A 122 fps, 1 MHz Bandwidth Multi-Frequency Wearable EIT Belt Featuring Novel Active Electrode Architecture for Neonatal Thorax Vital Sign Monitoring

Simultaneous Acquisition of EIT and ECG Signals on Active EIT Electrodes

OBJECTIVE

This paper introduces a new method of simultaneous acquisition of electrocardiogram (ECG) signals and electrical impedance tomography (EIT) measurements on active electrodes, i.e. electrodes that are applying current, in an EIT system.

METHODS

Howland noise reduction followed by an integrate-and-dump filter and adaptive filtering are used to extract the ECG signal without loss of amplitude.

RESULTS

Results of simultaneous ECG signals and EIT reconstructions on human subjects are shown. It is also demonstrated that the recovered ECG waveforms from 32 electrodes can be used to reconstruct the heart current source vectors during a cardiac cycle, yielding an approximate solution to the inverse problem of electrocardiography.

SIGNIFICANCE

Acquiring ECG signals from all electrodes attached to the body simultaneously with EIT data acquisition eliminates the need for a separate system to collect ECG signals. Time-aligned ECG signals are helpful in interpreting pulsatile perfusion images by providing exact timing of each image in relation to the cardiac cycle. Additionally, collecting ECG signals from many or all of the EIT electrodes enables reconstruction of the heart's moving dipole moment at the same time as the EIT images.

A Bioimpedance Spectroscopy Interface for EIM Based on IF-Sampling and Pseudo 2-Path SC Bandpass ∆Σ ADC

This paper presents a low-noise bioimpedance (bio-Z) spectroscopy interface for electrical impedance myography (EIM) over the 1 kHz to 2 MHz frequency range. The proposed interface employs a sinusoidal signal generator based on direct-digital-synthesis (DDS) to improve the accuracy of the bio-Z reading, and a quadrature low-intermediate frequency (IF) readout to achieve a good noise-to-power efficiency and the required data throughput to detect muscle contractions. The readout is able to measure baseline and time-varying bio-Z by employing robust and power-efficient low-gain IAs and sixth-order single-bit bandpass (BP) ∆Σ ADCs. The proposed bio-Z spectroscopy interface is implemented in a 180 nm CMOS process, consumes 344.3 - 479.3 μW, and occupies 5.4 mm2 area. Measurement results show 0.7 m Ω/[Formula: see text] sensitivity at 15.625 kHz, 105.8 dB SNR within 4 Hz bandwidth, and a 146.5 dB figure-of-merit. Additionally, recording of EIM in time and frequency domain during contractions of the bicep brachii muscle demonstrates the potential of the proposed bio-Z interface for wearable EIM systems.

Impedance-Readout Integrated Circuits for Electrical Impedance Spectroscopy: Methodological Review

This review article provides a comprehensive overview of impedance-readout integrated circuits (ICs) for electrical impedance spectroscopy (EIS) applications. The readout IC, a crucial component of on-chip EIS systems, significantly affects key performance metrics of the entire system, such as frequency range, power consumption, accuracy, detection range, and throughput. With the growing demand for portable, wearable, and implantable EIS systems in the Internet-of-Things (IoT) era, achieving high energy efficiency while maintaining a wide frequency range, high accuracy, wide dynamic range, and high throughput has become a focus of research. Furthermore, to enhance the miniaturization and convenience of EIS systems, many emerging systems utilize two-electrode or dry electrode configurations instead of the conventional four-electrode configuration with wet electrodes for impedance measurement. In response to these trends, various technologies have been developed to ensure reliable operations even at two- or dry-electrode interfaces. This article reviews the principles, advantages, and disadvantages of techniques employed in state-of-the-art impedance-readout ICs, aiming to achieve high energy efficiency, wide frequency range, high accuracy, wide dynamic range, low noise, high throughput, and/or high input impedance. The thorough review of these advancements will provide valuable insights into the future development of impedance-readout ICs and systems for IoT and biomedical applications.

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.

Wearable Sensors for Respiration Monitoring: A Review

This paper provides an overview of flexible and wearable respiration sensors with emphasis on their significance in healthcare applications. The paper classifies these sensors based on their operating frequency distinguishing between high-frequency sensors, which operate above 10 MHz, and low-frequency sensors, which operate below this level. The operating principles of breathing sensors as well as the materials and fabrication techniques employed in their design are addressed. The existing research highlights the need for robust and flexible materials to enable the development of reliable and comfortable sensors. Finally, the paper presents potential research directions and proposes research challenges in the field of flexible and wearable respiration sensors. By identifying emerging trends and gaps in knowledge, this review can encourage further advancements and innovation in the rapidly evolving domain of flexible and wearable sensors.

Robust electrical impedance tomography for biological application: A mini review

Electrical impedance tomography (EIT) has been used by researchers across several areas because of its low-cost and no-radiation properties. Researchers use complex conductivity in bioimpedance experiments to evaluate changes in various indicators within the image target. The diverse volumes and edges of biological tissues and the large impedance range impose dedicated demands on hardware design. The EIT hardware with a high signal-to-noise ratio (SNR), fast scanning and suitable for the impedance range of the image target is a fundamental foundation that EIT research needs to be equipped with. Understanding the characteristics of this technique and state-of-the-art design will accelerate the development of the robust system and provide a guidance for the superior performance of next-generation EIT. This review explores the hardware strategies for EIT proposed in the literature.

High-Resolution and Multidimensional Phenotypes Can Complement Genomics Data to Diagnose Diseases in the Neonatal Population

Advances in genomic medicine have greatly improved our understanding of human diseases. However, phenome is not well understood. High-resolution and multidimensional phenotypes have shed light on the mechanisms underlying neonatal diseases in greater details and have the potential to optimize clinical strategies. In this review, we first highlight the value of analyzing traditional phenotypes using a data science approach in the neonatal population. We then discuss recent research on high-resolution, multidimensional, and structured phenotypes in neonatal critical diseases. Finally, we briefly introduce current technologies available for the analysis of multidimensional data and the value that can be provided by integrating these data into clinical practice. In summary, a time series of multidimensional phenome can improve our understanding of disease mechanisms and diagnostic decision-making, stratify patients, and provide clinicians with optimized strategies for therapeutic intervention; however, the available technologies for collecting multidimensional data and the best platform for connecting multiple modalities should be considered.

Real-Time Wrist Motion Decoding With High Framerate Electrical Impedance Tomography (EIT)

Human wrist motion decoding with a biological-signal-based interface is a key technique in the upper-limb exoskeleton and prosthesis control. One critical issue in this field is achieving high recognition precision and fast time response while against external disturbances of sensor re-wearing. In this study, we proposed a high-framerate Electrical Impedance Tomography (EIT) system combined with an adaptive recognition algorithm for real-time wrist kinematics decoding. The high-framerate EIT system was developed by a parallel stimulation-measurement sequence, and the sampling rate was as high as 104 Hz. Compared to the most widely used myoelectric techniques, the EIT-based interface can provide extra deep muscular spatial information with similar surface electrodes. It greatly benefited the subsequent recognition algorithms, in which the key EIT regions indicating muscle morphology kept consistent after an arbitrary sensor re-donning. The designed adaptive algorithm achieved equally high performance with an automatic update of the classifier mean values with a fast self-operated calibration process. We validated the approach on 12 subjects with a 2-dimensional Fitts' law test. The wrist gestures and joint angles were mapped to the direction and speed of the cursor movement, respectively. The average throughputs (TPs) of Fitts' law tests were 1.0269 ± 0.0971 bits/s and 1.0095 ± 0.0931 bits/s without and with sensor re-donning, respectively, which were comparable to the TPs of sEMG-based studies. The results showed the promise of the EIT-based interface on real-time human motion intent recognition. Future endeavors are worth being paid in this direction for more complicated robotic tasks.

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.

Artificial intelligence-driven wearable technologies for neonatal cardiorespiratory monitoring: Part 1 wearable technology

With the development of Artificial Intelligence techniques, smart health monitoring is becoming more popular. In this study, we investigate the trend of wearable sensors being adopted and developed in neonatal cardiorespiratory monitoring. We performed a search of papers published from the year 2000 onwards. We then reviewed the advances in sensor technologies and wearable modalities for this application. Common wearable modalities included clothing (39%); chest/abdominal belts (25%); and adhesive patches (15%). Popular singular physiological information from sensors included electrocardiogram (15%), breathing (24%), oxygen saturation and photoplethysmography (13%). Many studies (46%) incorporated a combination of these signals. There has been extensive research in neonatal cardiorespiratory monitoring using both single and multi-parameter systems. Poor data quality is a common issue and further research into combining multi-sensor information to alleviate this should be investigated. IMPACT STATEMENT: State-of-the-art review of sensor technology for wearable neonatal cardiorespiratory monitoring. Review of the designs for wearable neonatal cardiorespiratory monitoring. The use of multi-sensor information to improve physiological data quality has been limited in past research. Several sensor technologies have been implemented and tested on adults that have yet to be explored in the newborn population.

Characteristics and topic trends on electrical impedance tomography hardware publications

Objective: Electrical impedance tomography (EIT) is a technique to measure electrical properties of tissue. With the progress of modern integrated circuits and microchips, EIT instrumentation becomes an active research area to improve all aspects of device performance. Plenty of studies on EIT hardware have been presented in prestigious journals. This study explores publications on EIT hardware to identify the developing hotspots and trends. Method: Publications covering EIT hardware on the Web of Science Core Collection (WoSCC) database from 1989 to 2021 were collected for bibliometric analysis. CiteSpace and VOS viewer were used to study the characteristics of the publications. Main results: A total of 592 publications were analyzed, showing that the number of annual publications steadily increased. China, England, and South Korea were the most prolific countries on EIT hardware publications with productive native institutions and authors. Research topics spread out in "bio-electrical impedance imaging", "hardware optimization", "algorithms" and "clinical applications" (e.g., tissue, lung, brain, and oncology). Hardware research in "pulmonary" and "hemodynamic" applications focused on monitoring and were represented by silhouette recognition and dynamic imaging while research in "tumor and tissue" and "brain" applications focused on diagnosis and were represented by optimization of precision. Electrode development was a research focus through the years. Imaging precision and bioavailability of hardware optimization may be the future trend. Conclusion: Overall, system performance, particularly in the areas of system bandwidth and precision in applications may be the future directions of hardware research.

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

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

FPGA-Based Processor for Continual Capacitive-Coupling Impedance Spectroscopy and Circuit Parameter Estimation

In principle, the recently proposed capacitive-coupling impedance spectroscopy (CIS) has the capability to acquire frequency spectra of complex electrical impedance sequentially on a millisecond timescale. Even when the measured object with time-varying unknown resistance R_x is capacitively coupled with the measurement electrodes with time-varying unknown capacitance C_x, CIS can be measured. As a proof of concept, this study aimed to develop a prototype that implemented the novel algorithm of CIS and circuit parameter estimation to verify whether the frequency spectra and circuit parameters could be obtained in milliseconds and whether time-varying impedance could be measured. This study proposes a dedicated processor that was implemented as field-programmable gate arrays to perform CIS, estimate R_x and C_x, and their digital-to-analog conversions at a certain time, and to repeat them continually. The proposed processor executed the entire sequence in the order of milliseconds. Combined with a front-end nonsinusoidal oscillator and interfacing circuits, the processor estimated the fixed R_x and fixed C_x with reasonable accuracy. Additionally, the combined system with the processor succeeded in detecting a quick optical response in the resistance of the cadmium sulfide (CdS) photocell connected in series with a capacitor, and in reading out their resistance and capacitance independently as voltages in real-time.

Simplifying the hardware requirements for fast neural EIT of peripheral nerves

OBJECTIVE

The main objective of this study was to assess the feasibility of lowering the hardware requirements for fast neural EIT in order to support the distribution of this technique. Specifically, the feasibility of replacing the commercial modules present in the existing high-end setup with compact and cheap customized circuitry was assessed.

APPROACH

Nerve EIT imaging was performed on rat sciatic nerves with both our standard ScouseTom setup and a customized version in which commercial benchtop current sources were replaced by custom circuitry. Electrophysiological data and images collected in the same experimental conditions with the two setups were compared. Data from the customized setup was subject to a down-sampling analysis to simulate the use of a recording module with lower specifications.

MAIN RESULTS

Compound action potentials (573±287µV and 487±279µV, p=0.28) and impedance changes (36±14µV and 31±16µV, p=0.49) did not differ significantly when measured using commercial high-end current sources or our custom circuitry, respectively. Images reconstructed from both setups showed neglibile (<1voxel, i.e. 40µm) difference in peak location and a high degree of correlation (R2=0.97). When down-sampling from 24 to 16 bits ADC resolution and from 100KHz to 50KHz sampling frequency, signal-to-noise ratio showed acceptable decrease (<-20%), and no meaningful image quality loss was detected (peak location difference <1voxel, pixel-by-pixel correlation R2=0.99).

SIGNIFICANCE

The technology developed for this study greatly reduces the cost and size of a fast neural EIT setup without impacting quality and thus promotes the adoption of this technique by the neuroscience research community.

A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT's exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object's and the reconstruction domain's geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs' significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.

A Charge Balanced Neural Stimulator Silicon Chip for Human-Machine Interface

This paper proposes a neural stimulator silicon chip design with an improved charge balancing technology. The proposed neural stimulation integrated circuit (IC) uses two charge balancing modules including synchronous charge detection module and short-time pulse insertion module. The synchronous charge detection module is designed based on a current splitter with ultra-small output current and an integrator circuit for neural stimulation pulse width control, which greatly reduces the residual charge remained on the electrode-tissue interface. The short-time pulse insertion module is designed based on the electrode voltage detection and compensation current control, which further reduces the accumulated residual charge and keeps the electrode voltage within a safety range of ±25 mV during multiple stimulation cycles. Finally, this neural stimulator is implemented in TSMC 0.18-μm CMOS process technology, and the chip function is tested and verified in both experiments with the electrode-tissue RC model and the PBS saline solution environment. The measurement result shows the neural stimulator chip achieves improved charge balancing with the residual charge smaller than 0.95 nC, which is the lowest compared to the traditional neural stimulator chips.

System introduction and evaluation of the first Chinese chest EIT device for ICU applications

Chest electrical impedance tomography (EIT) is a promising application which is used to monitor the ventilation and perfusion of the lung at the bedside dynamically. The aim of the study was to introduce the first Chinese made chest EIT device for ICU application (Pulmo EIT-100). The system design of the hardware and software was briefly introduced. The performance of the system was compared to PulmoVista 500 (Dräger Medical) in healthy volunteers. The EIT system Pulmo EIT-100 consists of impedance measurement module, power supply module, PC all-in-one machine, medical cart and accessories. The performance of the system current source and voltage measurement unit was tested. A total of 50 healthy lung volunteers were prospectively examined. Subjects were asked to perform repetitive slow vital capacity (SVC) maneuvers with a spirometer. EIT measurements were performed in the following sequence during each SVC with: (1) Pulmo EIT-100, (2) PulmonVista500, (3) Pulmo EIT-100 and (4) PulmonVista500. Linearity and regional ventilation distribution of the reconstructed images from two devices were compared. The output frequency stability of the current source was 2 ppm. The amplitude error within one hour was less than 0.32‰. The output impedance of the current source was about 50kΩ. The signal-to-noise ratio of each measurement channel was ≥ 60 dB. For fixed resistance measurements, the measured values drifted about 0.08% within one hour. For human subjects, the correlations between the spirometry volume and EIT impedance from two devices were both 0.99 ± 0.01. No statistical significances were found in the parameters investigated. The repeatability (variability) of measures from the same device was comparable. Our EIT device delivers reliable data and might be used for patient measurement in a clinical setting.

Wearable Electrical Impedance Tomography Belt With Dry Electrodes

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

A FPGA-based adaptive differential current source for electrical impedance tomography

A high output impedance current source with a wide bandwidth is needed in electrical impedance tomography systems. Limitations appear mainly at higher frequencies and non-simple loads. In order to adjust the output current, the amplitude and phase are made to achieve the expected value automatically. A current source based on the field programmable gate array is designed. In this paper, we proposed a double DAC differential current source structure. By measuring the voltage of the sampling resistor in series with the load and using the proposed dynamic reference point demodulation algorithm, the actual current amplitude and phase on the load can be quickly obtained. Through the adaptive compensation module, the output current is adjusted to the expected value. The experimental results show that the output resistance of the current source can reach 10 MΩ and the output capacitance can be less than 0.8 pF in the frequency range of 10 kHz-1.28 MHz. At the same time, the current amplitude attenuation is less than 0.016%, and the phase error is less than 0.0025° after compensation. Therefore, the proposed current source achieves widebands, biocompatibility, and high precision.

Evaluation of Thoracic Equivalent Multiport Circuits Using an Electrical Impedance Tomography Hardware Simulation Interface

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography can be a valuable tool for monitoring patients. However, this technique is very sensitive to measurement noise or possible minor signal errors, coming from either the hardware, the electrodes, or even particular biological signals. Thus, the design of a good performance electrical impedance tomography hardware setup which properly interacts with the tissue examined is both an essential and a challenging concept. In this paper, we adopt an extensive simulation approach, which combines the system’s analogue and digital hardware, along with equivalent circuits of 3D finite element models that represent thoracic cavities. Each thoracic finite element model is created in MATLAB based on existing CT images, while the tissues’ conductivity and permittivity values for a selected frequency are acquired from a database using Python. The model is transferred to a multiport RLC network, embedded in the system’s hardware which is simulated at LT SPICE. The voltage output data are transferred to MATLAB where the electrical impedance tomography signal sampling and digital processing is also simulated. Finally, image reconstructions are performed in MATLAB, using the EIDORS library tool and considering the signal noise levels and different electrode and signal sampling configurations (ADC bits, sampling frequency, number of taps).

Analysis, Simulation, and Development of a Low-Cost Fully Active-Electrode Bioimpedance Measurement Module

A low-cost 1 kHz–400 kHz operating frequency fully-active electrode bioimpedance measurement module, based on Howland current source, is presented in this paper. It includes a buffered positive feedback Howland current source, implemented with operational amplifiers, as well as an AD8421 instrumentation amplifier, for the differential voltage measurements. Each active electrode module can be connected to others, assembling a wearable active electrode module array. From this array, 2 electrodes can be selected to be driven from a THS413 fully differential amplifier, activating a mirrored Howland current source. This work performs a complete circuit analysis, verified with MATLAB and SPICE simulations of the current source’s transconductance and output impedance over the frequency range between 1 kHz and 1 MHz. Resistors’ tolerances, possible mismatches, and the operational amplifiers’ non-idealities are considered in both the analysis and simulations. A comparison study between four selected operational amplifiers (ADA4622, OPA2210, AD8034, and AD8672) is additionally performed. The module is also hardware-implemented and tested in the lab for all four operational amplifiers and the transconductance is measured for load resistors of 150 Ω, 660 Ω, and 1200 Ω. Measurements showed that, using the AD8034 operational amplifier, the current source’s transconductance remains constant for frequencies up to 400 KHz for a 150 Ω load and 250 kHz for a 1200 Ω load, while lower performance is achieved with the other 3 operational amplifiers. Finally, transient simulations and measurements are performed at the AD8421 output for bipolar measurements on the 3 aforementioned load resistor values.

Locating Functionalized Gold Nanoparticles Using Electrical Impedance Tomography

OBJECTIVE

An imaging device to locate functionalized nanoparticles, whereby therapeutic agents are transported from the site of administration specifically to diseased tissues, remains a challenge for pharmaceutical research. Here, we show a new method based on electrical impedance tomography (EIT) to provide images of the location of gold nanoparticles (GNPs) and the excitation of GNPs with radio frequencies (RF) to change impedance permitting an estimation of their location in cell models Methods: We have created an imaging system using quantum cluster GNPs as a contrast agent, activated with RF fields to heat the functionalized GNPs, which causes a change in impedance in the surrounding region. This change is then identified with EIT.

RESULTS

Images of impedance changes of around 804% are obtained for a sample of citrate stabilized GNPs in a solution of phosphate-buffered saline. A second quantification was carried out using colorectal cancer cells incubated with culture media, and the internalization of GNPs into the colorectal cancer cells was undertaken to compare them with the EIT images. When the cells were incubated with functionalized GNPs, the change was more apparent, approximately 402%. This change was reflected in the EIT image as the cell area was more clearly identifiable from the rest of the area.

SIGNIFICANCE

EIT can be used as a new method to locate functionalized GNPs in human cells and help in the development of GNP-based drugs in humans to improve their efficacy in the future.

An Imaged Based Method for Universal Performance Evaluation of Electrical Impedance Tomography Systems

This paper describes a simple and reproducible method for universal evaluation of the performance of electrical impedance tomography (EIT) systems using reconstructed images. To address the issues where common electrical parameters are not directly related to the quality of EIT images, based on objective full reference (FR) image quality assessment, the method provides a visually distinguishable hot colormap and two new FR metrics, the global and the more specific 'region of interest'. A passive 16 electrode EIT system using an application specific integrated circuit front-end was used to evaluate the proposed method. The measured results show, both visually and in terms of the proposed FR metrics, the impact on recorded EIT images with different design parameters and non-idealities. The paper also compares the image results of a passive electrode system with a matched 'single variable' active electrode system and demonstrates the merit of an active electrode system for noise interference. A figure of merit based on the FR metrics is proposed.

Model Selection Based Algorithm in Neonatal Chest EIT

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models. Absolute/static image reconstruction is performed as the core of the posterior probability calculations. The validity and reliability of the algorithm in detecting a suitable model in the presence of measurement noise is studied with simulated and measured data from 11 patients. The paper also demonstrates the potential improvements on the clinical parameters extracted from EIT images by considering a unique case study with a neonate patient undergoing computed tomography imaging as clinical indication prior to EIT monitoring. Two well-known image reconstruction techniques, namely GREIT and tSVD, are implemented to create the final tidal images. The impacts of appropriate model selection on the clinical extracted parameters such as center of ventilation and silent spaces are investigated. The results show significant improvements to the final reconstructed images and more importantly to the clinical EIT parameters extracted from the images that are crucial for decision-making and further interventions.

Development of a Portable, Reliable and Low-Cost Electrical Impedance Tomography System Using an Embedded System

Electrical impedance tomography (EIT) is a useful procedure with applications in industry and medicine, particularly in the lungs and brain area. In this paper, the development of a portable, reliable and low-cost EIT system for image reconstruction by using an embedded system (ES) is introduced herein. The novelty of this article is the hardware development of a complete low-cost EIT system, as well as three simple and efficient algorithms that can be implemented on ES. The proposed EIT system applies the adjacent voltage method, starting with an impedance acquisition stage that sends data to a Raspberry Pi 4 (RPi4) as ES. To perform the image reconstruction, a user interface was developed by using GNU Octave for RPi4 and the EIDORS library. A statistical analysis is performed to determine the best average value from the samples measured by using an analog-to-digital converter (ADC) with a capacity of 30 kSPS and 24-bit resolution. The tests for the proposed EIT system were performed using materials such as metal, glass and an orange to simulate its application in food industry. Experimental results show that the statistical median is more accurate with respect to the real voltage measurement; however, it represents a higher computational cost. Therefore, the mean is calculated and improved by discarding data values in a transitory state, achieving better accuracy than the median to determine the real voltage value, enhancing the quality of the reconstructed images. A performance comparison between a personal computer (PC) and RPi4 is presented. The proposed EIT system offers an excellent cost-benefit ratio with respect to a traditional PC, taking into account precision, accuracy, energy consumption, price, light weight, size, portability and reliability. The proposed EIT system has potential application in mechanical ventilation, food industry and structural health monitoring.

Low Power Bio-Impedance Sensor Interfaces: Review and Electronics Design Methodology

Assessing blood flow, respiration patterns, and body composition with wearable and noninvasive bio-impedance (BioZ) sensors has distinctive advantages over the conventional clinical practice. The merits of BioZ sensors derive from having long-term monitoring capability and improved user friendliness. These open up the way to build medical grade wearable devices for chronic conditions. Low power, high precision BioZ sensor interface IC is the heart of such devices, it also determines the signal integrity of the overall system. Nevertheless, electrical design challenges from both circuit and system perspective still need to be addressed. This paper reviews the pioneering BioZ interface ICs and systems, and proposes major electrical specifications for wearable BioZ sensors. System design methodologies and circuit optimization techniques are summarized as guidelines to develop the next generation BioZ interface electronics.

Analog Realization of Fractional-Order Skin-Electrode Model for Tetrapolar Bio-Impedance Measurements

This work compares two design methodologies, emulating both AgCl electrode and skin tissue Cole models for testing and verification of electrical bio-impedance circuits and systems. The models are based on fractional-order elements, are implemented with active components, and capture bio-impedance behaviors up to 10 kHz. Contrary to passive-elements realizations, both architectures using analog filters coupled with adjustable transconductors offer tunability of the fractional capacitors’ parameters. The main objective is to build a tunable active integrated circuitry block that is able to approximate the models’ behavior and can be utilized as a Subject Under Test (SUT) and electrode equivalent in bio-impedance measurement applications. A tetrapolar impedance setup, typical in bio-impedance measurements, is used to demonstrate the performance and accuracy of the presented architectures via Spectre Monte-Carlo simulation. Circuit and post-layout simulations are carried out in 90-nm CMOS process, using the Cadence IC suite.

Time Stamp - A Novel Time-to-Digital Demodulation Method for Bioimpedance Implant Applications

Bioimpedance analysis is a noninvasive and inexpensive technology used to investigate the electrical properties of biological tissues. The analysis requires demodulation to extract the real and imaginary parts of the impedance. Conventional systems use complex architectures such as I-Q demodulation. In this paper, a very simple alternative time-to-digital demodulation method or 'time stamp' is proposed. It employs only three comparators to identify or stamp in the time domain, the crossing points of the excitation signal, and the measured signal. In a CMOS proof of concept design, the accuracy of impedance magnitude and phase is 97.06% and 98.81% respectively over a bandwidth of 10 kHz to 500 kHz. The effect of fractional-N synthesis is analysed for the counter-based zero crossing phase detector obtaining a finer phase resolution (0.51˚ at 500 kHz) using a counter clock frequency ( f_clk = 12.5 MHz). Because of its circuit simplicity and ease of transmitting the time stamps, the method is very suited to implantable devices requiring low area and power consumption.

A 1 MHz Miniaturized Electrical Impedance Tomography System for Prostate Imaging

An ASIC for a high frequency electrical impedance tomography (EIT) imaging system for prostate cancer screening is presented. The ASIC enables a small form-factor architecture, which ensures high signal-to-noise ratio (SNR) at MHz frequencies. The 4-channel ASIC was designed and fabricated in a standard CMOS 0.18- μm technology and integrates a novel current driver for current stimulus, instrumentation amplifier to interface with the tissue, VGA to provide variable gain and ADC with SPI interface for digitization. A prototype miniaturized EIT system was built and it was evaluated using a model transrectal imaging probe immersed into a tank filled with saline and a metal inclusion that demonstrated the open-domain problem of imaging prostate cancer lesion. The system maintained an SNR between 66 and 76 dB over the frequency range of 500 Hz to 1 MHz. Also, it produced reconstructed EIT images that depicted the presence of the small metal inclusion that modeled a prostate cancer imaging application.

A Novel General Purpose Combined DFVF/VCII Based Biomedical Amplifier

We here present a 0.15 µm CMOS high input impedance and low noise AC coupled flipped voltage follower-based amplifier for high integration level in integrated circuits in a wide range of sensing applications. With such a circuit, it is possible to achieve a high level of integration, thanks to the absence of passive resistors, and also to implement a very high input impedance without capacitive feedback thanks to bootstrap operation, thus offering a very low high-pass cutoff frequency. Simulated results with a proven and well modeled standard technology show a whole circuit input-referred noise of 5.4 µVrms. The bias voltage is ±0.6 V with a total power consumption of the single amplifier of 20 µW. The very low circuit complexity allows a very low estimated reduced area occupation giving, as a general example, the possibility of integrating an array of up to thousands of channels for biomedical applications. Detailed simulation results, PVT analysis and comparison tables are also presented in the paper.

A Parametric EIT System Spice Simulation with Phantom Equivalent Circuits

In this paper a number of LT Spice simulations have been carried out on an Electrical Impedance Tomography (EIT) system, which includes the whole analog and digital circuitry as well as the subject to be examined (phantom model). The aim of this study is to show how the analog and digital parts, the electrodes and the subject’s physical properties may impact the measurements and the quality of the reconstructed image. This could provide a useful tool for designing an EIT system. Special attention has been given to the current source’s output impedance and swing, to the noise produced by the circuits and to the Analog to Digital Converters (ADCs) resolution and sampling rate. Furthermore, some 3D phantom subjects have been modeled and simulated as equivalent circuits, merged with the EIT simulated hardware, in order to observe how changes on their properties interact with the whole circuitry and affect the final result. Observations show that mirrored current sources with z o u t > 350 k Ω and sufficiently high ADC acquisition sampling rate ( f s a m p l e ≥ 16 f i n ) can result to accurate impedance measurements and therefore quality image reconstruction within a frequency span of at least 10 to 100 kHz. Moreover, possible hardware failures (electrode disconnections and imbalanced contact impedances) can be detected with a simple examination of the first extracted image and measurement set, so that by direct modification of the reconstruction process, a corrected result can be obtained.