Title :
Eigenbrains: The free vibrational modes of the brain as a new representation for EEG
Author :
Poli, Riccardo ; Citi, Luca ; Salvaris, Mathew ; Cinel, Caterina ; Sepulveda, Francisco
Author_Institution :
Sch. of Comput. Sci. & Electron. Eng., Univ. of Essex, Colchester, UK
fDate :
Aug. 31 2010-Sept. 4 2010
Abstract :
We present a new transform for EEG signals whose basis functions are well suited to represent the large-scale dynamics associated with event related potentials. The method involves instantiating an approximate model of the electrical properties of the brain as a conductor medium and then studying the free vibrational modes of the model. These form a set of basis functions, which we call eigenbrains, that can be used to meaningfully re-represent the brain´s electrical activity. Eigenbrains are compared to principal component analysis and independent component analysis to highlight differences and similarities.
Keywords :
bioelectric potentials; electroencephalography; independent component analysis; medical signal processing; principal component analysis; signal representation; EEG representation; basis functions; brain; eigenbrains; electrical properties; event-related potentials; free vibrational modes; independent component analysis; large-scale dynamics; principal component analysis; Ash; Brain modeling; Electrodes; Electroencephalography; Independent component analysis; Principal component analysis; Adult; Brain; Discriminant Analysis; Electroencephalography; Female; Humans; Male; Models, Biological; Principal Component Analysis; Reproducibility of Results; Statistics, Nonparametric; Vibration; Young Adult;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627593