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Iterative Optimization Algorithm to Design Biplanar Coils for Dynamic Magnetoencephalography

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In this article, an iterative optimization algorithm is proposed to design biplanar coils, which is used for dynamic magnetoencephalography to compensate for residual fields in the magnetic shielding room. The… Click to show full abstract

In this article, an iterative optimization algorithm is proposed to design biplanar coils, which is used for dynamic magnetoencephalography to compensate for residual fields in the magnetic shielding room. The effects of magnetic shielding layers and plane’s side length on the uniformity are both considered for designing coils. The iterative calculation is used to minimize the side length of the coil plane. The biplanar coils with 1.3-m side length are designed, which consist of three homogeneous-field coils ($B_{x}, B_{y},\; { \rm and }\; B_{z}\; { \rm coils }$) and five gradient-field coils ($dB_{x}/dy, dB_{x}/dz, dB_{y}/dy, dB_{y}/dz,\; { \rm and }\; dB_{z}/dz\; { \rm coils }$). The coil system can produce homogeneous and gradient fields within 1% error over the volume of 40 cm × 40 cm × 40 cm. Through active magnetic shielding, the central field inside the magnetic room is reduced from 7.56 to 0.17 nT, and standard deviation from the mean value in the target area falls from 1.366 to 0.177 nT. The dynamic auditory stimulation experiment proves that the biplanar coil system will improve the quality of the evoked signals.

Keywords: iterative optimization; optimization algorithm; design biplanar; biplanar; dynamic magnetoencephalography; biplanar coils

Journal Title: IEEE Transactions on Industrial Electronics
Year Published: 2023

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