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Common-mode currents can be induced on cables attached to printed circuit boards (PCBs) due to electric and magnetic field coupling. This paper describes a technique for using transverse electromagnetic (TEM) cell measurements to obtain an effective common-mode voltage (or magnetic moment) that quantifies the ability of traces anal integrated circuits on PCBs to drive common-mode currents onto cables due to magnetic field coupling. This equivalent common-mode voltage can be used to reduce the complexity of full-wave models that calculate the radiated emissions from a system containing the board. It can also be used without full-wave modeling to provide a relative indication of the likelihood that a particular board design will have unintentional radiated emissions problems due to magnetic field coupling. Index Terms--Magnetic field coupling, mutual inductance, radiated emissions, transverse electromagnetic (TEM) cell.

High-frequency currents on the pins of integrated circuits (ICs) and on printed circuit board (PCB) traces are needed to predict and analyze electromagnetic interference in high-speed devices. These currents can, however, be difficult to measure when traces are buried within the PCB or chip-package, especially when several current-carrying traces are in close proximity. Techniques for estimating high-frequency currents from near-field scan data are proposed in this paper. These techniques are applied to find currents on the pins of an IC, on traces buried beneath other traces in a PCB, and on traces over a slot in the ground plane. Methods of dealing with the ill-posed nature of the current-estimation problem are discussed, as are applications to electrically large structures. A study of the sensitivity of the technique to errors in the measured fields, errors in the circuit geometry, and errors in the estimated dielectric constant of the PCB or chip package show that, for reasonable errors in these parameters, currents can be estimated to within an average of 20% (1.6 dB) or less of their correct values. Index Terms--Compensation, current measurement, estimation, inverse problems, magnetic field measurement.

One method for evaluating the unintentional radiated emissions from integrated circuits (ICs) involves mounting the IC on a printed circuit board (PCB) embedded in the wall of a transverse electromagnetic (TEM) cell. The signal voltages on the IC and its package produce electric fields that can couple to cables and other structures attached to the PCB, inducing common-mode currents that can be a primary source of unintentional radiated emissions. The signal currents in the IC and its package produce magnetic fields that can also result in common-mode currents on larger radiating structures. This paper describes a TEM cell measurement method employing a hybrid to separate the electric field coupling and the magnetic field coupling. The results of this measurement can be used to determine the product of the IC's selfcapacitance and the effective voltage that drives this capacitance. This voltage-capacitance product characterizes the IC's ability to drive common-mode currents onto cables or enclosures due to electric field coupling. This information can then be used to estimate the resulting radiated emissions. Index Terms--Closed-form equation, mutual capacitance, radiated emissions, self-capacitance, transverse electromagnetic (TEM) cell.

When running, vehicles with internal combustion engines radiate electromagnetic emissions that are characteristic of the vehicle. Emissions depend on the electronics, harness wiring, body type, and many other features. Since emissions are unique to each vehicle, these may be used for identification purposes. This paper investigates a procedure for detecting and identifying vehicles based on their RF emissions. Parameters like the average magnitude or standard deviation of magnitude within a frequency band were extracted from measured emission data. These parameters were used as inputs to an artificial neural network (ANN) that was trained to identify the vehicle that produced the emissions. The approach was tested using the emissions captured from a Toyota Tundra, a GM Cadillac, a Ford Windstar, and ambient noise. The ANN was able to classify the source of signals with 99% accuracy when using emissions that captured an ignition spark event. Index Terms--Detectors, electromagnetic radiation, identification, neural networks, vehicles.

Direct inference of heart-surface potentials from body-surface potentials has been the goal of most recent work on electrocardiographic inverse solutions. We developed and tested indirect methods for inferring heart-surface potentials based on estimation of regularized multipole sources. Regularization was done using Tikhonov, constrained-least-squares, and multipole-truncation techniques. These multipole-equivalent methods (MEMs) were compared to the conventional mixed boundary-value method (BVM) in a realistic torso model with up to 20% noise added to body-surface potentials and [+ or -] 1 cm error in heart position and size. Optimal regularization was used for all inverse solutions. The relative error of inferred heart-surface potentials of the MEM was significantly less (p < 0.05) than that of the BVM using zeroth-order Tikhonov regularization in 10 of the 12 cases tested. These improvements occurred with a fourth-degree (24 coefficients) or smaller multipole moment. From these multipole coefficients, heart-surface potentials can be found at an unlimited number of heart-surface locations. Our indirect methods for estimating heart-surface potentials based on multipole inference appear to offer significant improvement over the conventional direct approach. Index Terms--Constrained least squares, inverse electrocardiology, multipole expansion, Tikhonov regularization.

Variations in electrical impedance over frequency might be used to distinguish basal cell carcinoma (BCC) from benign skin lesions, although the patterns that separate the two are nonobvious. Artificial neural networks (ANNs) may be good pattern classifiers for this application. A preliminary study to show the potential of neural networks to distinguish benign from malignant skin lesions using electrical impedance is presented. Electrical impedance was measured in vivo from 1 kHz to 1 MHz at five virtual depths on 18 BCC and 16 benign or premalignant lesions. A feed-forward neural network was trained using back propagation to classify these lesions. Two methods of preprocessing were used to account for the impedance of normal skin and the size of the lesion, one based on estimating the impedance of the lesion relative to adjacent normal skin and one based on estimating the impedance of the lesion independent of size or surrounding normal skin. Neural networks were able to classify measurements in a test set with 100% accuracy for the first preprocessing technique and 85% accuracy for the second. These results indicate electrical impedance may be a promising clinical diagnostic tool for basal cell carcinoma or other forms of skin cancer. Index Terms--Basal cell carcinoma, bioimpedance, frequency, resistivity, tissue characterization.

This paper presents a preliminary study showing the diagnostic potential of electrical impedance to detect basal cell carcinoma (BCC). Electrical impedance was measured in vivo from 1 kHz to 1 MHz on 24 human subjects over BCC (19 lesions), over benign tumors (11 lesions), and over normal skin (all 24 patients). Lesions ranged from 2-15 mm in diameter. Indexes based on the magnitude (MIX), phase (PIX), real-part (RIX) and imaginary-part (IMIX) of impedance were calculated for each measurement. Significant differences were found between measurements over BCC, benign lesions and normal skin for indexes MIX, PIX, and IMIX (P = 0.04 to P = 7 x [10.sup.-7]). Indexes were generally smaller for measurements of BCC than for benign lesions or normal skin. Differences were not a result of differences in the patient's age or the measurement location. The large size of our measurement electrode (10 mm) probably limited our ability to differentiate lesions because significant amounts of normal skin were included in each lesion measurement. A linear regression fit of data with tumor size suggests that a smaller probe or more sophisticated analysis techniques may improve differentiation. Results suggest that electrical impedance could be used to provide rapid and noninvasive differentiation of BCC from similar looking benign lesions. Index Terms--Basal cell carcinoma, bioelectrical impedance, electric conductivity, spectrum analysis, tissue characterization.