Multimodal fusion of EEG and fMRI for epilepsy detection

Xiashuang Wang; Guanghong Gong; Ni Li

doi:10.1142/S1793962318500101

Multimodal fusion of EEG and fMRI for epilepsy detection

Xiashuang Wang
, Guanghong Gong
, Ni Li

School of Automation Science and Electrical Engineering

Beihang University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

Technology of brain-computer interface (BCI) provides a new way of communication and control without language or physical action. Brain signal tracking and positioning is the basis of BCI research, while brain modeling affects the treatment analysis of (EEG) and functional magnetic resonance imaging (fMRI) directly. This paper proposes human ellipsoid brain modeling method. Then, we use non-parametric spectral estimation method of time-frequency analysis to deal with simulation and real EEG of epilepsy patients, which utilizes both the high spatial and the high time resolution to improve the doctor's diagnostic efficiency.

Original language	English
Article number	1850010
Journal	International Journal of Modeling, Simulation, and Scientific Computing
Volume	9
Issue number	2
DOIs	https://doi.org/10.1142/S1793962318500101
State	Published - 1 Apr 2018

Keywords

Brain model
medical diagnosis
multimodal fusion
time-frequency analysis

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10.1142/S1793962318500101

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title = "Multimodal fusion of EEG and fMRI for epilepsy detection",

abstract = "Technology of brain-computer interface (BCI) provides a new way of communication and control without language or physical action. Brain signal tracking and positioning is the basis of BCI research, while brain modeling affects the treatment analysis of (EEG) and functional magnetic resonance imaging (fMRI) directly. This paper proposes human ellipsoid brain modeling method. Then, we use non-parametric spectral estimation method of time-frequency analysis to deal with simulation and real EEG of epilepsy patients, which utilizes both the high spatial and the high time resolution to improve the doctor's diagnostic efficiency.",

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author = "Xiashuang Wang and Guanghong Gong and Ni Li",

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AU - Wang, Xiashuang

AU - Gong, Guanghong

AU - Li, Ni

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N2 - Technology of brain-computer interface (BCI) provides a new way of communication and control without language or physical action. Brain signal tracking and positioning is the basis of BCI research, while brain modeling affects the treatment analysis of (EEG) and functional magnetic resonance imaging (fMRI) directly. This paper proposes human ellipsoid brain modeling method. Then, we use non-parametric spectral estimation method of time-frequency analysis to deal with simulation and real EEG of epilepsy patients, which utilizes both the high spatial and the high time resolution to improve the doctor's diagnostic efficiency.

AB - Technology of brain-computer interface (BCI) provides a new way of communication and control without language or physical action. Brain signal tracking and positioning is the basis of BCI research, while brain modeling affects the treatment analysis of (EEG) and functional magnetic resonance imaging (fMRI) directly. This paper proposes human ellipsoid brain modeling method. Then, we use non-parametric spectral estimation method of time-frequency analysis to deal with simulation and real EEG of epilepsy patients, which utilizes both the high spatial and the high time resolution to improve the doctor's diagnostic efficiency.

KW - Brain model

KW - medical diagnosis

KW - multimodal fusion

KW - time-frequency analysis

UR - https://www.scopus.com/pages/publications/85029763523

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M3 - 文章

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JO - International Journal of Modeling, Simulation, and Scientific Computing

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IS - 2

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ER -

Multimodal fusion of EEG and fMRI for epilepsy detection

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Keywords

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