Electrical impedance tomography device of electrodes 32

Abstract

The invention relates to an electrical impedance tomography device of electrodes 32. Channel 32 multi-way switches are adopted for constructing an electrical impedance tomography system of an electrode 32 physical model, in this way, the complexity of obtaining channels 32 through connecting channel 16 multi-way switches in parallel is lowered, control is easier compared with simulation matrix switches, performance is better, and the collection precision of the system is improved. For a control module, a processor ARM9 is adopted according to the design, serves as an embedded microprocessor of the electrical impedance tomography system, has high control capacity and data processing capacity, and improves the collection speed and real-time performance of the system, and many interfaces facilitate expanding of more functions of the system. In addition, for a high-precision instrument amplifier, a variable gain amplifying circuit is further introduced, the high-precision instrument amplifier and the variable gain amplifying circuit form a two-stage amplifying circuit, in this way, changes of gains can be controlled in a programmed mode, the amplification factor of collected voltage signals is increased, the flexibility of the collected voltage signals is improved, and follow-up processing of the signals is facilitated.

Description

technical field [0001] The invention relates to a 32-electrode electrical impedance imaging device, which belongs to the technical field of medical detection. Background technique [0002] Electrical Impedance Tomography (EIT) is a new imaging technology based on biomedicine. Its basic principle is that different biological tissues have different electrical impedances. Changes in electrical impedance. Due to its non-destructive, non-radiation and non-invasive characteristics, it has aroused extensive research in the fields of geophysics, environmental monitoring, non-destructive testing and medical testing. It injects excitation current signals into the organism through the corresponding electrode system, obtains the voltage signal from the electrodes, and uses a specific algorithm to reconstruct the graph reflecting the internal electrical characteristics of the organism, so as to obtain relevant information such as the structure and function of the internal tissues and or...

AI Technical Summary

Problems solved by technology

In 1998, Margaret Cheney of the United States adopted a 32-electrode multi-current excitation mode and conducted research on the optimal excitation current mode with human simulated organs as the experimental object. The experimental results have improved, but the image resolution is still not ideal.

In 2008, the Oxford Brookes group in the United Kingdom developed the OXBACT-5 imaging system, which can monitor chronic heart failure. It has a 16-channel multi-frequency sinusoidal excitation source, and uses FPGA to realize multi-frequency digital quadrature sequence demodulation. The system is relatively complex

[0004] The difficulties of the existing technology are mainly manifested in: it is necessary to generate a current source with stable amplitude, high precision and high output impedance, but in practice the load impedance of the current source is always limited, and it is impossible to meet the requirements unlimitedly; the EIT system can The amount of collected information is small. Although the amount of measurement data can be increased by increasing the number of electrodes, this will make the hardware system complex, and the increase in the number of electrodes is also limited; the inverse problem of electrical impedance imaging is pathological , a small disturbance of the boundary voltage data will cause a huge change in the solution, and the current electrical impedance imaging algorithm has a low resolution for the center of the object, but a high resolution for the boundary, so the reconstructed image is not ideal. Imaging algorithms with high quality and high precision need to be designed

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