Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace: http://hdl.handle.net/10854/2104

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination
Universitat de Vic. Escola Politècnica Superior; Universitat de Vic. Grup de Recerca en Tecnologies Digitals; International Conference on Bio-inspired Systems and Signal Proceesing (2a: 2009: Porto); BIOSIGNALS 2009
In this paper, we present a comprehensive study of different Independent Component Analysis (ICA) algorithms for the calculation of coherency and sharpness of electroencephalogram (EEG) signals, in order to investigate the possibility of early detection of Alzheimer’s disease (AD). We found that ICA algorithms can help in the artifact rejection and noise reduction, improving the discriminative property of features in high frequency bands (specially in high alpha and beta ranges). In addition to different ICA algorithms, the optimum number of selected components is investigated, in order to help decision processes for future works.
Algorismes
(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
info:eu-repo/semantics/conferenceObject
Springer
         

Documentos con el texto completo de este documento

Ficheros Tamaño Formato Vista
artconlli_a2009 ... di_coherency_sharpness.pdf 198.3 KB application/pdf Vista/Abrir

Mostrar el registro completo del ítem