Fusion Methods for Biosignal Analysis: Theory and Applications

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 (...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Computational Intelligence and Neuroscience 2017-01, Vol.2017, p.1-2
Hauptverfasser: Salazar, Addisson, Zarzoso, Vicente, Rosa-Zurera, Manuel, Vergara, Luis
Format: Artikel
Sprache:eng
Schlagworte:
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
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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.
ISSN:1687-5265
1687-5273
DOI:10.1155/2017/7152546