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.
References
Jan 1, 1987·Physics in Medicine and Biology·J Sarvas
Sep 1, 1995·Electroencephalography and Clinical Neurophysiology·C D TescheO Salonen
Sep 1, 1993·IEEE Transactions on Bio-medical Engineering·A I AhonenV A Vilkman
Mar 1, 1997·Medical & Biological Engineering & Computing·M A Uusitalo, R J Ilmoniemi
Oct 6, 1997·Proceedings of the National Academy of Sciences of the United States of America·S MakeigT J Sejnowski
Feb 25, 2000·Biological Psychiatry·A J RushR Goodman
Jan 26, 2002·Science·S MakeigT J Sejnowski
Jan 28, 2004·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Elina PihkoYoshio Okada
Sep 24, 2004·Brain Topography·Samu TauluJuha Simola
Oct 23, 2004·Experimental Neurology·Marie CheourPatricia Kuhl
Dec 25, 2004·Neuroreport·Minna HuotilainenRisto Näätänen
Mar 23, 2006·Physics in Medicine and Biology·S Taulu, J Simola
Jun 23, 2006·Neuroreport·Toshiaki ImadaPatricia K Kuhl
Sep 7, 2006·Neurosurgery·Jyrki P MäkeläRitva Paetau
Feb 17, 2010·Physics in Medicine and Biology·J NurminenY Okada
Citations
Dec 3, 2009·Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society·Tao SongMingxiong Huang
Jul 5, 2013·PloS One·David HeisterMingxiong Huang
Apr 14, 2016·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Charles W HuangRoland R Lee
Jun 17, 2009·IEEE Transactions on Bio-medical Engineering·Tolga Esat OzkurtRobert J Sclabassi
Feb 24, 2010·IEEE Transactions on Bio-medical Engineering·Chenlei GuoDouglas J Weber
Mar 27, 2015·Journal of Neurotrauma·Ashley Robb SwanMing-Xiong Huang
Sep 12, 2015·Medical & Biological Engineering & Computing·Hui-min ShenXin Fu
Jun 25, 2015·NeuroImage. Clinical·Mithun DiwakarRoland R Lee
Sep 24, 2013·NeuroImage·Ming-Xiong HuangRoland R Lee
May 1, 2012·NeuroImage·Ming-Xiong HuangRoland R Lee
Sep 3, 2014·NeuroImage. Clinical·Ming-Xiong HuangDewleen G Baker
Jul 21, 2010·NeuroImage·Mithun DiwakarRoland R Lee
Mar 30, 2011·NeuroImage·Mithun DiwakarMing-Xiong Huang
Dec 3, 2010·NeuroImage·J HirschmannA Schnitzler
Jul 11, 2014·NeuroImage. Clinical·Ming-Xiong HuangRoland R Lee
Jul 5, 2016·Frontiers in Neuroscience·Michael DatkoJaime A Pineda
Aug 16, 2016·Computational Intelligence and Neuroscience·Niels Trusbak HaumannElvira Brattico
Oct 21, 2016·Journal of Neurotrauma·Ming-Xiong HuangDewleen G Baker
Sep 19, 2014·Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society·Chunyan CaoBomin Sun
Sep 20, 2017·Brain Injury : [BI]·Ming-Xiong HuangRoland R Lee
May 2, 2019·Cerebral Cortex·Ming-Xiong HuangDewleen G Baker
Feb 12, 2019·Restorative Neurology and Neuroscience·Teri Lawton, Ming-Xiong Huang
Apr 19, 2018·Cerebral Cortex·Ming-Xiong HuangDewleen G Baker