Search Results (179)

The grounding grid is an important piece of equipment to ensure the safety of a power system, and thus research detecting on its corrosion status is of great significance. Electrical impedance tomography (EIT) is an effective method for grounding grid corrosion imaging. However, the inverse process of image reconstruction has pathological solutions, which lead to unstable imaging results. This paper proposes a grounding grid electrical impedance imaging method based on an improved conditional generative adversarial network (CGAN), aiming to improve imaging precision and accuracy. Its generator combines a preprocessing module and a U-Net model with a convolutional block attention module (CBAM). The discriminator adopts a PatchGAN structure. First, a grounding grid forward problem model was built to calculate the boundary voltage. Then, the image was initialized through the preprocessing module, and the important features of ground grid corrosion were extracted again through the encoder module, decoder module and attention module. Finally, the generator and discriminator continuously optimized the objective function and conducted adversarial training to achieve ground grid electrical impedance imaging. Imaging was performed on grounding grids with different corrosion conditions. The results showed a final average peak signal-to-noise ratio of 20.04. The average structural similarity was 0.901. The accuracy of corrosion position judgment was 94.3%. The error of corrosion degree judgment was 9.8%. This method effectively improves the pathological problem of grounding grid imaging and improves the precision and accuracy, with certain noise resistance and universality. Full article

As a non-invasive imaging method, electrical impedance tomography (EIT) technology has become a research focus for grounding grid corrosion diagnosis. However, the existing algorithms have not produced ideal image reconstruction results. This article proposes an electrical impedance imaging method based on sparse representation, which can improve the accuracy of reconstructed images obviously. First, the basic principles of EIT are outlined, and the limitations of existing reconstruction methods are analyzed. Then, an EIT reconstruction algorithm based on sparse representation is proposed to address these limitations. It constructs constraints using the sparsity of conductivity distribution under a certain sparse basis and utilizes the accelerated Fast Iterative Shrinkage Threshold Algorithm (FISTA) for iterative solutions, aiming to improve the imaging quality and reconstruction accuracy. Finally, the grounding grid model is established by COMSOL simulation software to obtain voltage data, and the reconstruction effects of the Tikhonov regularization algorithm, the total variation regularization algorithm (TV), the one-step Newton algorithm (NOSER), and the sparse reconstruction algorithm proposed in this article are compared in MATLAB. The voltage relative error is introduced to evaluate the reconstructed image. The results show that the reconstruction algorithm based on sparse representation is superior to other methods in terms of reconstruction error and image quality. The relative error of the grounding grid reconstructed image is reduced by an average of 12.54%. Full article

Background/Objectives: The induction of general anesthesia leads to the development of atelectasis and redistribution of ventilation to non-dependent lung regions with subsequent impairment of gas exchange. However, it remains unclear how rapidly atelectasis occurs after the induction of anesthesia in obese patients. We therefore investigated the extent of atelectasis formation in obese patients in the first few minutes after the induction of general anesthesia and initiation of mechanical ventilation in the operating room. Methods: In 102 patients with morbid obesity (BMI ≥ 35 kg m⁻²) scheduled for laparoscopic intrabdominal surgery, induction of general anesthesia was performed while continuously monitoring regional pulmonary ventilation using electrical impedance tomography. Distribution of ventilation to non-dependent lung areas as a surrogate for atelectasis formation was determined by taking the mean value of five consecutive breaths for each minute starting five minutes before to five minutes after intubation. Ventilation inhomogeneity was assessed using the Global Inhomogeneity Index. Results: Median tidal volume in non-dependent lung areas was 58.3% before and 71.5% after intubation and increased by a median of 13.79% after intubation (p < 0.001). Median Global Inhomogeneity Index was 49.4 before and 71.4 after intubation and increased by a median of 21.99 units after intubation (p < 0.001). Conclusions: Atelectasis forms immediately after the induction of general anesthesia and increases the inhomogeneity of lung ventilation. Full article

This paper presents an energy optimization approach to applying electrical impedance tomography (EIT) for medical diagnostics, particularly in detecting lung diseases. The designed Lung Electrical Tomography System (LETS) incorporates 102 electrodes and advanced image reconstruction algorithms. Energy efficiency is achieved through the use of modern electronic components and high-efficiency DC/DC converters that reduce the size and weight of the device without the need for additional cooling. Special attention is given to minimizing energy consumption during electromagnetic measurements and data processing, significantly improving the system’s overall performance. Research studies confirm the device’s high energy efficiency while maintaining the accuracy of the classification of lung disease using the LightGBM algorithm. This solution enables long-term patient monitoring and precise diagnosis with reduced energy consumption, marking a key step towards sustainable medical diagnostics based on EIT technology. Full article

Accurate human cerebrospinal fluid (CSF) dielectric parameters are critical for biological electromagnetic applications such as the electromagnetic field modelling of the human brain, the localization and intensity assessment of electrical generators in the brain, and electromagnetic protection. To detect brain damage signals during temperature changes by electrical impedance tomography (EIT), the change in CSF dielectric parameters with frequency (10 Hz–100 MHz) and temperature (17–39 °C) was investigated. A Debye model was first established to capture the complex impedance frequency and temperature characteristics. Furthermore, the receiver operating characteristic (ROC) analysis based on the dielectric parameters of normal and diseased CSF was carried out to identify lesions. The Debye model’s characteristic f_c parameters linearly increased with increasing temperature (R² = 0.989), and R₀ and R₁ linearly decreased (R² = 0.990). The final established formula can calculate the complex impedivity of CSF with a maximum fitting error of 3.79%. Furthermore, the ROC based on the real part of impedivity at 10 Hz and 17 °C yielded an area under the curve (AUC) of 0.898 with a specificity of 0.889 and a sensitivity of 0.944. These findings are expected to facilitate the application of electromagnetic technology, such as disease diagnosis, specific absorption rate calculation, and biosensor design. Full article

Background: Changes in lung ventilation are well documented in term neonates while in late preterm neonates these patterns are poorly understood despite their increased risk of respiratory morbidity. Objectives: The study aimed to compare and clarify the differences in regional lung ventilation of late preterm and term neonates during the early adaptation period using electrical impedance tomography (EIT). Material and methods: The case-control study was conducted in the years 2020–2022. It included 51 late preterm neonates (LPN, Study group) and 45 term neonates (TN, Control) born by normal vaginal delivery (NVD). EIT examinations were performed with a Swisstom BB2 (Switzerland) equipment. The data recordings were performed no later than 30 (I Record), 60 (II), and 90 (III) minutes after the birth. Results: Statistically significant differences between LPN and TN were observed in the non-dependent lung areas at I record, with more silent spaces observed in the LPN (p < 0.001). Differences in the dependent lung regions were observed across all recordings, with LPN demonstrating more silent spaces (p < 0.001). LPN demonstrated greater stretch-related changes in the 10% and 20% stretch categories across all recordings, while TN showed greater changes in the 50%, 70%, and 90% categories. Tidal volumes in the right lung of TN are distributed more towards the ventral and central ventral regions. In contrast, tidal volumes of LPN are distributed to the central dorsal and dorsal regions of the right lung. Conclusions: LPN during the first 90 min after the birth show reduced lung ventilation assessed by EIT, suggesting a possible impairment of early postnatal adaptation. Full article

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. Full article

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. Full article

Flexible electronic skin (e-skin) can enable robots to have sensory forms similar to human skin, enhancing their ability to obtain more information from touch. The non-invasive nature of electrical impedance tomography (EIT) technology allows electrodes to be arranged only at the edges of the skin, ensuring the stretchability and elasticity of the skin’s interior. However, the image quality reconstructed by EIT technology has deteriorated in multi-touch identification, where it is challenging to clearly reflect the number of touchpoints and accurately size the touch areas. This paper proposed an EIT-based flexible tactile sensor that employs self-made hydrogel material as the primary sensing medium. The sensor’s structure, fabrication process, and tactile imaging principle were elaborated. To improve the quality of image reconstruction, the fast iterative shrinkage-thresholding algorithm (FISTA) was embedded into the EIDORS toolkit. The performances of the e-skin in aspects of assessing the touching area, quantitative force sensing and multi-touch identification were examined. Results showed that the mean intersection over union (MIoU) of the reconstructed images was improved up to 0.84, and the tactile position can be accurately imaged in the case of the number of the touchpoints up to seven (larger than two to four touchpoints in existing studies), proving that the combination of the proposed sensor and imaging algorithm has high sensitivity and accuracy in multi-touch tactile sensing. The presented e-skin shows potential promise for the application in complex human–robot interaction (HRI) environments, such as prosthetics and wearable devices. Full article

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. Full article

Peripheral nerve modulation via electrical stimulation shows promise for treating several diseases, but current approaches lack selectivity, leading to side effects. Exploring selective neuromodulation with commercially available nerve cuffs is impractical due to their high cost and limited spatial resolution. While custom cuffs reported in the literature achieve high spatial resolutions, they require specialized microfabrication equipment and significant effort to produce even a single design. This inability to rapidly and cost-effectively prototype novel cuff designs impedes research into selective neuromodulation therapies in acute studies. To address this, we developed a reproducible method to easily create multi-channel epineural nerve cuffs for selective fascicular neuromodulation. Leveraging commercial flexible printed circuit (FPC) technology, we created cuffs with high spatial resolution (50 μm) and customizable parameters like electrode size, channel count, and cuff diameter. We designed cuffs to accommodate adult mouse or rat sciatic nerves (300–1500 μm diameter). We coated the electrodes with PEDOT:PSS to improve the charge injection capacity. We demonstrated selective neuromodulation in both rats and mice, achieving preferential activation of the tibialis anterior (TA) and lateral gastrocnemius (LG) muscles. Selectivity was confirmed through micro-computed tomography (μCT) and quantified through a selectivity index. These results demonstrate the potential of this fabrication method for enabling selective neuromodulation studies while significantly reducing production time and costs compared to traditional approaches. Full article

Total knee arthroplasty (TKA) is a well-established and successful treatment option for patients with end-stage osteoarthritis of the knee, providing high patient satisfaction. Robotic systems have been widely adopted to perform TKA in orthopaedic centres. The exact spatial positions of the femur and tibia are usually determined through pinned trackers, providing the surgeon with an exact illustration of the axis of the lower limb. The drilling of holes required for mounting the trackers creates weak spots, causing adverse events such as bone fracture. In the presented computational feasibility study, time differential electrical impedance tomography is used to locate the femur positions, thereby the difference in conductivity distribution between two distinct states $s_0$ and $s_1$ of the measured object is reconstructed. The overall approach was tested by simulating five different configurations of thigh shape and considered tissue conductivity distributions. For the cylinder models used for verification and reference, the reconstructed position deviated by about $\approx 1$ mm from the actual bone centre. In case of models mimicking a realistic cross section of the femur position deviated between 7.9 mm 24.8 mm. For all models, the bone axis was off by about $\phi =1.50°$ from its actual position. Full article

Computed tomography (CT), magnetic resonance imaging (MRI), and radiography expose patients to electromagnetic fields (EMFs) and ionizing radiation. As an alternative, Electrical Impedance Tomography (EIT) offers a less EMF-influenced method for imaging by measuring superficial skin currents to provide a map of the body’s conductivity. EIT allows for functional monitoring of anatomical regions using low electromagnetic fields and minimal exposure times. This paper investigates the application of EIT for the morphological and functional assessment of tissues. Using the Finite Element Method (FEM) (Comsol 5.2), both two-dimensional and three-dimensional models and simulations of physiological and pathological tissues were developed to replicate EIT operations. The primary objective is to detect carcinoma by analysing the electrical impedance response to externally applied excitations. An eight-electrode tomograph was utilised for this purpose, specifically targeting epithelial tissue. The study allowed the characterisation of tomographs of any size and, therefore, the possibility to verify both their geometric profile and the ideal value of the excitation current to be delivered per second of the type of tissue to be analysed. Simulations were conducted to observe electrical impedance variations within a homogeneously modelled tissue and a carcinoma characterized by regular geometry. The outcomes demonstrated the potential of EIT as a viable technique for carcinoma detection, emphasizing its utility in medical diagnostics with reduced EMF exposure. Full article

Pulmonary monitoring is crucial for the diagnosis and management of respiratory conditions, especially after the epidemic of coronavirus disease. Electrical impedance tomography (EIT) is an alternative non-radioactive tomographic imaging tool for monitoring pulmonary conditions. This review proffers the current EIT technical principles and applications on pulmonary monitoring, which gives a comprehensive summary of EIT applied on the chest and encourages its extensive usage to clinical physicians. The technical principles involving EIT instrumentations and image reconstruction algorithms are explained in detail, and the conditional selection is recommended based on clinical application scenarios. For applications, specifically, the monitoring of ventilation/perfusion (V/Q) is one of the most developed EIT applications. The matching correlation of V/Q could indicate many pulmonary diseases, e.g., the acute respiratory distress syndrome, pneumothorax, pulmonary embolism, and pulmonary edema. Several recently emerging applications like lung transplantation are also briefly introduced as supplementary applications that have potential and are about to be developed in the future. In addition, the limitations, disadvantages, and developing trends of EIT are discussed, indicating that EIT will still be in a long-term development stage before large-scale clinical applications. Full article

There is an extensive need for surface sensors for applications such as tactile sensing for robotics, damage and strain detection for structural health monitoring and leak detection for buried structures. One type of surface sensor is electrical impedance tomography (EIT)-based sensing skins, which use electrically conductive coatings applied on the object’s surface to monitor physical or chemical phenomena on the surface. In this article, we propose a sensing skin with two electrically coupled layers separated by an insulator. Based on electrical measurements, the spatial distribution of the electrical coupling between the layers is estimated. This coupling is sensitive to both the pressure distribution on the surface and water entering between the layers through a leak. We present simulations and experimental studies to evaluate the feasibility of the proposed method for pressure sensing and leak detection. The results support the feasibility of the proposed method for both of these applications. Full article