A comparison of techniques to optimize measurement of voltage changes in electrical impedance tomography by minimizing phase shift errors

FPGA-based voltage and current dual drive system for high frame rate electrical impedance tomography

Electrical impedance tomography (EIT) is used to image the electrical property distribution of a tissue under test. An EIT system comprises complex hardware and software modules, which are typically designed for a specific application. Upgrading these modules is a time-consuming process, and requires rigorous testing to ensure proper functioning of new modules with the existing ones. To this end, we developed a modular and reconfigurable data acquisition (DAQ) system using National Instruments' (NI) hardware and software modules, which offer inherent compatibility over generations of hardware and software revisions. The system can be configured to use up to 32-channels. This EIT system can be used to interchangeably apply current or voltage signal, and measure the tissue response in a semi-parallel fashion. A novel signal averaging algorithm, and 512-point fast Fourier transform (FFT) computation block was implemented on the FPGA. FFT output bins were classified as signal or noise. Signal bins constitute a tissue's response to a pure or mixed tone signal. Signal bins' data can be used for traditional applications, as well as synchronous frequency-difference imaging. Noise bins were used to compute noise power on the FPGA. Noise power represents a metric of signal quality, and can be used to ensure proper tissue-electrode contact. Allocation of these computationally expensive tasks to the FPGA reduced the required bandwidth between PC, and the FPGA for high frame rate EIT. In 16-channel configuration, with a signal-averaging factor of 8, the DAQ frame rate at 100 kHz exceeded 110 frames s (-1), and signal-to-noise ratio exceeded 90 dB across the spectrum. Reciprocity error was found to be for frequencies up to 1 MHz. Static imaging experiments were performed on a high-conductivity inclusion placed in a saline filled tank; the inclusion was clearly localized in the reconstructions obtained for both absolute current and voltage mode data.

Calibration methods for a multi-channel multi-frequency EIT system

Multi-channel multi-frequency electrical impedance tomography (EIT) systems require a careful calibration to minimize systematic errors. We describe novel calibration methods for the recently developed KHU Mark1 EIT system. Current source calibration includes maximization of output resistance and minimization of output capacitance using multiple generalized impedance converters. Phase and gain calibrations are used for voltmeters. Phase calibration nulls out the total system phase shift in measured voltage data. Gain calibrations are performed in two steps of intra- and inter-channel calibrations. Intra-channel calibration for each voltmeter compensates frequency dependence of its voltage gain and also discrepancy between design and actual gains. Inter-channel calibration compensates channel-dependent voltage gains of all voltmeters. Using the calibration methods described in this paper, we obtained 1 MOmega minimal output impedance of the current source in the frequency range 10 Hz-500 kHz. The reciprocity error was as small as 0.05% after intra- and inter-channel voltmeter calibrations. To demonstrate effects of calibration in reconstructed images, we used a homogenous phantom from which uniform images should be produced. Reconstructed time- and frequency-difference images using uncalibrated data showed spurious anomalies. By using calibrated data, standard deviations of time- and frequency-difference images of the homogenous phantom were reduced by about 40% and 90%, respectively.

A review of errors in multi-frequency EIT instrumentation

Multi-frequency electrical impedance tomography (MFEIT) was proposed over 10 years ago as a potential spectroscopic impedance imaging method. At least seven systems have been developed for imaging the lung, heart, breast and brain, yet none has yet achieved clinical acceptance. While the absolute impedance varies considerably between different tissues, the changes in the spectrum due to physiological changes are expected to be quite small, especially when measured through a volume. This places substantial requirements on the MFEIT instrumentation to maintain a flat system frequency response over a broad frequency range (dc-MHz). In this work, the EIT measurement problem is described from a multi-frequency perspective. Solutions to the common problems are considered from recent MFEIT systems, and the debate over four-terminal or two-terminal (multiple source) architecture is revisited. An analysis of the sources of MFEIT errors identifies the major sources of error as stray capacitance and common-mode voltages which lead to a load dependence in the frequency response of MFEIT systems. A system that employs active electrodes appears to be the most able to cope with these errors (Li et al 1996). A distributed system with digitization at the electrode is suggested as a next step in MFEIT system development.

Bioimpedance tomography (electrical impedance tomography)

Electrical impedance tomography (EIT) is a relatively new imaging method that has evolved over the past 20 years. It has the potential to be of great value in clinical diagnosis; however, EIT is a technically difficult problem to solve in terms of developing hardware for data capture and the algorithms to reconstruct the images. This review looks at the development of EIT and how it has evolved. It focuses on its clinical applications, examining hardware for the collection of data and reconstruction algorithms to generate images. Finally, this review looks at future developments that are evolving from EIT. These new variations use mixed modalities that may produce interesting new clinical imaging tools.

Electrical impedance tomography spectroscopy (EITS) for human head imaging

Electrical impedance tomography (EIT) is a recently developed medical imaging method which has practical advantages for imaging brain function as it is inexpensive, rapid and portable. Its principal use in validated human studies to date has been to image changes in impedance at a single excitation frequency over time, but there are potential applications where it is desirable to obtain images from a single point in time, which could be achieved by imaging over multiple frequencies. We describe a novel multifrequency EIT design which provides up to 64 electrodes for imaging in the head. This was achieved by adding a multiplexer to a single channel of an existing system, the Sheffield Mark 3.5. This provides a flexible protocol for addressing up to 64 electrodes but CMRR decreases from 90 dB to 80 dB and analogue amplifier bandwidth from > 1.6 MHz to 0.8 MHz. This did not significantly affect performance, as cylinders of banana, 10% of the diameter of a saline filled spherical tank, could be visualized with frequency referenced imaging. The design appears to have been an acceptable compromise between practicality and performance and will now be employed in clinical trials of multifrequency EIT in stroke, epilepsy and neonatal brain injury.

A comparison of headnet electrode arrays for electrical impedance tomography of the human head

Three types of commercially available headnet electrode arrays, designed for use in EEG, and conventional EEG Ag/AgCl cup electrodes were tested on human subjects, and a realistic, saline-filled head-shaped tank was prepared with vegetable skin to simulate human skin in order to determine the optimum electrode system for electrical impedance tomography (EIT) of the human head. Impedance changes during EIT acquisition were produced in healthy volunteers during a finger-thumb apposition task and in tanks by the insertion of a Perspex rod. Signal-to-baseline noise, measured from raw EIT data, was 2.3 +/- 0.3 and 2.3 +/- 0.2 for the human and tank data, respectively. In both the human and tank experiments, a commercial hydrogel elasticated electrode headnet produced the least amount of baseline noise, and was the only headnet in the human data with noise levels acceptable for EIT imaging. Image quality measured in the tank was similar for most of the headnets tested, except that the EEG electrodes produced a higher positional error and electrodes in a geodesic elasticated net produced images with worse subjective image quality. Overall, the hydrogel elasticated headnet was judged to be the most suitable for human neuroimaging with EIT.