Evaluation of Sensor and Analysis Area in the Signal Source Estimation by Spatial Filter for Magnetocardiography

Iwai, Morio; Seihou, Narita; Kobayashi, Kei; Sun, Wenxu

doi:10.1109/tmag.2021.3083329

Cited by 1 publication

(2 citation statements)

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“…where 𝐇 𝑖 is the lead field matrix related to the 𝑖 𝑡ℎ voxel according to (2), and the optimum 𝐖 𝑖 matrices can be calculated using the following set of equations…”

Section: A Eloretamentioning

confidence: 99%

“…XACT low-resolution electromagnetic tomography (eLORETA) is a brain source localization (BSL) technique that is widely used to localize the source of electrical activity in the brain using electroencephalography (EEG) signals measured from a set of electrodes placed on the scalp [1], [2]. The localized brain source resulting from this so-called EEG inverse problem then can be used for a better diagnosis and treatment of mental or neurological disorders such as epilepsy [3], depression [4], and schizophrenia [5].…”

Section: Introductionmentioning

confidence: 99%

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A Robust eLORETA Technique for Localization of Brain Sources in the Presence of Forward Model Uncertainties

Noroozi

Ravan

Razavi

et al. 2023

IEEE Trans. Biomed. Eng.

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In this paper, we present a robust version of the well-known exact low-resolution electromagnetic tomography (eLORETA) technique, named ReLORETA, to localize brain sources in the presence of different forward model uncertainties. Methods: We first assume that the true lead field matrix is a transformation of the existing lead field matrix distorted by uncertainties and propose an iterative approach to estimate this transformation accurately. Major sources of the forward model uncertainties, including differences in geometry, conductivity, and source space resolution between the real and simulated head models, and misaligned electrode positions, are then simulated to test the proposed method. Results: ReLORETA and eLORETA are applied to simulated focal sources in different regions of the brain and the presence of various noise levels as well as real data from a patient with focal epilepsy. The results show that ReLORETA is considerably more robust and accurate than eLORETA in all cases. Conclusion: Having successfully dealt with the forward model uncertainties, ReLORETA proved to be a promising method for real-world clinical applications.Significance: eLORETA is one of the localization techniques that could be used to study brain activity for medical applications such as determining the epileptogenic zone in patients with medically refractory epilepsy. However, the major limitation of eLORETA is sensitivity to the uncertainties in the forward model. Since this problem can substantially undermine its performance in real-world applications where the exact lead field matrix is unknown, developing a more robust method capable of dealing with these uncertainties is of significant interest.

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“…where 𝐇 𝑖 is the lead field matrix related to the 𝑖 𝑡ℎ voxel according to (2), and the optimum 𝐖 𝑖 matrices can be calculated using the following set of equations…”

Section: A Eloretamentioning

confidence: 99%