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Introduction
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sors, and any pieces of magnetized material in/on the body may cause
very large disturbances.
Identification and suppression of the S T -space components require additional knowledge of the temporal dynamics. Spatio-temporal extension to
Maxwell filtering, called MaxST, widens significantly the software shielding capability of MaxFilter, because MaxST can suppress also internal
interferences that arise in the S T -space or very close to it. Such internal
interferences can be caused, for example, by magnetized pieces in/on the
subject's head (such as dental work, braces, or magnetized left-overs in
burr-holes), or by pacemakers or stimulators attached to the patient.
Maxwell filtering inherently transforms measured MEG signals into virtual channels in terms of harmonic function amplitudes. Because the virtual channels are independent of the device, they offer a straightforward
method for estimating corresponding MEG signals in other sensor arrays.
This function called MaxMove provides an elegant way to transfer MEG
signals between different head positions and to compensate for disturbances caused by head movements during recordings.
The mathematical basis of Maxwell filtering is described briefly in
Appendix A. The Signal Space Separation algorithms and their applications are discussed in detail in:
1. S. Taulu, M. Kajola, and J. Simola. Suppression of interference and
artifacts by the signal space separation method. Brain Topography
16(4), 269-275, 2004.
2. S. Taulu, and M. Kajola. Presentation of electromagnetic multichannel
data: the signal space separation method. Journal of Applied Physics,
97(12), 124905, June 2005.
3. S. Taulu, J. Simola, and M. Kajola. Applications of the signal space
separation method. IEEE Transactions on Signal Processing, 53(9),
3359-3372, 2005.
4. S. Taulu, and J. Simola. Spatiotemporal signal space separation method
for rejecting nearby interference in MEG measurements. Physics in
Medicine and Biology, 51, 1759-1768, 2006.
NM21993A
2006-10-31
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