Multiple signal source localization from spatio-temporal magnetocardiogram

Mosher et al. (1992) have proposed a new method to localize multiple dipoles from spatio-temporal biomagnetic data. The method is based on the multiple signal classification (MUSIC) developed in the field of array signal processing. However, the MUSIC fails to produce good solutions in some situations where time series from multiple dipoles are strongly correlated, multiple dipoles are closely spaced, or signal to noise ratio of time series is low. To improve the performance of the MUSIC, we propose new localization methods based on the subspace fitting framework developed by Viberg and Ottersten (1991). Simulation studies demonstrate that the new methods produce better solutions than the MUSIC in the above mentioned ill-conditioned situations. Furthermore, we apply these methods to real magnetocardiograms measured by using 64 channel SQUID magnetometers