MagnetoEncephaloGraphy (MEG) devices are helmet–shaped arrays of sensors that measure the tiny magnetic fields produced by neural currents. As they operate at low temperature, they are typically immersed in liquid helium. However, during the cooling process the sensor position and shape can change, with respect to nominal values, due to thermal stress. This implies that an accurate sensor calibration is required before a MEG device is utilized in either neuroscientific research or clinical workflow. Here we describe a calibration scheme developed for the optimal use of a MEG system recently realized at the “Istituto di Cibernetica e Biofisica” of the Italian CNR. To achieve the calibration goal a dedicated magnetic source is used (calibration device) and the geometric parameters of the sensors are determined through an optimisation procedure, based on the Nelder-Mead algorithm, which maximises the correlation coefficient between the predicted and the recorded magnetic field. Then the sensitivity of the sensors is analytically estimated. The developed calibration procedure is validated with synthetic data mimicking a real scenario.
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