Robust imaging using electrical impedance tomography: review of current tools

Seeing Through Muddy Water: Laser-Induced Graphene for Portable Tomography Imaging

Due to its outstanding physical and chemical properties, graphene synthesized by laser scribing on polyimide (PI) offers excellent opportunities for photothermal applications, antiviral and antibacterial surfaces, and electrochemical storage and sensing. However, the utilization of such graphene for imaging is yet to be explored. Herein, using chemically durable and electrically conductive laser-induced graphene (LIG) for tomography imaging in aqueous suspensions is proposed. These graphene electrodes are designed as impedance imaging units for four-terminal electrical measurements. Using the real-time portable imaging prototypes, the conductive and dielectric objects can be seen in clear and muddy water with equivalent impedance modeling. This low-cost graphene tomography measurement system offers significant advantages over traditional visual cameras, in which the suspended muddy particles hinder the imaging resolution. This research shows the potential of applying graphene nanomaterials in emerging marine technologies, such as underwater robotics and automatic fisheries.

Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning

Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection is a public health priority but challenging. In this study, an adhesive, soft on-skin sensor with low electrode-skin contact impedance for early-stage NAFLD detection is fabricated. A method is developed to synthesize platinum nanoparticles and reduced graphene quantum dots onto the on-skin sensor to reduce electrode-skin contact impedance by increasing double-layer capacitance, thereby enhancing detection accuracy. Furthermore, an attention-based deep learning algorithm is introduced to differentiate impedance signals associated with early-stage NAFLD in high-fat-diet-fed low-density lipoprotein receptor knockout (Ldlr-/-) mice compared to healthy controls. The integration of an adhesive, soft on-skin sensor with low electrode-skin contact impedance and the attention-based deep learning algorithm significantly enhances the detection accuracy for early-stage NAFLD, achieving a rate above 97.5% with an area under the receiver operating characteristic curve (AUC) of 1.0. The findings present a non-invasive approach for early-stage NAFLD detection and display a strategy for improved early detection through on-skin electronics and deep learning.

A non-invasive approach to skin cancer diagnosis via graphene electrical tattoos and electrical impedance tomography

Objective.Making up one of the largest shares of diagnosed cancers worldwide, skin cancer is also one of the most treatable. However, this is contingent upon early diagnosis and correct skin cancer-type differentiation. Currently, methods for early detection that are accurate, rapid, and non-invasive are limited. However, literature demonstrating the impedance differences between benign and malignant skin cancers, as well as between different types of skin cancer, show that methods based on impedance differentiation may be promising.Approach.In this work, we propose a novel approach to rapid and non-invasive skin cancer diagnosis that leverages the technologies of difference-based electrical impedance tomography (EIT) and graphene electronic tattoos (GETs).Main results.We demonstrate the feasibility of this first-of-its-kind system using both computational numerical and experimental skin phantom models. We considered variations in skin cancer lesion impedance, size, shape, and position relative to the electrodes and evaluated the impact of using individual and multi-electrode GET (mGET) arrays. The results demonstrate that this approach has the potential to differentiate based on lesion impedance, size, and position, but additional techniques are needed to determine shape.Significance.In this way, the system proposed in this work, which combines both EIT and GET technology, exhibits potential as an entirely non-invasive and rapid approach to skin cancer diagnosis.

Quantifying heterogeneity in an animal model of acute respiratory distress syndrome, a comparison of inspired sinewave technique to computed tomography

The inspired sinewave technique (IST) is a non-invasive method to measure lung heterogeneity indices (including both uneven ventilation and perfusion or heterogeneity), which reveal multiple conditions of the lung and lung injury. To evaluate the reproducibility and predicted clinical outcomes of IST heterogeneity values, a comparison with a quantitative lung computed tomography (CT) scan is performed. Six anaesthetised pigs were studied after surfactant depletion by saline-lavage. Paired measurements of lung heterogeneity were then taken with both the IST and CT. Lung heterogeneity measured by the IST was calculated by (a) the ratio of tracer gas outputs measured at oscillation periods of 180 s and 60 s, and (b) by the standard deviation of the modelled log-normal distribution of ventilations and perfusions in the simulation lung. In the CT images, lungs were manually segmented and divided into different regions according to voxel density. A quantitative CT method to calculate the heterogeneity (the Cressoni method) was applied. The IST and CT show good Pearson correlation coefficients in lung heterogeneity measurements (ventilation: 0.71, and perfusion, 0.60, p < 0.001). Within individual animals, the coefficients of determination average ventilation (R2 = 0.53) and perfusion (R2 = 0.68) heterogeneity. Strong concordance rates of 98% in ventilation and 89% when the heterogeneity changes were reported in pairs measured by CT scanning and IST methods. This quantitative method to identify heterogeneity has the potential to replicate CT lung heterogeneity, and to aid individualised care in ARDS.

Rapid patient-specific FEM meshes from 3D smart-phone based scans

Objective.The objective of this study was to describe and evaluate a smart-phone based method to rapidly generate subject-specific finite element method (FEM) meshes. More accurate FEM meshes should lead to more accurate thoracic electrical impedance tomography (EIT) images.Approach.The method was evaluated on an iPhone®that utilized an app called Heges, to obtain 3D scans (colored, surface triangulations), a custom belt, and custom open-source software developed to produce the subject-specific meshes. The approach was quantitatively validated via mannequin and volunteer tests using an infrared tracker as the gold standard, and qualitatively assessed in a series of tidal-breathing EIT images recorded from 9 subjects.Main results.The subject-specific meshes can be generated in as little as 6.3 min, which requires on average 3.4 min of user interaction. The mannequin tests yielded high levels of precision and accuracy at 3.2 ± 0.4 mm and 4.0 ± 0.3 mm root mean square error (RMSE), respectively. Errors on volunteers were only slightly larger (5.2 ± 2.1 mm RMSE precision and 7.7 ± 2.9 mm RMSE accuracy), illustrating the practical RMSE of the method.Significance.Easy-to-generate, subject-specific meshes could be utilized in the thoracic EIT community, potentially reducing geometric-based artifacts and improving the clinical utility of EIT.

Electrical Impedance Tomography: From the Traditional Design to the Novel Frontier of Wearables

Electrical impedance tomography (EIT) is a medical imaging technique based on the injection of a current or voltage pattern through electrodes on the skin of the patient, and on the reconstruction of the internal conductivity distribution from the voltages collected by the electrodes. Compared to other imaging techniques, EIT shows significant advantages: it does not use ionizing radiation, is non-invasive and is characterized by high temporal resolution. Moreover, its low cost and high portability make it suitable for real-time, bedside monitoring. However, EIT is also characterized by some technical limitations that cause poor spatial resolution. The possibility to design wearable devices based on EIT has recently given a boost to this technology. In this paper we reviewed EIT physical principles, hardware design and major clinical applications, from the classical to a wearable setup. A wireless and wearable EIT system seems a promising frontier of this technology, as it can both facilitate making clinical measurements and open novel scenarios to EIT systems, such as home monitoring.

Performance evaluation of electrode design and material for a large animal electrical impedance tomography belt

BACKGROUND

Electrical impedance tomography (EIT) produces lung ventilation images via a thoracic electrode belt. Robust electrode design and material, providing low electrode skin contact impedance (SCI), is needed in veterinary medicine. The aim of this study was to compare three EIT electrode designs and materials.

METHODS

Simulations of cylindrical, rectangular and spiked electrode designs were used to evaluate electrode SCI as a function of electrode size, where skin contact was uneven. Gold-plated washers (E_GW ), zinc-plated rivets (E_ZR ) and zinc-galvanised spikes (E_ZS ) were assigned randomly on two interconnected EIT belts. Gel was applied to the cranial or caudal belt and placed on 17 standing cattle. SCI was recorded at baseline and 3, 5, 7, 9 and 11 minutes later.

RESULTS

Simulations that involved electrodes with a greater skin contact area had lower and more uniform SCI. In cattle, SCI decreased with all electrodes over time (p < 0.01). Without gel, no difference was found between E_GW and E_ZS , while SCI was higher for E_ZR (p < 0.03). With gel, SCI was lower in E_GW and E_ZR (p < 0.026), with the SCI in E_GW being the lowest (p < 0.01).

LIMITATIONS

Low numbers of animals and static electrode position may affect SCI.

CONCLUSIONS

Electrode design is important for EIT measurement, with larger electrode designs able to compensate for the use of less conductive materials. Gel is not necessary to achieve acceptable SCI in large animals.

E-Skin Using Fringing Field Electrical Impedance Tomography with an Ionic Liquid Domain

Electrical impedance tomography (EIT) is a promising technique for large area tactile sensing for robotic skin. This study presents a novel EIT-based force and touch sensor that features a latex membrane acting as soft skin and an ionic liquid domain. The sensor works based on fringing field EIT where the touch or force leads to a deformation in the latex membrane causing detectable changes in EIT data. This article analyses the performance of this electronic skin in terms of its dynamical behaviour, position accuracy and quantitative force sensing. Investigation into the sensor’s performance showed it to be hypersensitive, in that it can reliably detect forces as small as 64 mN. Furthermore, multi-touch discrimination and annular force sensing is displayed. The hysteresis in force sensing is investigated showing a very negligible hysteresis. This is a direct result of the latex membrane and the ionic liquid-based domain design compared to more traditional fabric-based touch sensors due to the reduction in electromechanical coupling. A novel test is devised that displayed the dynamic performance of the sensor by showing its ability to record a 1 Hz frequency, which was applied to the membrane in a tapping fashion. Overall, the results show a considerable progress in ionic liquid EIT-based sensors. These findings place the EIT-based sensors that comprise a liquid domain, at the forefront of research into tactile robotic skin.