Abstract
Abstract 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.
It has immense applications in medical fields. For example in field of breast cancer cure, EIT has been used to map the electrical properties of breast at signal frequencies ranging from few Hz to 1Mhz.The electrical impedance of different tissues is made the criteria for differentiating the tissues. The electrical impedance of the tissues is measured and an algorithm is employed to generate the detailed image from the impedance measurement data.
In clinical applications also includes:
-monitoring of pulmonary activity
-gastric emtiying
-Brain function
It has been suggested that minimum signal-to-noise ratio (SNR) of 60 dB is necessary for distinguishing between two different impedance distributions.
For attaining high degree of accuracy:
-complex circuits are designed to negate the parasitic impedance along the analog path.
-model the circuit to determine the individual parasitic elements within the measurement path.
-As the frequency ofmeasurement increases, design high frequency models for the parasitic impedance.
instead measure each channelâ„¢s frequency de- pendent parasitic impedance and correct the subsequent mea- sured voltages through a calibration procedure. This provides a mechanism for compensating for both low and high order effects associated with a particular signal frequency without resorting to complex circuitry or modeling.
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