Title :
Regional head tissue conductivity estimation for improved EEG analysis
Author :
Ferree, T.C. ; Eriksen, K.J. ; Tucker, D.M.
Author_Institution :
Electr. Geodesics Inc., Eugene, OR, USA
Abstract :
The authors develop a method for estimating regional head tissue conductivities in vivo, by injecting small (1-10 μA) electric currents into the scalp, and measuring the potentials at the remaining electrodes of a dense-array electroencephalography net. They first derive analytic expressions for the potentials generated by scalp current injection In a four-sphere model of the human head. They then use a multistart downhill simplex algorithm to find regional tissue conductivities which minimize the error between measured and computed scalp potentials. Two error functions are studied, with similar results. The results show that, despite the low skull conductivity and expected shunting by the scalp, all four regional conductivities can be determined to within a few percent error. The method is robust to the noise levels expected in practice. To obtain accurate results the cerebrospinal fluid must be included In the forward solution, but may be treated as a known parameter in the inverse solution.
Keywords :
electrical conductivity measurement; electroencephalography; medical signal processing; 1 to 10 muA; analytic expressions; cerebrospinal fluid; computed scalp potentials; dense-array electroencephalography net; electric currents injection; error functions; forward solution; improved EEG analysis; inverse solution; multistart downhill simplex algorithm; regional head tissue conductivity estimation; regional tissue conductivities; Brain modeling; Conductivity measurement; Current measurement; Electric variables measurement; Electrodes; Electroencephalography; Humans; In vivo; Scalp; Skull; Action Potentials; Algorithms; Artifacts; Bias (Epidemiology); Computer Simulation; Electric Conductivity; Electroencephalography; Head; Humans; Imaging, Three-Dimensional; Numerical Analysis, Computer-Assisted; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on