Performance of Signal Space Separation Depending on Sensor Array Arrangement in Biomagnetic Measurements
Signal source separation (SSS) has widely been adopted for magnetoencephalography (MEG) to reduce external magnetic noise interference. The basic idea of SSS is based on decomposing measured fields into spherical harmonic bases. Due to the feature, the performance of SSS strongly depends on the shape of a measuring sensor array. In this article, we show the noise reduction performances in several different shapes of the sensor and array and demonstrate SSS is only effective for a non-spherical sensor array or for a gradiometric arrangement.
K. W. Kim et al., "Performance of Signal Space Separation Depending on Sensor Array Arrangement in Biomagnetic Measurements", Key Engineering Materials, Vols. 480-481, pp. 1418-1425, 2011