Abstract

Info

Title:: Magnetocardiogram source reconstruction based on principal eigenvector of signal subspace

Author(s):: LI Haoran; ZHU Junjie; School of Electrical Engineering and Automation, Henan Polytehinc University, Jiaozuo 454000, China

Keywords:: Keywords: cardiac electrical activity magnetocardiogram inverse problem beamforming

Abstract:: Abstract: In the noninvasive imaging of cardiac electrical activity using magnetic field data measured on human body surface, when the signal-to-noise ratio is low, the minimum variance beamforming (MVB) method has poor ability of noise reduction in the reconstruction of the source of cardiac magnetic signal. Herein an improved beamforming method based on the principal eigenvector of signal subspace (ISPEB) which combines constraint matrix with SPEB method is proposed. The strategies of signal subspace projection and noise spatial spectral intensity normalization based on principal eigenvector are adopted for constraining the noise power and its gain output by spatial filter, and compensating the effect of signal principal eigenvector on the uniformity of noise spatial spectral intensity distribution. By comparing the performance of SPEB, ISPEB and MVB, the results show that ISPEB is superior to SPEB and MVB in source reconstruction. Finally, SPECB, ISPEB and MVB are separately used to conduct source reconstruction imaging on 61 channel R wave peak time cardiac magnetic field data of two healthy individuals, and the results showed that both SPECB and ISPEB perform well in source reconstruction and had high accuracy for source reconstruction.