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Evaluation of signal space separation via simulation

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Abstract

Signal space separation (SSS) method is an advanced signal-processing approach that can be used to recover bio-magnetic signal and remove external disturbance in empirical magnetoencephalography (MEG) measurements. SSS is based on the solution of the quasi-static approximation of Maxwell equations (i.e., Laplace’s equation) which can be expressed as linear combinations of spherical harmonic functions. In applying SSS, MEG measurements can be split into two parts: brain signals and external interferences. In this paper, after a brief review of the basics of SSS, we evaluate SSS systematically via computer simulation and real MEG data. In the simulations of this paper, two types of interference sources with magnetic and electric current dipoles are used. The interference suppression effects and the quality of the reconstruction of the interested signal are investigated. Also, the degree of spherical harmonic functions and its relationship with signal reconstruction and interference suppression are studied thoroughly. Finally, we provide objective assessments of the advantages and limitations of the SSS approach, and its practical value in MEG measurements.

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Acknowledgments

The authors would like to thank Samu Taulu of Elekta Neuromag Oy for the helpful suggestions. This work was funded by VA Merit Review Grants awarded to Drs. Huang and Lee.

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Authors and Affiliations

  1. Radiology Department, University of California, San Diego, CA, USA

    Tao Song, Kathleen Gaa, Li Cui, Roland R. Lee & Mingxiong Huang

  2. Radiology Service, San Diego VA Healthcare System, San Diego, USA

    Lori Feffer, Roland R. Lee & Mingxiong Huang

  3. Radiology Imaging Lab, UCSD, 3510 Dunhill Street, San Diego, CA, 92121, USA

    Mingxiong Huang

Authors
  1. Tao Song
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  2. Kathleen Gaa
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  3. Li Cui
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  4. Lori Feffer
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  5. Roland R. Lee
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  6. Mingxiong Huang
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Correspondence to Mingxiong Huang.

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Song, T., Gaa, K., Cui, L. et al. Evaluation of signal space separation via simulation. Med Biol Eng Comput 46, 923–932 (2008). https://doi.org/10.1007/s11517-007-0290-y

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  • DOI: https://doi.org/10.1007/s11517-007-0290-y

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