Electrical Impedance Tomography System Research Articles

A Low-Power Recursive I/Q Signal Generator and Current Driver for Bioimpedance Applications

This brief presents a power-efficient quadrature signal generator and current driver application-specific integrated circuit (ASIC) for bioimpedance measurements in an electrical impedance tomography system for monitoring lung function. The signal generator is realized by a digital recursive signal oscillator with the ability of generating quadrature signals over a wide frequency range. The generated in-phase signal is applied to a current driver. It uses a balanced current-mode feedback architecture that monitors the output current through a feedback loop to minimize common-mode voltage build-up at the injection site. The quadrature signals can be used for I/Q demodulation of the measured bioimpedance. The ASIC was designed in TSMC 65 nm technology occupying an area of 0.21 mm2. The current driver can generate up to 0.7 mA <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$_{\text {p-p}}$ </tex-math></inline-formula> current up to 200 kHz and consumes 2.7 mW power using ±0.8 V supplies.

A new portable electrical impedance tomography system for measuring two-dimensional stem water content distribution

Stem water content (StWC) is an important parameter for characterizing plant–water relations. Most sensors and methods can measure only one-dimensional StWC, and those measuring two-dimensional (2D) StWC distributions are expensive. In this study, we developed a low-cost and portable electrical impedance tomography (EIT) system to measure 2D StWC distributions in vivo. The performance of the EIT system was tested in a laboratory setting. An analog stem made of gypsum and two true stems cut from apple trees were used to calibrate the relationship between the average StWC (θv¯) and average change in electrical conductivity (Δσ¯) determined by the EIT system during the stepwise drying procedure. Evaporation experiments were conducted in the laboratory with hollow analog and cut stems to detect variations in StWC (Δθv) and its 2D distribution. Finally, the EIT system was installed in an apple tree for the in vivo monitoring of the diurnal variation of the 2D StWC distribution. The results indicated that the optimal measurement frequency of the EIT system was 47 kHz. After correcting for the effect of temperature, the average relative error of the measurement was reduced (approximately 80.21%). The effective height of the volume sensitivity of the EIT system was approximately 6 cm. The relationship between θv¯ and Δσ¯ showed a strong positive correlation, with all R2 values higher than 0.9808 for the analog stem and two cut stems. Moreover, the actual and EIT-estimatedθv¯ of the analog and cut stems during the evaporation experiments agreed well (R2 = 0.9367 and 0.9610, respectively), which validated the feasibility of the EIT system for StWC measurements. Furthermore, the in vivo EIT-estimated Δθv distribution of the apple tree was highly consistent with the regulation of diurnal variation in StWC in a greenhouse under irrigation and drought stress conditions. The new portable EIT system was able to measure the 2D StWC distribution and has great potential for application in drought monitoring of plant in the near future.

Imaging spatial-temporal distribution of moisture in intact maize ear

The moisture distribution in maize ears during the growth period has a major impact on crop quality and post-harvest production costs and is an important indicator for plant breeding. An electrical impedance tomography system with a resilient electrode array was designed to fit around a maize ear, and featured an adjustable diameter that can be adapted to the growth of the ear. We used the system to monitor the dehydration of an intact maize ear in situ over 5 days and observe the changes in moisture distribution. The high-contrast images correlated with the moisture distribution in the maize ear. We also created a 3D model to visualize the distribution of moisture content within the maize ear. Our method provides a novel tool to monitor the spatial-temporal dynamics of the water content within the maize ear in situ.

Electrical Impedance Tomography Based on Grey Wolf Optimized Radial Basis Function Neural Network.

Electrical impedance tomography (EIT) is a non-invasive, radiation-free imaging technique with a lot of promise in clinical monitoring. However, since EIT image reconstruction is a non-linear, pathological, and ill-posed issue, the quality of the reconstructed images needs constant improvement. To increase image reconstruction accuracy, a grey wolf optimized radial basis function neural network (GWO-RBFNN) is proposed in this paper. The grey wolf algorithm is used to optimize the weights in the radial base neural network, determine the mapping between the weights and the initial position of the grey wolf, and calculate the optimal position of the grey wolf to find the optimal solution for the weights, thus improving the image resolution of EIT imaging. COMSOL and MATLAB were used to numerically simulate the EIT system with 16 electrodes, producing 1700 simulation samples. The standard Landweber, RBFNN, and GWO-RBFNN approaches were used to train the sets separately. The obtained image correlation coefficient (ICC) of the test set after training with GWO-RBFNN is 0.9551. After adding 30, 40, and 50 dB of Gaussian white noise to the test set, the attained ICCs with GWO-RBFNN are 0.8966, 0.9197, and 0.9319, respectively. The findings reveal that the proposed GWO-RBFNN approach outperforms the existing methods when it comes to image reconstruction.

High Frame Rate Electrical Impedance Tomography System for Monitoring of Regional Lung Ventilation.

This paper describes the development of a compact high frame rate passive electrical impedance tomography system. The injected current amplitude and frequency can be adjusted to fit any EIT application. Measured results show that the system is capable of high frame rate of 89 fps and has power consumption of 1.7 W. It has automatic gain control that reduces noise and improves the quality of the measured EIT image. A comparison is made with other EIT systems to show the potential of the developed system. Clinical Relevance- The developed EIT system has application in the clinical assessment of neonatal and SARS-Co V-2 patients. In these applications there is an urgent need for a low cost bedside non-invasive imaging system to continuously monitor dynamic changes in regional lung ventilation.

A Rapid, Low-Cost, and High-Precision Multifrequency Electrical Impedance Tomography Data Acquisition System for Plant Phenotyping

Plant phenotyping plays an important role for the thorough assessment of plant traits such as growth, development, and physiological processes with the target of achieving higher crop yields by the proper crop management. The assessment can be done by utilizing two- and three-dimensional image reconstructions of the inhomogeneities. The quality of the reconstructed image is required to maintain a high accuracy and a good resolution, and it is desirable to reconstruct the images with the lowest possible noise. In this work, an electrical impedance tomography (EIT) data acquisition system is developed for the reconstruction and evaluation of the inhomogeneities by utilizing a non-destructive method. A high-precision EIT system is developed by designing an electrode array sensor using a cylindrical domain for the measurements in different planes. Different edible plant slices along with multiple plant roots are taken in the EIT domain to assess and calibrate the system, and their reconstructed results are evaluated by utilizing an impedance imaging technique. A non-invasive imaging is carried out in multiple frequencies by utilizing a difference method of reconstruction. The performance and accuracy of the EIT system are evaluated by measuring impedances between 1 and 100 kHz using a low-cost and rapid electrical impedance spectroscopy (EIS) tool connected to the sensor. A finite element method (FEM) modeling is utilized for image reconstruction, which is carried out using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). The reconstruction is made successfully with the optimized results obtained using Gauss–Newton (GN) algorithms.

An In Situ Electrical Impedance Tomography Sensor System for Biomass Estimation of Tap Roots.

Root biomass is one of the most relevant root parameters for studies of plant response to environmental change. In this work, a dynamic and adjustable electrode array sensor system is designed for developing a cost-effective, high-speed data acquisition system based on electrical impedance tomography (EIT). The developed EIT system is found to be suitable for in situ measurements and capable of monitoring the changes in root growth and development with three-dimensional imaging by measuring impedances in multiple frequencies with the help of an EIT sensor. The designed EIT sensor system is assessed and calibrated by the inhomogeneities in both water and soil media. The impedances are measured for multiple tap roots using an electrical impedance spectroscopy (EIS) tool connected to the sensor at frequencies ranging from 1 kHz to 100 kHz. The changes in conductivity are calculated by obtaining the boundary voltages from the measured impedances for a given stimulation current. A non-invasive imaging method is utilized, and the spectral changes are observed accordingly to evaluate the growth of the roots. A further root analysis helps us estimate the root biomass non-destructively in real-time. The root size (such as, weight, length) is correlated with the measured impedances. A regression analysis is performed using the least square method, and more than 97% correlation is found for the biomass estimation of carrot roots with an RMSE of 4.516. The obtained models are later validated using a new and separate set of carrot root samples and the accuracy of the predicted models is found to be 93% or above. A complete electrode model is utilized, and the reconstruction analysis is performed and optimized by utilizing the impedance imaging technique in difference method. The tomography of the root is reconstructed with finite element method (FEM) modeling considering one-step Gauss–Newton (GN) algorithm which is carried out using an open source software known as electrical impedance and diffuse optical tomography reconstruction software (EIDORS).

Development of a Wearable Gesture Recognition System Based on Two-Terminal Electrical Impedance Tomography.

This paper proposes a low-cost, wearable gesture recognition system based on the two-terminal electrical impedance tomography (EIT) technique. The system includes a wearable EIT sensor of eight electrodes, a hardware device, and gesture recognition software running on a PC. Nine different gestures can be stably identified from the measured impedance changes through machine learning algorithms. Experimental results show that the Quadric Discriminator algorithm has the highest recognition rate of 98.49% for the filtered validation set. Besides, the recognition results in the two-terminal mode and transformed four-terminal mode are compared by applying a two-to-four-terminal mapping to the two-terminal EIT system, and the recognition rate decreases with the most classification models in the latter mode. Thus, it is supposed that contact impedance plays an important role in gesture recognition. By analyzing the data characteristics with variance inflation factor (VIF) test and principal component analysis (PCA), the supposition is explained and verified, proving the merit of a two-terminal EIT system in gesture recognition.

Generation of Anatomically Inspired Human Airway Tree Using Electrical Impedance Tomography: A Method to Estimate Regional Lung Filling Characteristics.

The purpose of lung recruitment is to improve and optimize the air exchange flow in the lungs by adjusting the respiratory settings during mechanical ventilation. Electrical impedance tomography (EIT) is a monitoring tool that permits measurement of regional pulmonary filling characteristics or filling index (FI) during ventilation. The conventional EIT system has limitations which compromise the accuracy of the FI. This paper proposes a novel and automated methodology for accurate FI estimation based on EIT images of recruitable regional collapse and hyperdistension during incremental positive end-expiratory pressure. It identifies details of the airway tree (AT) to generate a correction factor to the FIs providing an accurate measurement. Multi-scale image enhancement followed by identification of the AT skeleton with a robust and self-exploratory tracing algorithm is used to automatically estimate the FI. AT tracing was validated using phantom data on a ground-truth lung. Based on generated phantom EIT images, including an established reference, the proposed method results in more accurate FI estimation of 65% in all quadrants compared with the current state-of-the-art. Measured regional filling characteristics were also examined by comparing regional and global impedance variations in clinically recorded data from ten different subjects. Clinical tests on filling characteristics based on extraction of the AT from the resolution enhanced EIT images indicated a more accurate result compared with the standard EIT images.

Surfactant Treatment Shows Higher Correlation Between Ventilator and EIT Tidal Volumes in an RDS Animal Model.

Neonatal respiratory distress syndrome (RDS) is a condition of pulmonary surfactant insufficiency in the premature newborn. As such, artificial pulmonary surfactant administration is a key treatment. Despite continued improvement in the clinical outcomes of RDS, there are currently no established bedside tools to monitor whether pulmonary surfactant is effectively instilled throughout the lungs. Electrical impedance tomography (EIT) is an emerging technique in which physiological functions are monitored on the basis of temporal changes in conductivity of different tissues in the body. In this preliminary study, we aimed to assess how EIT tidal volumes correlate with ventilator tidal volumes in an RDS animal model, namely untreated, surfactant-treated, and normal control rabbit pups. Tidal volumes were measured simultaneously on an EIT system and a mechanical ventilator and compared at different peak inspiratory pressures. The linear correlation between tidal volumes measured by EIT and by ventilator had an R 2 of 0.71, 0.76 and 0.86 in the untreated, surfactant-treated, and normal control groups, respectively. Bland–Altman analysis showed a good correlation between the measurements obtained with these two modalities. The intraclass correlation coefficients (ICC) between ventilator tidal volume and EIT tidal volume were 0.83, 0.87, and 0.93 (all p < 0.001) in the untreated, surfactant-treated, and normal control groups, respectively, indicating that the higher ICC value, the better inflated status of the lung. In conclusion, we demonstrated that EIT tidal volume correlated with ventilator tidal volume. ICC was higher in the surfactant treated group.

Improvement of performance and sensitivity of 2D and 3D image reconstruction in EIT using EFG forward model

This paper presents a pure element-free Galerkin method (EFGM) forward model for image reconstruction in 2D and 3D electrical impedance tomography (EIT) using an adaptive current injection method. In EIT systems with the adapting current injection method, both static and dynamic images can be reconstructed; however, determination of electrode contact impedances in the complete electrode model is difficult and the Gap model is used. In this paper, in the EIT forward problem a weak form functional based on the Gap model and a pure EFGM approach are developed, and in the EIT inverse problem, Jacobian matrix is computed by the EFGM, and a fast integration technique is introduced to calculate the entries of the Jacobian matrix within an adequate computation time. The influence of increasing the density of nodes at and near the electrodes with steep electric potential gradients on the accuracy of FEM and EFGM forward solutions is investigated, and the performance of the image reconstruction algorithm with the proposed fast integration technique is examined. The numerical results reveal that the proposed EFGM forward model with the fast integration technique has an efficient performance both in terms of mean relative imaging errors and computational time.

A DSP-Based EIT System With Adaptive Boundary Voltage Acquisition

Electrical Impedance Tomography (EIT), a valuable technique modality for estimating electrical properties of an object by electrode measurements. During the measurement process, high-frequency excitation signal and the large dynamic range of boundary voltage both cause negative effects on system detection accuracy. Focusing on the induced signal detection, we proposed an adaptive boundary voltage acquisition method, which thoroughly modeled the EIT system by LTSPICE and MATLAB, dynamically adjusted the boundary voltage amplitude gain according to the induced signal voltage range, and changed sampling period for high frequency component of excitation signal. A DSP-based EIT hardware experimental platform under development was constructed, including a current source integrated direct digital synthesis and data acquisition circuit. The data acquisition circuit composed of programmable differential amplifier, low-pass filter and offset adjustment circuit is used for signal acquisition. Comparative experiments are systematically implemented for evaluating the proposed method. Quantitatively, the SNR difference of each measurement channel is reduced from 26.42dB to 6.33dB. The maximum SNR of the system can reach 60.67dB. The maximum image error (IE) is reduced from 28.17% to 15.60%. Accordingly, the proposed adaptive boundary voltage acquisition method is proved to be great beneficial to improve EIT system accuracy.

Wearable Electrical Impedance Tomography Belt With Dry Electrodes.

Electrical impedance tomography (EIT) is a noninvasive imaging technology used to reconstruct the conductivity distribution in objects and the human body. In recent years, numerous EIT systems and image reconstruction algorithms have been developed. However, most of these EIT systems require conventional electrodes with conductive gels (wet electrodes) and cannot be adapted to different body types, resulting in limited applicability. In this study, a wearable wireless EIT belt with dry electrodes was designed to enable EIT imaging of the human body without using wet electrodes. The specific design of the belt mechanism and dry electrodes provide the advantages of easy wear and adaptation to different body sizes. Additionally, the Gauss-Newton method was used to optimize the EIT image. Finally, experiments were performed on the phantom and human body to validate the performance of the proposed EIT belt. The results demonstrate that the proposed system can provide accurate location information of the objects in the EIT image and the system can be successfully applied for noninvasive measurement of the human body.

Scalp-Mounted Electrical Impedance Tomography of Cerebral Hemodynamics.

An Electrical Impedance Tomography (EIT) system has been developed for dynamic three-dimensional imaging of changes in conductivity distribution in the human head, using scalp-mounted electrodes. We attribute these images to changes in cerebral perfusion. At 100 frames per second (fps), voltage measurement is achieved with full-scale signal-to-noise ratio of 105 dB and common-mode rejection ratio > 90 dB. A novel nonlinear method is presented for 3-D imaging of the difference in conductivity distribution in the head, relative to a reference time. The method achieves much reduced modelling error. It successfully localizes conductivity inclusions in experimental and simulation tests, where previous methods fail. For > 50 human volunteers, the rheoencephalography (REG) waveform is observed in EIT voltage measurements for every volunteer, with peak-to-peak amplitudes up to approx. 50 μVrms. Images are presented of the change in conductivity distribution during the REG/cardiac cycle, at 50 fps, showing maximum local conductivity change of approx. 1% in grey/white matter. A total of 17 tests were performed during short (typically 5s) carotid artery occlusions on 5 volunteers, monitored by Transcranial Doppler ultrasound. From EIT measurements averaged over complete REG/cardiac cycles, 13 occlusion tests showed consistently decreased conductivity of cerebral regions on the occluded side, and increased conductivity on the opposite side. The maximum local conductivity change during occlusion was approx. 20%. The simplicity of the carotid artery intervention provides a striking validation of the scalp-mounted measurement system in imaging cerebral hemodynamics, and the REG images indicate its unique combination of sensitivity and temporal resolution.

A Modified Noise Model of Electrical Impedance Tomography System by Considering Colored Noises

Sufficient signal-to-noise ratio (SNR) is critical to guarantee the satisfactory performance of an electrical impedance tomography (EIT) system. In this article, a thorough SNR analysis of EIT systems is presented. Besides the well-known random noise, the influences of colored noises, such as switching noise, low-frequency noise, and harmonic noise, are considered. By investigating the colored noises, a novel noise model of electrical impedance tomography systems is first proposed, which is validated by both simulation and experiment conducted in a laboratory-built electrical impedance tomography system. Finally, different conventional methods to reduce the colored noises are discussed and associated circuit-level considerations are evaluated by applying a front-end isolation structure in the laboratory-built EIT system. Overall, this work provides a more practical noise model of electrical impedance tomography systems by including the colored noises. It can serve as a guide to improve the SNR and therefore the performance of an electrical impedance tomography system for high-demanding biomedical applications.

Design of multi-frequency electrical impedance tomography system based on multisine excitation and integer-period sampling

Starting from the principle that the integer-period sampling (IPS) of periodic signals is free of spectrum leakage, in this paper we propose the multisine-IPS theory, deduce theoretically the sampling rate setting formula of multisine-IPS condition for the first time, and build its realization method based on field-programmable gate array (FPGA) plus digital-to-analog converter (DAC) plus analog-to-digital converter (ADC). A new multi-frequency electrical impedance tomography (mfEIT) system based on multisine excitation and its IPS theory is developed, and a dual-target imaging model including a carrot stick and a cucumber stick is designed. The experiments of multi-frequency time-difference imaging and frequency-difference imaging are carried out on the mfEIT system. The experimental results show that the newly-designed mfEIT system can achieve full-band impedance measurements on multiple objective tissue boundary at 20 frequency points (2–997 kHz) within one fundamental period (1 ms), and the structure and position of biological tissues with different electrical properties can also be distinguished from the resulting images. The proposed multisine-IPS theory and its implementation method can complete a full-band impedance measurement within one multisine fundamental period, which lays a theoretical and technical foundation for developing high-speed mfEIT system.

Design Automation of a Dynamic Thorax-Like Mesh Phantom for Evaluating the Performance of Electrical Impedance Tomography System

Abstract&#x2014;Phantoms are used to evaluate, calibrate, and compare the performance of electrical impedance tomography (EIT) systems. This paper presents a dynamic thorax-like mesh phantom, which mimics the changes in electrical conductivity distribution within a human thorax at different time frames. Furthermore, element merging and contour smoothing, electrode placement techniques, and PCB design automation methods are proposed to simplify, optimize the mesh phantom, and reduce the hardware implementation cost. To verify the accuracy of the mesh phantom and its PCB, SPICE simulations and experimental testings are performed to obtain the conductance of the mesh phantom and reconstruct the images through the EIDORS software. These images achieve an image correlation coefficient (ICC) of 0.680 (model versus SPICE simulation) and 0.9098 (SPICE simulation versus measurement result), respectively. This demonstrates the validity of our proposed dynamic thorax-like mesh phantom.

Design of a High Linearity Sinusoidal Current Generator Using Shifting Current Mirror Architecture

To develop a simple current generator (CG) for bio-impedance (BioZ) and electrical impedance tomography (EIT) systems, this paper proposes using a shifting-current-mirror (S-CM) architecture to realize a high linearity sinusoidal CG. The proposed S-CM CG controls the amplitude of its output by selecting the unit elements using data weighted averaging (DWA) at every clock cycle, thus suppressing the mismatch. The proposed current generator has shown an improvement in the average signal-to-noise-and-distortion ratio (SNDR) of up to 4.78 dB with DWA for resolutions up to 14 bits and has high linearity for resolutions up to 14 bits, 12 bits, and 10 bits while having area savings of 5×, 10×, and 20×, respectively.

A Methodology to Assist in Improvements of Low-cost Electrical Impedance Tomography Systems

Electrical Impedance Tomography (EIT) is a technique that enables the reconstruction of the impedance distributions inside a vessel in a multiphase flow of industrial processes. Such a technique combines a data acquisition (DAQ) system to inject a current and to measure the voltages on the sensors and an inverse problem technique to reconstruct the image properly. This problem is highly ill-conditioned, causing errors to produce instabilities. Therefore, when performing the acquisition, the DAQ system must have adequate accuracy to allow the reconstruction of images with good quality. To avoid these measurement inaccuracies, this paper introduces a methodology that aid in the process of development of low-cost systems. It consists of investigating the errors in the current version of the system. Further, predicting the systematic errors of each subsystem by modeling its frequency response by Simulation Program with Integrated Circuit Emphasis (SPICE). From this information, it is possible to perform critical analysis, aiding design decisions.

Experimental evaluation of some current injection-voltage reading patterns in electrical impedance tomography (EIT) and comparison to simulation results - Case study: Large scales

Each electrical impedance tomography system to be prosper, usually would had its own current injection and voltage reading patterns within domains under test. So in different domains, each of sensing patterns have different performances. In industrial application for conductive carrier-phases and in large domains, impedance imaging of real phantoms would be advisable candidate for better performance. Therefore in this study, performance of five sensing patterns in a large scale (outer diameter of 700 mm) were evaluated. Based on the sensing patterns, parameters such as; applicability in the domain and online mode, voltage signal-to-noise ratio (SNR), boundary voltage changes (BVC), sensitivity distributions, size error (SE) and ringing, in different object locations were studied by simulation and experimentally. The results illustrated that there is a significant difference between the reconstruction images of simulation and experimental data in the patterns with low SNR. Also, in a pattern with high SNR, due to the low BVC, the desired performance was not achieved. The highest correlation in the image reconstruction of the simulation and experimental data was obtained in the Opposite-Adjacent pattern with high SNR and BVC. The results show that the selection of this sensing pattern can improve the object's SE up to 0.68%.