Electrical Impedance Tomography System Research Articles

Development and Validation of a Portable EIT System for Real-Time Respiratory Monitoring.

This work contributes to the improvement of novel medical technologies for the prevention and treatment of diseases. Electrical impedance tomography (EIT) has gained attention as a valuable tool for non-invasive monitoring providing real-time insights. The purpose of this work is to develop and validate a novel portable EIT system with a small form factor for respiratory monitoring. The device uses a 16-electrode architecture with adjacent stimulation and measurement patterns, an integrated circuit current source and a single high-speed ADC operating with multiplexers to stimulate and measure across all electrodes. Tests were conducted on 25 healthy subjects who performed a pulmonary function test with a flowmeter while using the EIT device. The results showed a good performance of the device, which was able to recognize all respirations correctly, and from the EIT signals and images, correlations of 96.7% were obtained for instantaneous respiratory rate and 96.1% for tidal volume prediction. These results validate the preliminary technical feasibility of the EIT system and demonstrates its potential as a reliable tool for non-invasive respiratory assessment. The significance of this work lies in its potential to democratize advanced respiratory monitoring technologies, making them accessible to a wider population, including those in remote or underserved areas.

Modular and Portable System Design for 3D Imaging of Breast Tumors Using Electrical Impedance Tomography

This paper presents a prototype of a portable and modular electrical impedance tomography (EIT) system for breast tumor detection. The proposed system uses MATLAB to generate three-dimensional representations of breast tissue. The modular architecture of the system allows for flexible customization and scalability. It consists of several interconnected modules. Each module can be easily replaced or upgraded, facilitating system maintenance and future enhancements. Testing of the prototype has shown promising results in preliminary screening based on experimental studies. Agar models were used for the experimental stage of this project. The 3D representations provide clinicians with valuable information for accurate diagnosis and treatment planning. Further research and refinement of the system is warranted to validate its performance in future clinical trials.

Remotely Powered Two-Wire Cooperative Sensors for Bioimpedance Imaging Wearables.

Bioimpedance imaging aims to generate a 3D map of the resistivity and permittivity of biological tissue from multiple impedance channels measured with electrodes applied to the skin. When the electrodes are distributed around the body (for example, by delineating a cross section of the chest or a limb), bioimpedance imaging is called electrical impedance tomography (EIT) and results in functional 2D images. Conventional EIT systems rely on individually cabling each electrode to master electronics in a star configuration. This approach works well for rack-mounted equipment; however, the bulkiness of the cabling is unsuitable for a wearable system. Previously presented cooperative sensors solve this cabling problem using active (dry) electrodes connected via a two-wire parallel bus. The bus can be implemented with two unshielded wires or even two conductive textile layers, thus replacing the cumbersome wiring of the conventional star arrangement. Prior research demonstrated cooperative sensors for measuring bioimpedances, successfully realizing a measurement reference signal, sensor synchronization, and data transfer though still relying on individual batteries to power the sensors. Subsequent research using cooperative sensors for biopotential measurements proposed a method to remove batteries from the sensors and have the central unit supply power over the two-wire bus. Building from our previous research, this paper presents the application of this method to the measurement of bioimpedances. Two different approaches are discussed, one using discrete, commercially available components, and the other with an application-specific integrated circuit (ASIC). The initial experimental results reveal that both approaches are feasible, but the ASIC approach offers advantages for medical safety, as well as lower power consumption and a smaller size.

A solar-driven hygroscopic aerogel using electrical impedance tomography for exploiting differentiated photothermal interfaces

Photothermal materials and structures are essential for the actual performance of interfacial solar-steam generation systems in atmospheric water harvesting (AWH) technologies. However, the absence of theoretical insights into water desorption, diffusion, and heat transfer at the photothermal interface can impede the development of efficient solar interfacial AWH technologies. To address this gap, we introduce an in-situ imaging approach utilizing the electrical impedance tomography (EIT) system to dynamically visualize the water desorption process within aerogels in real time. The visualization outcomes highlight that the effectiveness of moisture desorption in aerogels is influenced by critical factors, including heat concentration, the localization of heating and cooling, and minimal diffusion resistance. Furthermore, the microstructure and temperature disparities on different sides drive internal water movement and evaporation. The proposed design of the generalized EIT visualization detection system aims to reveal the desorption kinetics of highly efficient solar-driven AWH materials, paving the way for a new frontier in studying the interfacial solar-steam generation process.

A GUI-BASED DATA ACQUISITION SYSTEM FOR EIT USING TWO CURRENT INJECTION METHODS

The current injection method played an essential role in the data quality of impedance measurement using the electrical impedance tomography (EIT) technique. Previous studies have largely utilized only a single current injection method with limited interface access, which restricts the effectiveness of EIT systems. In this paper, a graphical user interface (GUI)-based data acquisition system was designed to improve user interaction and optimize the control system. The system was equipped with multiple current injection methods, allowing researchers to choose which method to use in the measurement process. The designed hardware comprises a V-to-I converter circuit, multiplexer, electrodes, peak detector, and filter circuit. Testing results indicate that the V to I converter circuit has an average peak difference between voltage and current of 4.86% and an average error of 0.69% in the peak detector circuit. The multiplexer circuit switches quickly and consistently, while the filter circuit remains stable at the 50 kHz frequency used in this study. These results demonstrate that the designed circuits perform adequately and effectively, ensuring reliable and accurate measurements. Additionally, the data acquisition software, presented as a GUI, effectively facilitates the selection of current injection methods and the display of boundary data simulation (BDS) on the object. This is demonstrated by the spatial inhomogeneity patterns visible through BDS in both the adjacent and opposite methods

Electrical impedance tomography provides information of brain injury during total aortic arch replacement through its correlation with relative difference of neurological biomarkers

Postoperative neurological dysfunction (PND) is one of the most common complications after a total aortic arch replacement (TAAR). Electrical impedance tomography (EIT) monitoring of cerebral hypoxia injury during TAAR is a promising technique for preventing the occurrence of PND. This study aimed to explore the feasibility of electrical impedance tomography (EIT) for warning of potential brain injury during total aortic arch replacement (TAAR) through building the correlation between EIT extracted parameters and variation of neurological biomarkers in serum. Patients with Stanford type A aortic dissection and requiring TAAR who were admitted between December 2021 to March 2022 were included. A 16-electrode EIT system was adopted to monitor each patient’s cerebral impedance intraoperatively. Five parameters of EIT signals regarding to the hypothermic circulatory arrest (HCA) period were extracted. Meanwhile, concentration of four neurological biomarkers in serum were measured regarding to time before and right after surgery, 12 h, 24 h and 48 h after surgery. The correlation between EIT parameters and variation of serum biomarkers were analyzed. A total of 57 TAAR patients were recruited. The correlation between EIT parameters and variation of biomarkers were stronger for patients with postoperative neurological dysfunction (PND(+)) than those without postoperative neurological dysfunction (PND(−)) in general. Particularly, variation of S100B after surgery had significantly moderate correlation with two parameters regarding to the difference of impedance between left and right brain which were MRAIabs and TRAIabs (0.500 and 0.485 with p < 0.05, respectively). In addition, significantly strong correlations were seen between variation of S100B at 24 h and the difference of average resistivity value before and after HCA phase (ΔARVHCA), the slope of electrical impedance during HCA (kHCA) and MRAIabs (0.758, 0.758 and 0.743 with p < 0.05, respectively) for patients with abnormal S100B level before surgery. Strong correlations were seen between variation of TAU after surgery and ΔARVHCA, kHCA and the time integral of electrical impedance for half flow of perfusion (TARVHP) (0.770, 0.794 and 0.818 with p < 0.01, respectively) for patients with abnormal TAU level before surgery. Another two significantly moderate correlations were found between TRAIabs and variation of GFAP at 12 h and 24 h (0.521 and 0.521 with p < 0.05, respectively) for patients with a normal GFAP serum level before surgery. The correlations between EIT parameters and serum level of neurological biomarkers were significant in patients with PND, especially for MRAIabs and TRAIabs, indicating that EIT may become a powerful assistant for providing a real-time warning of brain injury during TAAR from physiological perspective and useful guidance for intensive care units.

Bulk resistance and contact impedance: Particular solution for annulus, homogeneous domain and dimensional analysis of the complete electrode model

Viewing the complexity of multiphase flows, in which multi-dimensional and time-changing fluid structures, known as flow patterns, must be captured, electrical impedance tomography (EIT) stands out as an alternative for fluid flow visualization. Using an EIT system, this study presents an enhanced approach for measuring film thickness in two-phase flows. Incorporating bulk resistance and contact impedance contributions, the proposed ohmic model significantly improves accuracy, particularly in low-conductivity scenarios, yielding a robust, accurate, and rapid technique for obtaining images from an EIT-based low-cost acquisition system. Tomographic experiments validate the model’s efficacy using cylindrical sensors and diverse conductivity mediums, including two distinct phantoms. The dimensional analysis of the model yields five dimensionless numbers, revealing interrelations between electrical parameters and sensor construction. A correlation based on a dimensionless number for the contact impedance is obtained. Additionally, the experiments demonstrate a strong interplay with the polarization phenomenon.

Electrode module for EIT with a robust howland current source

Electrical Impedance Tomography (EIT) is a non-invasive imaging technique that reconstructs internal conductivity distributions of a body from electrical measurements taken on its boundary. This study contributes to the field by focusing on the technological intricacies of absolute EIT imaging, which is challenged by limitations such as the resolution capacity of the hardware and the complexities introduced by imaging capacitive bodies. The novel EIT system architecture proposed enhances the accuracy of measurement by integrating current sources and Analog-to-Digital Converters (ADCs) closer to the electrodes, employing alternating current excitations to accurately capture phase information. This system uses a dynamic arrangement of surface electrodes that continuously alter their roles between current injection and voltage measurement, in a synchronized sequence, to ensure the accuracy of the measurements. The paper describes the design and implementation of both the excitation and measurement subsystems, highlighting the use of digital signal demodulation near the electrode to reduce data transfer issues. Experimental results confirm the system’s capability for real-time image reconstruction at 50 frames per second with precision in phase delay measurements, suggesting significant potential for clinical and industrial applications. Future work will aim to further refine signal generation with higher-speed DACs and expand to image reconstruction with more channels.

In situ Electrical Impedance Tomography for Visualizing Water Transportation in Hygroscopic Aerogels.

The global water crisis demands immediate attention, and atmospheric water harvesting (AWH) provides a viable alternative. However, studying the real-time subtle relationship between water absorption, diffusion, and internal structure for hygroscopic materials is challenging. Herein, a dynamic visualization technique is proposed that utilizes an in situ electrical impedance tomography (EIT) system and a precise reconstruction algorithm to achieve real-time monitoring of the water sorption process within aerogels from an internal microstructural perspective. These results can be inferred that composites' pore sizes affecting the kinetics of their moisture absorption. In addition, the diffusion path of moisture absorption and the distribution of stored moisture inside aerogels exhibit intrinsic self-selective behavior, where the fiber skeleton of the aerogel plays a crucial role. In summary, this work proposes a generic EIT-based technique for the in situ and dynamic monitoring of the hygroscopic process, pointing to an entirely new approach regarding research on AWH materials.

Electrical Impedance Tomography for Real-Time Monitoring of Muscle Activity in Robot-Assisted Rehabilitation

This work looks at how Electrical Impedance Tomography (EIT) can be used in robot-assisted rehabilitation to make it easier to watch how muscle activity changes in real time. Quantitative methods are used in this study to look into how well EIT works, including full analyses and comparisons with common tracking methods like Electromyography (EMG). Both EIT and EMG are used to record the participants' mean and peak muscle activation levels as they do a set of Upper Limb, Lower Limb, and Full Body exercises. The study's findings show that EIT is incredibly flexible when it comes to capturing complex patterns of muscle activation across a wide range of rehabilitation routines. Each participant's involvement is shown by different patterns of muscle activation, and these patterns can be seen across different types of exercise. We can learn a lot about how muscles work during rehabilitation by measuring their mean and peak activation levels. This helps us see how well EIT works as a tracking tool. A very important step in validating EIT is to compare it to EMG readings. This shows how consistent and accurate EIT is in real-time monitoring situations. The high level of agreement between the two methods shows that EIT is a reliable alternative to standard monitoring methods, providing an easy to use and non-invasive way to measure muscle activity. The results of this study are even stronger because they include quantitative analyses and a detailed look at system performance data. We carefully check things like signal-to-noise ratio, reconstruction accuracy, and reliability, which shows how strong and dependable the combined EIT system is. These metrics are important for showing how well the system can measure things accurately and reliably in changing rehabilitation situations. This study adds to the growing amount of research on EIT uses in rehabilitation by showing that it can be a useful tool for keeping track of real-time muscle activity. This study opens the door for EIT to be widely used in rehabilitation by showing how muscle activation changes over time and proving its effectiveness against well-known methods. This will eventually lead to better patient outcomes and more effective rehabilitation.

A Wearable Open-Source electrical impedance tomography device

Electrical impedance tomography (EIT) is medical imaging technique in which small electrical signals are used to map the electrical impedance distribution within the body. It is safe and non-invasive, which make it attractive for use in continuous monitoring or outpatient applications, but the high cost of commercial devices is an impediment to its adoption. Over the last 10 years, many research groups have developed their own EIT devices, but few designs for open-source EIT hardware are available. In this work, we present a complete open-source EIT system that is designed to be suitable for monitoring the lungs of free breathing subjects. The device is low-cost, wearable, and is designed to comply with the industry accepted safety standard for EIT. The device has been tested in two regimes: Firstly in terms of measurement uncertainty as a voltage measurement system, and secondly against a set of measures that have been proposed specifically for EIT hardware. The voltage measurement uncertainty of the device was measured to be − 0.7 % ± 0.36 mV. The EIT specific performance was measured in a phantom test designed to be as physiologically representative as practicable, and the device performed similarly to other published devices. This work will contribute to increased accessibility of EIT for study and will contribute to consensus on testing methodology for EIT devices.

A multi-scale attention residual-based U-Net network for stroke electrical impedance tomography.

Electrical impedance tomography (EIT), a non-invasive, radiation-free, and convenient imaging technique, has been widely used in the diagnosis of stroke. However, due to soft-field nonlinearity and the ill-posed inverse problem, EIT images always suffer from low spatial resolution. Therefore, a multi-scale convolutional attention residual-based U-Net (MARU-Net) network is proposed for stroke reconstruction. Based on the U-Net network, a residual module and a multi-scale convolutional attention module are added to the concatenation layer. The multi-scale module extracts feature information of different sizes, the attention module strengthens the useful information, and the residual module improves the performance of the network. Based on the above advantages, the network is used in the EIT system for stroke imaging. Compared with convolutional neural networks and one-dimensional convolutional neural networks, the MARU-Net network has fewer artifacts, and the reconstructed image is clear. At the same time, the reduction of noisy artifacts in the MARU-Net network is verified. The results show that the image correlation coefficient of the reconstructed image with noise is greater than 0.87. Finally, the practicability of the network is verified by a model physics experiment.

Design of Three-Dimensional Electrical Impedance Tomography System for Rock Samples

Research on the electrical properties of rocks and ores plays a crucial role in the development of geophysical electromagnetism methods. However, currently available instruments suffer from high power consumption, a limited number of electrodes, inaccurate measurements, poor portability, and a limited ability to measure the electrical parameters of rocks and ores. To address these issues, this paper presents a three-dimensional electrical impedance tomography system for rock samples with high-density microelectrodes based on an Android system and STM32 microcontroller. The system features high observation accuracy, dense electrode arrays (with 384 current and potential electrodes), flexible electrode selection, user-friendly human–computer interaction, good stability, and real-time performance. Powered by a single power bank, the entire instrument can be controlled and monitored wirelessly via Bluetooth and Wi-Fi technology using an Android smartphone. Additionally, the system not only enables accurate measurement of electrical parameters, but also facilitates the generation of three-dimensional impedance imaging of specimens via inversion algorithms after data export, allowing for a comprehensive understanding of the electrical properties of rocks and ores. This system holds great potential for future research in this field.

Flexi-EIT: A Flexible and Reconfigurable Active Electrode Electrical Impedance Tomography System.

Electrical Impedance Tomography (EIT) systems have shown great promise in many fields such as real-time wearable healthcare imaging, but their fixed number of electrodes and placement locations limit the system's flexibility and adaptability for further advancement. In this article, we propose a flexible and reconfigurable EIT system (Flexi-EIT) based on digital active electrode (DAE) architecture to address these limitations. By integrating a reconfigurable number of up to 32 replaceable DAEs into the flexible printed circuit (FPC) based wearable electrode belt, we can enable rapid, reliable, and easy placement while maintaining high device flexibility and reliability. We also explore hardware-software co-optimization image reconstruction solutions to balance the size and accuracy of the model, the power consumption, and the real-time latency. Each DAE is designed using commercial chips and fabricated on a printed circuit board (PCB) measuring 13.1 mm × 24.4 mm and weighing 2 grams. In current excitation mode, it can provide programmable sinusoidal current signal output with frequencies up to 100 kHz and amplitudes up to 1 mA p-p that meets IEC 60601-1 standard. In voltage acquisition mode, it can pre-amplify, filter, and digitize the external response voltage signal, improving the robustness of the system while avoiding the need for subsequent analog signal processing circuits. Measured results on a mesh phantom demonstrate that the Flexi-EIT system can be easily configured with different numbers of DAEs and scan patterns to provide EIT measurement frames at 38 fps and real-time EIT images with at least 5 fps, showing the potential to be deployed in a variety of application scenarios and providing the optimal balance of system performance and hardware resource usage solutions.

A CV weighted method for oil-water two-phase flow of non-contact multi-frequency el7ectrical impedance tomography

Electrical tomography (ET) technology has attracted extensive attention in the field of scientific research on oil–water two-phase flow due to its advantages of non-intrusion, non-radiation, and simple equipment structure. Affected by Maxwell–Wagner-Sillars (MWS) effect, more imaging information can be obtained by changing the excitation frequency, especially for the mixtures with conductive phases. In this paper, a CV (coefficient of variation )-weighted method of non-contact multi-frequency electrical impedance tomography (NM-EIT) system is carried out for water-oil two-phase flow imaging. Firstly, the frequency response of the measurement system is studied and the electrical impedance information of medium in the region of interest (RoI) is observed. Secondly, the measured electrical impedance information with with different excitation frequencies are weighted by CV method. Finally, combined with the classic image reconstruction algorithm, the simulation and static experiment are carried out to verify the reconstruction effect of the proposed method. The imaging accuracies under different frequencies and flow patterns are analyzed, and a measurement experimental platform is set up to verify the reconstruction effect of the proposed method. The experimental results show that the CV-based multi-frequency weighted method maintains a higher imaging accuracy than single-frequency imaging.

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Objective. Wearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers. Approach. A total of 96 test sets of EIT measurement was recorded in 12 healthy subjects by employing adjacent and opposite current injection patterns with four amplitudes of small current (i.e. 1 mA, 500 uA, 250 uA and 125 uA). The performance of the two injection patterns with various currents was evaluated in terms of signal-to-noise ratio (SNR) of thorax impedance, EIT image metrics and EIT-based clinical parameters. Main results. Compared with adjacent injection, opposite injection had higher SNR (p < 0.01), less inverse artifacts (p < 0.01), and less boundary artifacts (p < 0.01) with the same current amplitude. In addition, opposite injection exhibited more stable EIT-based clinical parameters (p < 0.01) across the current range. For adjacent injection, significant differences were found for three EIT image metrics (p < 0.05) and four EIT-based clinical parameters (p < 0.01) between the group of 125 uA and the other groups. Significance. For better performance of wearable pulmonary EIT, currents greater than 250 uA should be used in opposite injection, 500 uA in adjacent one, to ensure a high level of SNR, a high quality of reconstructed image as well as a high reliability of clinical parameters.

Development of a Low-Cost and Compact Medical Image Reconstruction Platform Based on EIT Technique

Electrical impedance tomography (EIT) is an important imaging modality in non-invasive and radiation-free image reconstruction techniques. With the advantages of real-time imaging capabilities, portability, and safety features, EIT has acquired substantial significance as a valuable technique for lung patients during the COVID-19 pandemic. Nevertheless, a significant challenge arises when many COVID-19 patients need to utilize EIT devices for monitoring and treatment. To address this problem, a low-cost and compact wireless communication EIT platform was developed for impedance image reconstruction and real-time monitoring of human lung operations. Since the system was structured as a platform, it can be readily replicated and scaled up in emergencies. The proposed system consisted of 16 electrodes placed on the chest of the lung patients. A stable current was injected into the object through a pair of adjacent electrodes, while the voltage was measured on the remaining electrode pairs using a lock-in amplifier. The electrical impedance between each electrode pair was determined based on Ohm’s law. Experimental results showed that the system could reconstruct the shape and the position of objects inside the medium with high accuracy. The average blur radius and percentage of the location error of the reconstructed image were 1.01 ± 0.28 and 5.18 ± 1.35%, respectively. Furthermore, images showing the operation of the human lung were also observed by the proposed system, confirming the possibility of using the system in clinical applications. The proposed EIT system with wireless communication is a potential study for large-scale implementation, particularly in response to the COVID-19 pandemic.

ACT5 Electrical Impedance Tomography System.

This article introduces the Adaptive Current Tomograph 5 (ACT5) Electrical Impedance Tomography (EIT) system. ACT5 is a 32 electrode applied-current multiple-source EIT system that can display real-time images of conductivity and susceptivity at 27 frames per second. The adaptive current sources in ACT5 can apply fully programmable current patterns with frequencies varying from 5 kHz to 500 kHz. The system also displays real-time ECG readings during the EIT imaging process. The hardware and software design and specifications are presented, including the current source design, FPGA hardware, safety features, calibration, and shunt impedance measurement. Images of conductivity and susceptivity are presented from ACT5 data collected on tank phantoms and a human subject illustrating the system's ability to provide real-time images of pulsatile perfusion and ECG traces. The portability, high signal-to-noise ratio, and flexibility of applied currents over a wide range of frequencies enable this instrument to be used to obtain useful human subject data with relative clinical ease.

A low-cost, portable 32-channel EIT system with four rings based on AFE4300 for body composition analysis

A proposed low-cost, portable, 32-channel (4 rings of 8-channel) Electrical Impedance Tomography (EIT) system based on the AFE4300 analog front-end for body composition measurement. Each ring allows obtaining the conductivity distribution of 4 cross sections, 4 cm apart; to analyze the behavior of conductivity in a volume. The switching of the 4 rings and the current injection and voltage measurement patterns are done with three Texas Instruments 74HC4067 multiplexers, which are managed by an ESP32 board. The proposed system has an average signal-to-noise ratio of 74.71 dB and a frame rate of 50 fps. The sensitivity tests to impedance and volume changes consisted of introducing 4 tubes of different diameters (2 steel and 2 polyvinyl chloride) into a tank with saline solution; then conductivity distribution images were generated in 4 cross-sections of the tank, using the algorithms Gauss-Newton and Noser. Finally, the global impedance index (GI) is calculated to estimate the volume of each tube inside the tank. The results show that the proposed system is highly sensitive to impedance and volume changes, being a promising system for monitoring tissues, and fluids biological.

Recent Prospects of Medical Imaging and Sensing Technologies Based on Electrical Impedance Data Acquisition System

This paper presents a cost-effective data acquisition & medical imaging system using electrical impedance tomography (EIT). The presented method investigates & analyses the output image retrieved from the electrical conductivity distribution of a test object or phantom. The image reconstruction was performed using a modified imaging algorithm. The experimental setup of the proposed system mainly consists of convertible 16/8/4 electrodes (which are the phantom circumference attached), the accurate static Current Source (Milli Ampere Current with KHz Frequency) for providing current which passes into the boundary of an object through a different pair of electrodes. The output of electrodes is acquired as a voltage that is measured from the boundary of the conductive object of other electrodes pair and fed into a computer for the appropriate computing of the acquired data. EIT systems with GUI are used in the data collection procedure to provide a user-friendly interface for effective picture reconstruction, which is used both like offline and online functioning are possible. Performance testing was carried out utilizing a variety of phantom models that represented human test subjects and different physical objects. The data acquisition (DAQ) techniques used in EIT produced findings that were innovative, comparable and showed enhanced sensitivity, functionality for engineering society.