Detection and elimination of signal errors due to unintentional movements in biomedical magnetic induction tomography spectroscopy (MITS)

In biomedical MITS, slight unintentional movements of the patient during measurement can contaminate the aimed images to a great extent. This study deals with measurement optimization in biomedical MITS through the detection of these unpredictable movements during measurement and the elimination of the resulting movement artefacts in the images to be reconstructed after measurement. The proposed detection and elimination (D&E) methodology requires marking the surface of the object under investigation with specific electromagnetically perturbing markers during multi-frame measurements. In addition to the active marker concept already published, a new much simpler passive marker concept is presented. Besides the biological signal caused by the object, the markers will perturb the primary magnetic field inducing their own signals. The markers' signals will be used for the detection of any unwanted object movements and the signal frames corrupted thereby. The corrupted signal frames will be then excluded from image reconstruction in order to prevent any movement artefacts from being imaged with the object. In order to assess the feasibility of the developed D&E technique, different experiments followed by image reconstruction and quantitative analysis were performed. Hereof, target movements were provoked during multifrequency, multiframe measurements in the β-dispersion frequency range on a saline phantom of physiological conductivity. The phantom was marked during measurement with either a small single-turn coil, an active marker, or a small soft-ferrite plate, a passive marker. After measurement, the erroneous phantom signals were corrected according to the suggested D&E strategy, and images of the phantom before and after correction were reconstructed. The corrected signals and images were then compared to the erroneous ones on the one hand, and to other true ones gained from reference measurements wherein no target movements were provoked on the other hand. The obtained qualitative and quantitative measurement and image reconstruction results showed that the erroneous phantom signals could be accurately corrected, and the movement artefacts could be totally eliminated, verifying the applicability of the novel D&E technique in measurement optimization in biomedical MITS and supporting the proposed aspects.

Analysis and Experimental Estimation of Nonlinear Dispersion in a Periodic String

Wave dispersion in a string carrying periodically distributed masses is investigated analytically and experimentally. The effect of the string's geometric nonlinearity on its wave propagation characteristics is analyzed through a lumped parameter model yielding coupled Duffing oscillators. Dispersion frequency shifts are predicted that correspond to the hardening behavior of the nonlinear chain and that relate well to the backbone of individual Duffing oscillators. Experiments conducted on a string of finite length illustrate the relation between measured resonances and the dispersion properties of the medium. Specifically, the locus of resonance peaks in the frequency/wavenumber domain outlines the dispersion curve and highlights the existence of a frequency bandgap. Moreover, amplitude-dependent resonance shifts induced by the string nonlinearity confirm the hardening characteristics of the dispersion curve. Analytical and experimental results provide a critical link between nonlinear dispersion frequency shifts and the backbone curves intrinsic to nonlinear frequency response functions. Moreover, the study confirms that amplitude-dependent wave properties for nonlinear periodic systems may be exploited for tunability of wave transport characteristics such as frequency bandgaps and wave speeds.

Accurate and Efficient BER Calculation by Statistical Simulation Based on Physical Transmit Jitter Model

Statistical analysis provides an efficient alternative to the traditional Monte Carlo simulation for extremely low BER calculation in high speed serial link designs. Transmitter (TX) jitter posts a huge challenge in statistical simulation due to its pattern- and time-dependent nature and the resulting computational complexity. This paper presents a fast yet rigorous approach to calculate TX jitter in statistical simulation based on physical models of various jitter components. The approach accurately captures effects of uncorrelated random jitters, jitter amplification by channel dispersion, frequency dependency of periodic jitter and data duty-cycle-distortion.