Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Namazifard, Saina, Subbarao, Kamesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
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
_version_ 1784905384860844032
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