Fusion Methods for Biosignal Analysis: Theory and Applications

Data modalities include electrocardiography (ECG), electroencephalography (EEG), electrocorticography (ECoG), magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET), and diffusion tensor imaging (DTI). Different combinations of DA with other bioinspired methods (...

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Bibliographic Details
Published inComputational Intelligence and Neuroscience Vol. 2017; pp. 1 - 2
Main Authors Salazar, Addisson, Zarzoso, Vicente, Rosa-Zurera, Manuel, Vergara, Luis
Format Journal Article
LanguageEnglish
Published United States Hindawi Limiteds 01.01.2017
Hindawi
John Wiley & Sons, Inc
Hindawi Publishing Corporation
SeriesFusion Methods for Biosignal Analysis: Theory and Applications
Subjects
Algorithms
Bioengineering
Brain research
Computer Science
Electrocardiography
Electroencephalography
Hypothesis testing
Life Sciences
Localization
Machine Learning
Medical imaging
Methods
Neural networks
NMR
Nuclear magnetic resonance
Signal and Image Processing
France
Spain
Online AccessGet full text
ISSN1687-5265
1687-5273
1687-5273
DOI10.1155/2017/7152546

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Summary:Data modalities include electrocardiography (ECG), electroencephalography (EEG), electrocorticography (ECoG), magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET), and diffusion tensor imaging (DTI). Different combinations of DA with other bioinspired methods (bat algorithm, particle swarm optimization, and enhanced fireworks algorithm) and a neural network-based method called extreme learning machine are implemented. [...]Z. Weng et al. design a multimodal fusion method for localization of hub regions in the brain using MRI T1 and DTI.
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ISSN:1687-5265
1687-5273
1687-5273
DOI:10.1155/2017/7152546