the definitions and meanings of equations (1)-(3) as presented by Hilberts and Troch [2006]. First, equation (1) is the fundamental definition of the (complex) effective porosity as derived by Nielsen and Perrochet [2000]. Equations (2) and (3), however, represent the linear frequency response function of the water table in the sand column responding to simple harmonic forcing. This function, which was validated by Nielsen and Perrochet [2000], provides an alternative method for estimating the complex effective porosity from the experimental sand column data in the absence of direct measurements of h_(tot) (which are required if equation (1) is to be used).
Resumo:
Using only linear interactions and a local parity measurement we show how entanglement can be detected between two harmonic oscillators. The scheme generalizes to measure both linear and nonlinear functionals of an arbitrary oscillator state. This leads to many applications including purity tests, eigenvalue estimation, entropy, and distance measures-all without the need for nonlinear interactions or complete state reconstruction. Remarkably, experimental realization of the proposed scheme is already within the reach of current technology with linear optics.
Resumo:
Two-dimensional (2-D) strain (epsilon(2-D)) on the basis of speckle tracking is a new technique for strain measurement. This study sought to validate epsilon(2-D) and tissue velocity imaging (TVI)based strain (epsilon(TVI)) with tagged harmonic-phase (HARP) magnetic resonance imaging (MRI). Thirty patients (mean age. 62 +/- 11 years) with known or suspected ischemic heart disease were evaluated. Wall motion (wall motion score index 1.55 +/- 0.46) was assessed by an expert observer. Three apical images were obtained for longitudinal strain (16 segments) and 3 short-axis images for radial and circumferential strain (18 segments). Radial epsilon(TVI) was obtained in the posterior wall. HARP MRI was used to measure principal strain, expressed as maximal length change in each direction. Values for epsilon(2-D), epsilon(TVI), and HARP MRI were comparable for all 3 strain directions and were reduced in dysfunctional segments. The mean difference and correlation between longitudinal epsilon(2-D) and HARP MRI (2.1 +/- 5.5%, r = 0.51, p < 0.001) were similar to those between longitudinal epsilon(TVI), and HARP MRI (1.1 +/- 6.7%, r = 0.40, p < 0.001). The mean difference and correlation were more favorable between radial epsilon(2-D) and HARP MRI (0.4 +/- 10.2%, r = 0.60, p < 0.001) than between radial epsilon(TVI), and HARP MRI (3.4 +/- 10.5%, r = 0.47, p < 0.001). For circumferential strain, the mean difference and correlation between epsilon(2-D) and HARP MRI were 0.7 +/- 5.4% and r = 0.51 (p < 0.001), respectively. In conclusion, the modest correlations of echocardiographic and HARP MRI strain reflect the technical challenges of the 2 techniques. Nonetheless, epsilon(2-D) provides a reliable tool to quantify regional function, with radial measurements being more accurate and feasible than with TVI. Unlike epsilon(TVI), epsilon(2-D) provides circumferential measurements. (c) 2006 Elsevier Inc. All rights reserved.
Resumo:
Functional electrical impedance tomography (EIT) measures relative impedance change that occurs in the chest during a distinct observation period and an EIT image describing regional relative impedance change is generated. Analysis of such an EIT image may be erroneous because it is based on an impedance signal that has several components. Most of the change in relative impedance in the chest is caused by air movement but other physiological events such as cardiac activity change in end expiratory level or pressure swings originating from a ventilator circuit can influence the impedance signal. We obtained EIT images and signals in spontaneously breathing healthy adults, in extremely prematurely born infants on continuous positive airway pressure and in ventilated sheep on conventional mechanical or high frequency oscillatory ventilation (HFOV). Data were analyzed in the frequency domain and results presented after band pass filtering within the frequency range of the physiological event of interest. Band pass filtering of EIT data is necessary in premature infants and on HFOV to differentiate and eliminate relative impedance changes caused by physiological events other than the one of interest.