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Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals
The problem of precisely estimating the position and orientation of multiple dipoles using synthetic EEG signals is considered in this paper. After determining a proper forward model, a nonlinear constrained optimization problem with regularization is solved, and the results are compared with a wide...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006898/ https://www.ncbi.nlm.nih.gov/pubmed/36905060 http://dx.doi.org/10.3390/s23052855 |
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author | Namazifard, Saina Subbarao, Kamesh |
author_facet | Namazifard, Saina Subbarao, Kamesh |
author_sort | Namazifard, Saina |
collection | PubMed |
description | The problem of precisely estimating the position and orientation of multiple dipoles using synthetic EEG signals is considered in this paper. After determining a proper forward model, a nonlinear constrained optimization problem with regularization is solved, and the results are compared with a widely used research code, namely EEGLAB. A thorough sensitivity analysis of the estimation algorithm to the parameters (such as the number of samples and sensors) in the assumed signal measurement model is conducted. To confirm the efficacy of the proposed source identification algorithm on any category of data sets, three different kinds of data-synthetic model data, visually evoked clinical EEG data, and seizure clinical EEG data are used. Furthermore, the algorithm is tested on both the spherical head model and the realistic head model based on the MNI coordinates. The numerical results and comparisons with the EEGLAB show very good agreement, with little pre-processing required for the acquired data. |
format | Online Article Text |
id | pubmed-10006898 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100068982023-03-12 Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals Namazifard, Saina Subbarao, Kamesh Sensors (Basel) Article The problem of precisely estimating the position and orientation of multiple dipoles using synthetic EEG signals is considered in this paper. After determining a proper forward model, a nonlinear constrained optimization problem with regularization is solved, and the results are compared with a widely used research code, namely EEGLAB. A thorough sensitivity analysis of the estimation algorithm to the parameters (such as the number of samples and sensors) in the assumed signal measurement model is conducted. To confirm the efficacy of the proposed source identification algorithm on any category of data sets, three different kinds of data-synthetic model data, visually evoked clinical EEG data, and seizure clinical EEG data are used. Furthermore, the algorithm is tested on both the spherical head model and the realistic head model based on the MNI coordinates. The numerical results and comparisons with the EEGLAB show very good agreement, with little pre-processing required for the acquired data. MDPI 2023-03-06 /pmc/articles/PMC10006898/ /pubmed/36905060 http://dx.doi.org/10.3390/s23052855 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Namazifard, Saina Subbarao, Kamesh Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title | Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title_full | Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title_fullStr | Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title_full_unstemmed | Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title_short | Multiple Dipole Source Position and Orientation Estimation Using Non-Invasive EEG-like Signals |
title_sort | multiple dipole source position and orientation estimation using non-invasive eeg-like signals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10006898/ https://www.ncbi.nlm.nih.gov/pubmed/36905060 http://dx.doi.org/10.3390/s23052855 |
work_keys_str_mv | AT namazifardsaina multipledipolesourcepositionandorientationestimationusingnoninvasiveeeglikesignals AT subbaraokamesh multipledipolesourcepositionandorientationestimationusingnoninvasiveeeglikesignals |