Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces
This article examines the localization errors of equivalent dipolar sources inverted from the surface electroencephalogram in order to determine the feasibility of using their location as classification parameters for non-invasive brain computer interfaces. Inverse localization errors are examined f...
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-09-01
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| Series: | Brain Sciences |
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| Online Access: | https://www.mdpi.com/2076-3425/7/9/118 |
| _version_ | 1818382704822976512 |
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| author | Paul H. Schimpf |
| author_facet | Paul H. Schimpf |
| author_sort | Paul H. Schimpf |
| collection | DOAJ |
| description | This article examines the localization errors of equivalent dipolar sources inverted from the surface electroencephalogram in order to determine the feasibility of using their location as classification parameters for non-invasive brain computer interfaces. Inverse localization errors are examined for two head models: a model represented by four concentric spheres and a realistic model based on medical imagery. It is shown that the spherical model results in localization ambiguity such that a number of dipolar sources, with different azimuths and varying orientations, provide a near match to the electroencephalogram of the best equivalent source. No such ambiguity exists for the elevation of inverted sources, indicating that for spherical head models, only the elevation of inverted sources (and not the azimuth) can be expected to provide meaningful classification parameters for brain–computer interfaces. In a realistic head model, all three parameters of the inverted source location are found to be reliable, providing a more robust set of parameters. In both cases, the residual error hypersurfaces demonstrate local minima, indicating that a search for the best-matching sources should be global. Source localization error vs. signal-to-noise ratio is also demonstrated for both head models. |
| first_indexed | 2024-12-14T02:54:42Z |
| format | Article |
| id | doaj.art-59f4a272935d49f6b102d9b93de04708 |
| institution | Directory Open Access Journal |
| issn | 2076-3425 |
| language | English |
| last_indexed | 2024-12-14T02:54:42Z |
| publishDate | 2017-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Brain Sciences |
| spelling | doaj.art-59f4a272935d49f6b102d9b93de047082022-12-21T23:19:39ZengMDPI AGBrain Sciences2076-34252017-09-017911810.3390/brainsci7090118brainsci7090118Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer InterfacesPaul H. Schimpf0Department of Computer Science, Eastern Washington University, Cheney, WA 99004, USAThis article examines the localization errors of equivalent dipolar sources inverted from the surface electroencephalogram in order to determine the feasibility of using their location as classification parameters for non-invasive brain computer interfaces. Inverse localization errors are examined for two head models: a model represented by four concentric spheres and a realistic model based on medical imagery. It is shown that the spherical model results in localization ambiguity such that a number of dipolar sources, with different azimuths and varying orientations, provide a near match to the electroencephalogram of the best equivalent source. No such ambiguity exists for the elevation of inverted sources, indicating that for spherical head models, only the elevation of inverted sources (and not the azimuth) can be expected to provide meaningful classification parameters for brain–computer interfaces. In a realistic head model, all three parameters of the inverted source location are found to be reliable, providing a more robust set of parameters. In both cases, the residual error hypersurfaces demonstrate local minima, indicating that a search for the best-matching sources should be global. Source localization error vs. signal-to-noise ratio is also demonstrated for both head models.https://www.mdpi.com/2076-3425/7/9/118brain–computer interfaceelectroencephalogramequivalent source model |
| spellingShingle | Paul H. Schimpf Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces Brain Sciences brain–computer interface electroencephalogram equivalent source model |
| title | Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces |
| title_full | Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces |
| title_fullStr | Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces |
| title_full_unstemmed | Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces |
| title_short | Feasibility of Equivalent Dipole Models for Electroencephalogram-Based Brain Computer Interfaces |
| title_sort | feasibility of equivalent dipole models for electroencephalogram based brain computer interfaces |
| topic | brain–computer interface electroencephalogram equivalent source model |
| url | https://www.mdpi.com/2076-3425/7/9/118 |
| work_keys_str_mv | AT paulhschimpf feasibilityofequivalentdipolemodelsforelectroencephalogrambasedbraincomputerinterfaces |