Coupling Testing For Biological Magnetic Induction Tomography

Currently, health issues have become a hot topic among the international communities. The requirements of disease prevention and treatment promote the development in biomedical technology rapidly. Consequently, it will be an irresistible trend that innovations of biomedical examination system employ the combination of morphology and function. As a non-invasive, harmless and functional tomography, biomedical electromagnetic tomography is more suitable for long term biomedical imaging monitoring or medical screenings in a wide range because of the simple system structure, easily realized, low cost and without significantly harmful driving source to human body, like nuclide and radiation.Base on the electrical sensing theory, magnetic induction tomography started late; however, it has obvious benefits and also acquires wide attentions in industry processing and biomedical field from domestic and overseas. The explorations on magnetic induction tomography were mainly focused on cross section distribution testing meachnism for magnetic induction tomography, testing system realiazion for different applicaitons, testing data processing and imaging reconstruction with different methods, et al. Owing to the special features of objects in biomedical field applications, magnetic induction tomography still has to be discussed and analyzed deeply in testing mechanism and requirements, structure and function of testing system and processing and representation of testing information.With the combinations of advanced numerical simulation techniques, signal processing methods and circuit and sytem technologies, the topic oriented the improvement of magnetic induction tomography application foundation researches and work on the coupling testing mechanism, testing method, testing system, and testing signal processing. The main work has been finished as following.(1) Analyze the factors that would affect the magnetic induction tomography sensing field and optimize the structure of sensing array. Base on the finite element simulation method, aimat the affected factors for the sensing field distribution that conclude of the frequency of excitation signal, excitation strategies and medium distribution in sensing field, use numerical simulation and sensitivity matrix calculations to compare the responses. A higher excitation frequency could increase the response of system, but it also could amplify the detection errors. Compare three different excitation strategies, single excitation strategy should be considered first on account of the simple hardware structure and easy implementation. Base on results of the direct phase measurement, the conductivity of detected object satisfies the linear relationship with the phase of measurement. Base on the impedance analyses of sensor array to optimize the sensor structure, match the sensitive frequency range of sensor array with the excitation frequency that drive the system and improve the testing effectiveness of system.(2) Build an eight channel magnetic induction tomography system which is hoped to apply in biomedical testing. Base on the structure design of system function, it is possible to suitable both for traditional sensor array and balanced coils by changing the connections design of hardware which increase the adaption of hardware and extend the applications of system. Select data acquisition boards and collect the high frequency signal directly which could guarantee the system function, reduce the complexity in hardware design and shorten the system design cycle. The testing system also finishes the signal on-line/ off-line processing and monitoring and image reconstruction. According to the tests of sytem, the system platform is possible to satisfy the demands in detection.(3) Analyze the magntic induction responses for detection object with internal signal. Both conduct the work in numerical simulations and experiment verifications; take the electroencephalogram signal as an example of internal signal. Discuss and analyze the coupling effects on results of testing system caused by the internal signal and excitation signal. According to the imaging resultsof simulations, the detection object exists a shifting in reconstruction image. The experiment results also vertify that the internal signal would lead direct effects in system detection and the effects could not be ignored.(4) Select independent component analysis to achieve the signal separation and recognition. Aiming at the coupling action of internal signal and excitation signal on system detection, apply independent component analysis to implement the signal separation and extract the signal features to recognize different internal signals by calculation the high order statistics of signals. Apply the multi-separation method to process the measurements from multi-dipole source model, and it is possible to recover the incomplete separation problem for once separation in such signal processing and finish the signal recognition effectively.