Magnetocardiography Detection and Source Localization From Multiple Sources Using Magnetoimpedance Principle in Controlled Environment

Recent advances in non-invasive cardiac imaging techniques have highlighted the potential of Magnetocardiography (MCG) as a powerful diagnostic tool. However, existing approaches face significant challenges in accurately localizing and characterizing cardiac electrical sources. This study presents an innovative methodology for cardiac source localization using magnetocardiography based on the magnetoimpedance principle, addressing these limitations through an experimental framework and sophisticated computational approaches. This work has established a novel lead field matrix computation methodology that shows the relationship between source currents and resulting magnetic fields. The forward problem was solved using known source configurations and validated against experimental measurements. For the inverse problem, three mathematical approaches were implemented: Minimum Norm Estimation (MNE), Empirical covariance, and Gaussian Process Variance methods. Results demonstrate that the overall experimental setup successfully replicates key aspects of cardiac electromagnetic activity, with the MI sensor array providing sufficient spatial and temporal resolution for accurate source localization. The novel lead field computation method significantly improved source reconstruction accuracy compared to conventional approaches. This work establishes a foundation for cost-effective high-sensitivity magnetocardiographic systems that could enhance clinical cardiac diagnostics without the need for magnetically shielded environments.