RESUMO
The numerical accuracy of the boundary element (BE) method used to solve the volume conduction problem of nested compartments, each having a homogeneous conductivity, is studied. The following techniques for improving this accuracy are discussed: the handling of the auto solid angle element omega ii, the overall refinement of the level of discreteness, the use of a locally refined discrete grid, the isolated problem approach, and an adaptive refined computation of the discrete surface integrals involved in the BE method. The effects of these techniques on the numerical accuracy of the computed electrical potentials are illustrated by taking a volume conductor consisting of four concentric spheres representing the head since for this model an analytical (exact) solution is available. The techniques are of importance for numerically computed electroencephalograms (EEG's) since the numerically computed surface EEG's are severely affected by the relatively low conductivity of the compartment representing the skull.
Assuntos
Encéfalo/fisiologia , Eletroencefalografia , Modelos Biológicos , Condutividade Elétrica , Humanos , MatemáticaRESUMO
The ability to exchange in a meaningful, secure, and simple fashion relevant healthcare data about patients is seen as vital in the context of efficient and cost-effective shared or team-based care. The electronic healthcare record (EHCR) lies at the heart of this information exchange, and it follows that there is an urgent need to address the ability to share EHCR's or parts of records between carers and across distributed health information systems. This paper presents the Synapses approach to sharing based on a standardized shared record, the Federated Healthcare Record, which is implemented in an open and flexible manner using the Common Object Request Broker Architecture (CORBA). The architecture of the Federated Healthcare Record is based on the architecture proposed by the Technical Committee 251 of the European Committee for Standardization.