Name
Abstract | ||
|---|---|---|
Techniques based on electroencephalography (EEG) measure the electric potentials on the scalp and process them to infer the location, distribution, and intensity of underlying neural activity. Accuracy in estimating these parameters is highly sensitive to uncertainty in the conductivities of the head tissues. Furthermore, dissimilarities among individuals are ignored when standardized values are u... |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/TBME.2004.836507 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Conductivity,Electroencephalography,Brain modeling,Electric variables measurement,Electric potential,Scalp,Parameter estimation,Maximum likelihood estimation,Solid modeling,Geometry | Computer science,Neural activity,Artificial intelligence,Unknown Source,Electroencephalography,Computer vision,Neurophysiology,Algorithm,Speech recognition,Maximum a posteriori estimation,Eeg data,Standard deviation,Dipole | Journal |
Volume | Issue | ISSN |
51 | 12 | 0018-9294 |
Citations | PageRank | References |
23 | 1.86 | 7 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Gutiérrez | 1 | 33 | 4.63 |
| Arye Nehorai | 2 | 162 | 24.06 |
| C. Muravchik | 3 | 543 | 68.59 |