Application Of Electrical Impedance Tomography Research Articles

Clinical implementation of advanced respiratory monitoring with esophageal pressure and electrical impedance tomography: results from an international survey and focus group discussion

BackgroundPopularity of electrical impedance tomography (EIT) and esophageal pressure (Pes) monitoring in the ICU is increasing, but there is uncertainty regarding their bedside use within a personalized ventilation strategy. We aimed to gather insights about the current experiences and perceived role of these physiological monitoring techniques, and to identify barriers and facilitators/solutions for EIT and Pes implementation.MethodsQualitative study involving (1) a survey targeted at ICU clinicians with interest in advanced respiratory monitoring and (2) an expert focus group discussion. The survey was shared via international networks and personal communication. An in-person discussion session on barriers, facilitators/solutions for EIT implementation was organized with an international panel of EIT experts as part of a multi-day EIT meeting. Pes was not discussed in-person, but we found the focus group results relevant to Pes as well. This was confirmed by the survey results and four additional Pes experts that were consulted.ResultsWe received 138 survey responses, and 26 experts participated in the in-person discussion. Survey participants had diverse background [physicians (54%), respiratory therapists (19%), clinical researchers (15%), and nurses (6%)] with mostly > 10 year ICU experience. 84% of Pes users and 74% of EIT users rated themselves as competent to expert users. Techniques are currently primarily used during controlled ventilation for individualization of PEEP (EIT and Pes), and for monitoring lung mechanics and lung stress (Pes). EIT and Pes are considered relevant techniques to guide ventilation management and is helpful for educating clinicians; however, 57% of EIT users and 37% of Pes users agreed that further validation is needed. Lack of equipment/materials, evidence-based guidelines, clinical protocols, and/or the time-consuming nature of the measurements are main reasons hampering Pes and EIT application. Identified facilitators/solutions to improve implementation include international guidelines and collaborations between clinicians/researcher and manufacturers, structured courses for training and use, easy and user-friendly devices and standardized analysis pipelines.ConclusionsThis study revealed insights on the role and implementation of advanced respiratory monitoring with EIT and Pes. The identified barriers, facilitators and strategies can serve as input for further discussions to promote the development of EIT-guided or Pes-guided personalized ventilation strategies.

Monitoring of damage evolution in carbon fiber reinforced polymer composites by electrical impedance tomography

Electrical impedance tomography (EIT) has been widely investigated as a nondestructive testing method for carbon fiber reinforced polymer (CFRP) composites. However, the performance of EIT method on the damage process monitoring of the composites is lack of investigation. Herein, quasi-static indentation tests were utilized to introduce damage on CFRP laminates. The damage evolution process was monitored by EIT, while the potential of distinguishing the elastic deformation stage from the plastic stage was analyzed with the aid of acoustic emission. It was found that the changes in conductivity first appeared in the non-central region. With the accumulation of damage, the conductivity changes gradually extended to the center region. The reconstructed damage images were in the crossover shape, which was consist with the micro-CT results that showed the fracture of fibers in ±45° direction. This work further promotes the application of EIT in damage process monitoring of CFRP components.

Detection of indentation damage in carbon fiber/epoxy composites via EIT during the application of bending loads

Electrical impedance tomography (EIT) is a method of spatially mapping the conductivity distribution of a domain and has been studied as a potential embedded sensing or nondestructive evaluation (NDE) tool. An often touted advantage of EIT is that it can be used in-situ; that is, because the method only requires the application of unobtrusive electrodes, it can conceivably be used while the component or structure is in operation. This material-as-the-sensor philosophy strongly aligns with key components of the NDE 4.0 vision such as the realization of intelligent cyber–physical systems (CPS) and digital twins. To date, however, the claim of in-situ sensing via EIT has not been significantly substantiated. This is problematic because operational loads induce strains that often change the conductivity of the material. Establishing that EIT can detect damage-induced conductivity changes through the presence of unrelated strain-induced conductivity changes is therefore important. To that end, we herein study the application of EIT for detecting indentation damage in a carbon fiber/epoxy composite as the composite is loaded in a four-point bend. It was found that the bending load changes the contact impedance of the electrodes, which resulted in poor EIT images when solving the EIT inverse problem with the ℓ2-norm on the error term. Using the ℓ1-norm on the error term, solved via the primal–dual interior point method (PDIPM), significantly improved image quality. Image quality was even further improved through the use of a mixed prior for regularization, and EIT images were compared to thermography with good agreement. These results show that EIT can indeed detect damage through the presence of an applied load, but care must be taken to account for factors such as outlier data arising from electrode degradation and changing contact impedance. Use of the ℓ1-norm on the error term is therefore highly recommended for in-situ imaging via EIT.

EIT probe based intraoperative tissue inspection for minimally invasive surgery

Abstract Electrical impedance tomography (EIT) has become an integral component in the repertoire of medical imaging techniques, particularly due to its non-invasive nature and real-time imaging capabilities. Despite its potential, the application of EIT in minimally invasive surgery (MIS) has been hindered by a lack of specialized electrode probes. Existing designs often compromise between invasiveness and spatial sensitivity: probes small enough for MIS often fail to provide detailed imaging, while those offering greater sensitivity are impractically large for use through a surgical trocar. Addressing this challenge, our study presents a breakthrough in EIT probe design. The open electrode probe we have developed features a line of 16 electrodes, thoughtfully arrayed to balance the spatial demands of MIS with the need for precise imaging. Employing an advanced EIT reconstruction algorithm, our probe not only captures images that reflect the electrical characteristics of the tissues but also ensures the homogeneity of the test material is accurately represented. The versatility of our probe is demonstrated by its capacity to generate high-resolution images of subsurface anatomical structures, a feature particularly valuable during MIS where direct visual access is limited. Surgeons can rely on intraoperative EIT imaging to inform their navigation of complex anatomical landscapes, enhancing both the safety and efficacy of their procedures. Through rigorous experimental validation using ex vivo tissue phantoms, we have established the probe’s proficiency. The experiments confirmed the system’s high sensitivity and precision, particularly in the critical tasks of subsurface tissue detection and surgical margin delineation. These capabilities manifest the potential of our probe to revolutionize the field of surgical imaging, providing a previously unattainable level of detail and assurance in MIS procedures.

Engineering Biomedical Problems to Detect Carcinomas: A Tomographic Impedance Approach

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.

Technical Principles and Clinical Applications of Electrical Impedance Tomography in Pulmonary Monitoring.

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.

Electrical impedance tomography for meat marbling prediction

Electrical Impedance Tomography (EIT) is a promising noninvasive technology for predicting meat quality traits, such as marbling in beef. Marbling, characterized by intramuscular fat, significantly influences beef quality by enhancing flavor, tenderness, and juiciness. This review evaluated the application of EIT in meat quality control, highlighting its ability to measure changes in conductivity to assess marbling and other quality attributes. Integrating EIT with machine-learning techniques further refines its predictive capabilities. Although EIT provides real-time, noninvasive assessments with lower costs, challenges like lower signal-to-noise ratios and complex algorithm requirements persist. Future directions include the integration of EIT with modern packaging systems and automation tools to enhance meat quality monitoring and industrial efficiency.

Electrical Impedance Tomography, Artificial Intelligence, and Variable Ventilation: Transforming Respiratory Monitoring and Treatment in Critical Care.

Electrical Impedance Tomography (EIT), combined with variable ventilation strategies and Artificial Intelligence (AI), is poised to revolutionize critical care by transitioning from reactive to predictive approaches. This integration aims to enhance patient outcomes through personalized interventions and real-time monitoring. this narrative review explores the principles and applications of EIT, variable ventilation, and AI in critical care. EIT impedance sensing creates dynamic images of internal physiology, aiding the management of conditions like Acute Respiratory Distress Syndrome (ARDS). Variable ventilation mimics natural breathing variability to improve lung function and minimize ventilator-induced lung injury. AI enhances EIT through advanced image reconstruction techniques, neural networks, and digital twin technology, offering more accurate diagnostics and tailored therapeutic interventions. the confluence of EIT, variable ventilation, and AI represents a significant advancement in critical care, enabling a predictive, personalized approach. EIT provides real-time insights into lung function, guiding precise ventilation adjustments and therapeutic interventions. AI integration enhances EIT diagnostic capabilities, facilitating the development of personalized treatment plans. This synergy fosters interdisciplinary collaborations and sets the stage for innovative research, ultimately improving patient outcomes and advancing the future of critical care.

A preliminary study on the application of electrical impedance tomography based on cerebral perfusion monitoring to intracranial pressure changes.

In intracranial pathologic conditions of intracranial pressure (ICP) disturbance or hemodynamic instability, maintaining appropriate ICP may reduce the risk of ischemic brain injury. The change of ICP is often accompanied by the change of intracranial blood status. As a non-invasive functional imaging technique, the sensitivity of electrical impedance tomography (EIT) to cerebral hemodynamic changes has been preliminarily confirmed. However, no team has conducted a feasibility study on the dynamic detection of ICP by EIT technology from the perspective of non-invasive whole-brain blood perfusion monitoring. In this study, human brain EIT image sequence was obtained by in vivo measurement, from which a variety of indicators that can reflect the tidal changes of the whole brain impedance were extracted, in order to establish a new method for non-invasive monitoring of ICP changes from the level of cerebral blood perfusion monitoring. Valsalva maneuver (VM) was used to temporarily change the cerebral blood perfusion status of volunteers. The electrical impedance information of the brain during this process was continuously monitored by EIT device and real-time imaging was performed, and the hemodynamic indexes of bilateral middle cerebral arteries were monitored by transcranial Doppler (TCD). The changes in monitoring information obtained by the two techniques were compared and observed. The EIT imaging results indicated that the image sequence showed obvious tidal changes with the heart beating. Perfusion indicators of vascular pulsation obtained from EIT images decreased significantly during the stabilization phase of the intervention (PAC: 242.94 ± 100.83, p < 0.01); perfusion index which reflects vascular resistance increased significantly in the stable stage of intervention (PDT: 79.72 ± 18.23, p < 0.001). After the intervention, the parameters gradually returned to the baseline level before compression. The changes of EIT indexes in the whole process are consistent with the changes of middle cerebral artery velocity related indexes shown in TCD results. The EIT image combined with the blood perfusion index proposed in this paper can reflect the decrease of cerebral blood flow under the condition of increased ICP in real time and intuitively. With the advantages of high time resolution and high sensitivity, EIT provides a new idea for non-invasive bedside measurement of ICP.

The application of electrical impedance tomography and surgical outcomes of thoracoscope-assisted surgical stabilization of rib fractures in severe chest trauma

Serious blunt chest trauma usually induces hemothorax, pneumothorax, and rib fractures. More studies have claimed that early video-assisted thoracoscopic surgery with surgical stabilization of rib fractures (SSRF) results in a good prognosis in patients with major trauma. This study aimed to verify the outcomes in patients with chest trauma whether SSRF was performed. Consecutive patients who were treated in a medical center in Taiwan, for traumatic events between January 2015 and June 2020, were retrospectively reviewed. This study focused on patients with major trauma and thoracic injuries, and they were divided into groups based on whether they received SSRF. We used electrical impedance tomography (EIT) to evaluate the change of ventilation conditions. Different scores used for the evaluation of trauma severity were also compared in this study. Among the 8396 patients who were included, 1529 (18.21%) had major trauma with injury severity score > 16 and were admitted to the intensive care unit initially. A total of 596 patients with chest trauma were admitted, of whom 519 (87%) survived. Younger age and a lower trauma score (including injury severity scale, new injury severity score, trauma and injury severity score, and revised trauma score) account for better survival rates. Moreover, 74 patients received SSRF. They had a shorter intensive care unit (ICU) stay (5.24, p = 0.045) and better performance in electrical impedance tomography (23.46, p < 0.001). In patients with major thoracic injury, older age and higher injury survival scale account for higher mortality rate. Effective surgical stabilization of rib fractures shortened the ICU stay and helped achieve better performance in EIT. Thoracoscope-assisted rib fixation is suggested in severe trauma cases.

Contribution of electrical impedance tomography to personalize positive end-expiratory pressure under ECCO2R

Extracorporeal Carbon Dioxide Removal (ECCO2R) is used in acute respiratory distress syndrome (ARDS) patients to facilitate lung-protective ventilatory strategies. Electrical Impedance Tomography (EIT) allows individual, non-invasive, real-time, bedside, radiation-free imaging of the lungs, providing global and regional dynamic lung analyses. To provide new insights for future ECCO2R research in ARDS, we propose a potential application of EIT to personalize End-Expiratory Pressure (PEEP) following each reduction in tidal volume (VT), as demonstrated in an illustrative case. A 72-year-old male with COVID-19 was admitted to the ICU for moderate ARDS. Monitoring with EIT was started to determine the optimal PEEP value (PEEPEIT), defined as the intersection of the collapse and overdistention curves, after each reduction in VT during ECCO2R. The identified PEEPEIT values were notably low (< 10 cmH2O). The decrease in VT associated with PEEPEIT levels resulted in improved lung compliance, reduced driving pressure and a more uniform ventilation pattern. Despite current Randomized Controlled Trials showing that ultra-protective ventilation with ECCO2R does not improve survival, the applicability of universal ultra-protective ventilation settings for all patients remains a subject of debate. Inappropriately set PEEP levels can lead to alveolar collapse or overdistension, potentially negating the benefits of VT reduction. EIT facilitates real-time monitoring of derecruitment associated with VT reduction, guiding physicians in determining the optimal PEEP value after each decrease in tidal volume. This original description of using EIT under ECCO2R to adjust PEEP at a level compromising between recruitability and overdistention could be a crucial element for future research on ECCO2R.

IoT-Driven Experimental Framework for Advancing Electrical Impedance Tomography

This research paper focuses on the current emphasis on the latest industrial revolution, particularly the innovative integration of artificial intelligence and the Internet of Things (IoT). The study explores the seamless integration of Electrical Impedance Tomography (EIT) with IoT, presenting a groundbreaking framework where impedance-based sensing plays a vital role in enhancing the dynamic and adaptable qualities of IoT ecosystems. This contribution facilitates intelligent decision-making and real-time monitoring. The research investigates the application of non-invasive Electrical Impedance Tomography for the rapid identification of minor changes in the electrical impedance of the body or a simulated object. Electrodes positioned at the ends of the phantom’s cylinder measure impedance changes through the application of a high-frequency, low-current signal. Image reconstruction employs both forward and inverse solutions, utilizing a triangular finite element method (FEM) mesh to determine conductivity distribution based on recommended phantom models. The integration of IoT enables data capture, enhancing accessibility through remote monitoring. The novel IoT system proves advantageous for various engineering research applications, providing easily monitored parameters in both commercial and clinical contexts.

A Shifting Current Mirror Driver Circuit for Electrical Impedance Tomography Applications

This brief describes a high power efficiency, high linearity current driver for wearable electrical impedance tomography (EIT). It is extremely important to improve the power efficiency of the current driver circuit for wearable EIT applications because it consumes the majority of the power. As such, we propose a multi-stage shifting current mirror (SCM) current-steering current driver circuit with customized dynamic element matching (DEM) techniques to suppress harmonic distortion (HD) to the greatest extent. Furthermore, the placement of switches in the current mirror circuit is optimized to reduce glitches during the switching phases. Operating between 14 MHz to 56 MHz, the power consumptions for the current mirror and the digital control logic are 21.6-141.6 lW and 64.8-438 μW, respectively. The proposed circuit has demonstrated an excellent energy efficiency of 0.3 μW/kHz while maintaining a total harmonic distortion (HD) of <-43 dB (0.7%).

Three-dimensional electrical impedance tomography (EIT) to study regional ventilation/perfusion (V/Q̇) ratios in anesthetized pigs.

This study aimed to develop a 3D method for assessing ventilation/perfusion (V/Q̇) ratios in a pig model of hemodynamic perturbations using electrical impedance tomography (EIT). In order to evaluate the physiological coherence of changes in EIT-derived V/Q̇ ratios, global EIT-derived V/Q̇ mismatches were compared with global gold-standards. The study found regional heterogeneity in the distribution of V/Q̇ ratios in both the ventrodorsal and craniocaudal directions. Although global EIT-derived indices of V/Q̇ mismatch consistently underestimated both low and high V/Q̇ mismatch compared to global gold standards, the direction of the change was similar. We made the software available at no cost for other researchers to use. Future studies should compare regional V/Q̇ ratios determined by our method against other regional, high-resolution methods.

Numerical analysis of aerospace plate damage via 3D electrical impedance tomography.

The carbon fiber reinforced plastic (CFRP) is widely used in the aerospace industry due to its high strength and lightweight characteristics, making it crucial to ensure the reliability of these materials. This has led to an increasing focus on research on the health monitoring technologies of aerospace materials. Electrical impedance tomography (EIT) is a non-invasive and cost-effective technology that has the potential to realize real-time health monitoring of materials by measuring changes in electrical parameters. This paper investigates the application of EIT for direct 3D reconstruction of damage in CFRP laminates with significant conductivity anisotropy distribution. Based on the corrected sensitivity matrix formula, the direct 3D image reconstruction method combined with the fast iterative shrinkage-thresholding algorithm (FISTA) is proposed to achieve damage imaging of CFRP laminates in the inverse problem. The fast convergence of the FISTA makes it possible to solve complex inverse problems. The numerical simulation results indicate that, compared with 2D EIT, the proposed method is more capable of providing damage information, especially in the depth direction. This research plays a constructive role in realizing 3D image reconstruction of CFRP material damage and has significant implications for improving the reliability and safety of CFRP materials in aerospace applications.

Effective Electrical Impedance Tomography Based on Enhanced Encoder–Decoder Using Atrous Spatial Pyramid Pooling Module

Electrical impedance tomography (EIT) is a noninvasive and radiation-free imaging method. As a "soft-field" imaging technique, in EIT, the target signal in the center of the measured field is frequently swamped by the target signal at the edge, which restricts its further application. To alleviate this problem, this study presents an enhanced encoder-decoder (EED) method with an atrous spatial pyramid pooling (ASPP) module. The proposed method enhances the ability to detect central weak targets by constructing an ASPP module that integrates multiscale information in the encoder. The multilevel semantic features are fused in the decoder to improve the boundary reconstruction accuracy of the center target. The average absolute error of the imaging results by the EED method reduced by 82.0%, 83.6%, and 36.5% in simulation experiments and 83.0%, 83.2%, and 36.1% in physical experiments compared with the errors of the damped least-squares algorithm, Kalman filtering method, and U-Net-based imaging method, respectively. The average structural similarity improved by 37.3%, 42.9%, and 3.6%, and 39.2%, 45.2%, and 3.8% in the simulation and physical experiments, respectively. The proposed method provides a practical and reliable means of extending the application of EIT by solving the problem of weak central target reconstruction under the effect of strong edge targets in EIT.

Emerging nanomaterials to enhance electrochemical impedance spectroscopy for biomedical applications

Over the last few decades, electrical impedance-based sensors have been investigated for clinical translation to detect changes in tissue conductivities, including cardiac output and pulmonary function. Recently, electrochemical impedance spectroscopy (EIS) provides metabolic measurements that occur at the electrode-tissue interface, and the 3-D EIS can be reconstructed to generate electrical impedance tomography (EIT) for detecting the impedimetric properties of the vascular wall or fatty liver disease. In both EIS and EIT applications, the electrochemical properties of the interface electrodes are essential to address the signal-to-noise ratio or sensitivity of measurements in the biological environment. To enhance the conductive properties, we will survey a series of carbon-based nanomaterials as the emerging candidates for coating the electrodes of bioimpedance sensors. In this review, we will provide a theoretical background on impedance-based measurements and highlight the current state of EIS and EIT, including their applications for cancer screening and detection of vulnerable atherosclerotic plaques. Next, we will focus on the strengths of different nanomaterials when used as an electrode coating to optimize charge transfer across the electric double layers and to enhance measurement sensitivity. We will also identify some unmet clinical needs, such as the ability to adapt to different hemodynamic conditions and blood vessel geometries, that can be realized by the novel biomaterials for the future EIS-based sensors.

An Optimization Algorithm H-GVSPM for Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a novel industrial monitoring technology with the characteristics of safety, inexpensiveness, and real-time monitoring. Its imaging results are easily to generate artifacts due to the influence of various factors. Therefore, the image quality is low, and the contour of measured objects has a distortion phenomenon. An optimization algorithm H-GVSPM based on the Hadamard product is proposed for EIT to reduce the artifacts, and to improve the image quality. The relative conductivity difference between the measured object and the background becomes more distinguishable with the action of the Hadamard product. Simulation and experimental results show that H-GVSPM effectively reduces the influence of artifacts in the reconstructed images. The maximum increase of the correlation coefficient approximately is 15.56% and 22.80% respectively compared with GVSPM and TV method. The maximum reduction of the voltage relative residual is 22.12% in the simulation, and it is 8.12% in the experiment. The standard deviation of conductivity is about 1/10 of the original. This study provides a reference method for improving image quality, and it contributes to the application of EIT in industry, biomedicine, and other fields in the future.

Extracting reference voltages from measurement voltages for oil-water two-phase flow measurement of electrical impedance tomography

To apply electrical impedance tomography (EIT) for heterogeneous two-phase flow measurement, reference voltages have to be measured, which requires the entire pipeline filled with a homogeneous medium. Such process is often time-consuming, costly and infeasible in some cases. Reference voltages acquired initially could not be used later, because of electrical conductivity change of two-phase flow caused by temperature change or chemical reaction. It will be ideal if reference voltages could be extracted from measurement voltages. In this paper, a novel multiple measurements (MMs) method is proposed by data fitting and empirical formula to establish the mapping model from measurement voltages to reference voltages, and the effectiveness of the method is proved by the oil-water two-phase flow experiment. Compared with the measurement-scale feature (MSF) and best homogeneous (BH) methods, the proposed MMs method achieves 6.38% average relative error (RE) and 4.96% average volume fraction relative error (VFRE) in the test set. The work enables the accurate estimation of the reference voltage and thus the accurate measurement of the volume fraction of oil-water two-phase flows, which will broaden the application of EIT in the field of two-phase flow measurement.

Compensation of Contact Impedance Variation for Cerebral Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a promising technique for conductivity distribution reconstruction. Considering the fact that cerebral disease causes variation of conductivity distribution, EIT technique can be used to reflect the pathological change in the cerebral region. This would offer an alternative for the timely diagnosis and treatment of cerebral disease. In cerebral EIT, contact impedance between the electrode and the scalp changes with time, which largely affects the reconstruction quality. To conquer this problem, a compensation method is proposed for voltage data correction when contact impedance varies. By analysis of boundary measurement, the electrode with contact impedance variation and how much contact impedance changes are determined. Together with a prior matrix, voltage data in the case of contact impedance variation can be compensated. Reconstruction of conductivity distribution is implemented by the L1 regularization method. The performance of the proposed method is evaluated under contact impedance variation of a single electrode, a pair of electrodes, and 16 electrodes. In addition, the influence of noise with a signal-to-noise ratio of 40 dB is studied. The results show that the proposed method can effectively suppress the effect of contact impedance change on image quality. Even under the impact of noise, reconstructed images show great improvement. With this method, it is able to monitor cerebral disease in the clinical application of EIT where contact impedance variation is inevitable.