A CMOS current driver with built-in common-mode signal reduction capability for EIT

This paper presents an integrated fully differential current driver for wearable multi-frequency electrical impedance tomography (EIT). The integrated circuit (IC) comprises a wideband current driver (up to 500 kHz) functioning as the master for current sourcing, and a differential voltage receiver with common-mode feedback configuration as the slave for current sinking. The IC is fabricated in a 0.18-µm CMOS technology. It operates from ±1.65 V power supplies and occupies a total die area of less than 0.05 mm2 . The current driver has a measured output impedance of 750 kΩ at 500 kHz and provides a common-mode signal reduction of 32 dB at 500 kHz. The application of the IC in a wearable EIT lung monitoring system is presented

A comparison of techniques to optimize measurement of voltage changes in electrical impedance tomography by minimizing phase shift errors

In electrical impedance tomography, errors due to stray capacitance may be reduced by optimization of the reference phase of the demodulator. Two possible methods, maximization of the demodulator output and minimization of reciprocity error have been assessed, applied to each electrode combination individually, or to all combinations as a whole. Using an EIT system with a single impedance measuring circuit and multiplexer to address the 16 electrodes, the methods were tested on resistor-capacitor networks, saline-filled tanks and humans during variation of the saline concentration of a constant fluid volume in the stomach. Optimization of each channel individually gave less error, particularly on humans, and maximization of the output of the demodulator was more robust. This method is, therefore, recommended to optimize systems and reduce systematic errors with similar EIT systems

Absorption and optimal plasmonic resonances for small ellipsoidal particles in lossy media

A new simplified formula is derived for the absorption cross section of small dielectric ellipsoidal particles embedded in lossy media. The new expression leads directly to a closed form solution for the optimal conjugate match with respect to the surrounding medium, i.e. the optimal permittivity of the ellipsoidal particle that maximizes the absorption at any given frequency. This defines the optimal plasmonic resonance for the ellipsoid. The optimal conjugate match represents a metamaterial in the sense that the corresponding optimal permittivity function may have negative real part (inductive properties), and can not in general be implemented as a passive material over a given bandwidth. A necessary and sufficient condition is derived for the feasibility of tuning the Drude model to the optimal conjugate match at a single frequency, and it is found that all the prolate spheroids and some of the (not too flat) oblate spheroids can be tuned into optimal plasmonic resonance at any desired center frequency. Numerical examples are given to illustrate the analysis. Except for the general understanding of plasmonic resonances in lossy media, it is also anticipated that the new results can be useful for feasibility studies with e.g. the radiotherapeutic hyperthermia based methods to treat cancer based on electrophoretic heating in gold nanoparticle suspensions using microwave radiation

A 122 fps, 1 MHz bandwidth multi-frequency wearable EIT belt featuring novel active electrode architecture for neonatal thorax vital sign monitoring

A highly integrated, wearable electrical impedance tomography (EIT) belt for neonatal thorax vital multiple sign monitoring is presented. The belt has sixteen active electrodes. Each has an application specific integrated circuit (ASIC) connected to an electrode. The ASIC contains a fully differential current driver, a high-performance instrumentation amplifier (IA), a digital controller and multiplexors. The wearable EIT belt features a new active electrode architecture that allows programmable flexible electrode current drive and voltage sense patterns under simple digital control. It provides intimate connections to the electrodes for the current drive and to the IA for direct differential voltage measurement providing superior common-mode rejection ratio. The ASIC was designed in a CMOS 0.35-μm high-voltage technology. The high specification EIT belt has an image frame rate of 122 fps, a wide operating bandwidth of 1 MHz and multi-frequency operation. It measures impedance with 98% accuracy and has less than 0.5 Ω and 1o variation across all possible channels. The image results confirmed the advantage of the new active electrode architecture and the benefit of wideband, multi-frequency EIT operation. The wearable EIT belt can also detect patient position and torso shape information using a MEMS sensor interfaced to each ASIC. The system successfully captured high quality lung respiration EIT images, breathing cycle and heart rate

On the physical limitations for radio frequency absorption in gold nanoparticle suspensions

This paper presents a study of the physical limitations for radio frequency absorption in gold nanoparticle (GNP) suspensions. A spherical geometry is considered consisting of a spherical suspension of colloidal GNPs characterized as an arbitrary passive dielectric material which is immersed in an arbitrary lossy medium. A relative heating coefficient and a corresponding optimal near field excitation are defined taking the skin effect of the surrounding medium into account. The classical Mie theory for lossy media is also revisited, and it is shown that the optimal permittivity function yielding a maximal absorption inside the spherical suspension is a conjugate match with respect to the surrounding lossy material. A convex optimization approach is used to investigate the broadband realizability of an arbitrary passive material to approximate the desired conjugate match over a finite bandwidth, similar to the approximation of a metamaterial. A narrowband realizability study shows that for a surrounding medium consisting of a weak electrolyte solution, the electromagnetic heating due to the electrophoretic (plasmonic) resonance phenomena inside the spherical GNP suspension can be significant in the microwave regime, provided that the related Drude parameters can be tuned into (or near to) resonance. As a demonstration, some realistic Drude parameters are investigated concerning the volume fraction, mass, and friction constant of the GNPs. The amount of charge that can be accommodated by the GNPs is identified as one of the most important design parameters. However, the problem to reliably model, measure and control the charge number of coated GNPs is not yet fully understood, and is still an open research issue in this field. The presented theory and related physical limitations provide a useful framework for further research in this direction. Future research is also aiming at an expansion towards arbitrary suspension geometries and the inclusion of thermodynamical analysis

Analysis and compensation for errors in electrical impedance tomography images and ventilation-­related measures due to serial data collection

Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study was to determine the extent to which this affects derived parameters. Raw EIT data were acquired with the GOE­MF II EIT device (CareFusion, Höchberg, Germany) at a scan rate of 13 images/s during both spontaneous breathing and mechanical ventilation. Boundary data for periods of undisturbed tidal breathing were corrected for serial data collection errors using a Fourier based algorithm. Images were reconstructed for both the corrected and original data using the GREIT algorithm, and parameters describing the filling characteristics of the right and left lung derived on a breath by breath basis. Values from the original and corrected data were compared using paired t­ tests. Of the 33 data sets, 23 showed significant differences in filling index for at least one region, 11 had significant differences in calculated tidal impedance change and 12 had significantly different filling fractions (p = 0.05). We conclude that serial collection errors should be corrected before image reconstruction to avoid clinically misleading results

Forearm motion and hand grasp prediction based on target muscle bioimpedance for Human-Machine Interaction

This paper introduces a novel methodology for simultaneously predicting hand grasp and forearm motion using target muscle bioimpedance measurements and regression models. A total of six channels, formed by nine electrodes, are employed for this multi-degree of freedom (DoF) prediction. Given the time-dependent nature of bioimpedance variation, the long short-term memory (LSTM) regression model is more competent in multi-DoF prediction, compared to linear regression (LR), support vector regression (SVR) and multilayer perceptron (MLP). In intra-subject cross-validation, MLP yields an average coefficient of determination (R2) of 0.9256 for predicting hand grasping angle, while LSTM achieves an average R2 of 0.9483 for predicting random simultaneous forearm two-DoF motion. Operation by amputees without the need to train the regression models is possible by mapping muscle bioimpedance variation directly to the prediction angle, allowing for the approximate estimation of single-DoF motion. The efficacy of these prediction approaches is demonstrated in a real-time object grasping task

A compact neural network for high accuracy bioimpedance-based hand gesture recognition

This paper presents a compact customised neural network with 44 parameters for hand gesture recognition based on electrical impedance tomography (EIT) using a flexible 8-electrode band. The classification accuracy is improved by assigning higher weights to the impedances captured closer to the current injection position. The non-fully connected layer working as a spatial filter reduces the complexity of the network structure. Validated on a discrete EIT system, the proposed network structure can distinguish eight gestures with an accuracy of 99.49%. Towards a low-power wearable design, an analogue inference circuit based on the proposed network structure was also designed in 65 nm CMOS. The system features a low-power multi-output digital-to-analogue converter (DAC) to provide data for the analogue computation efficiently. This designed CMOS analogue inference has a recognition accuracy of 98.13%

A current DAC based current generator with fourth-order current-mode filter for electrical impedance tomography

The current generator is one of the most essential parts in electrical impedance tomography (EIT) systems. State-of-art current generators suffer from the trade-off between current efficiency, linearity, output impedance and well-controlled output current level. To address these challenges, a current DAC based current generator with a fourth-order current-mode filter is proposed. The current generator was designed and simulated in a 65 nm CMOS process. By utilizing the proposed current-mode filter and the master and slave current DAC, the current generator achieves a well-controlled output current leveling with 255 tunning steps, 83.9% current efficiency, 0.11% THD at 1 mA pp output current and 2 MΩ output impedance at 500 kHz