The Signal Space Separation method

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dc.creatorTaulu, Samu
dc.creatorKajola, Matti
dc.creatorSimola, Juha
dc.date2004-01-30
dc.date.accessioned2026-07-07T05:51:07Z
dc.date.available2026-07-07T05:51:07Z
dc.descriptionMultichannel measurement with hundreds of channels essentially covers all measurable degrees of freedom of a curl and source free vector field, like the magnetic field in a volume free of current sources (e.g. in magnetoencephalography, MEG). A functional expansion solution of Laplace's equation enables one to separate signals arising from the sphere enclosing the interesting sources, e.g. the currents in the brain, from the rest of the signals. The signal space separation (SSS) is accomplished by calculating individual basis vectors for each term of the functional expansion solution to create a signal basis covering all measurable signal vectors. Any signal vector has a unique SSS decomposition with separate coefficients for the interesting signals and signals coming from outside the interesting volume. Thus, SSS basis provides an elegant method to remove external disturbances, and to transform the interesting signals to virtual sensor configurations. SSS can also be used in compensating the movements of the subject and removing the artefacts caused by magnetized particles in the subject.
dc.descriptionFour pages, six figures. To appear in Proceedings of 14th Conference of the International Society for Brain Electromagnetic Topography (ISBET), Nov 19-23, 2003, Santa Fe, NM
dc.identifierhttps://arxiv.org/abs/physics/0401166
dc.identifierhttp://arxiv.org/abs/physics/0401166
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/85923
dc.subjectInstrumentation and Detectors
dc.subjectMedical Physics
dc.titleThe Signal Space Separation method
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