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Título:
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Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination
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Autor/a:
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Solé-Casals, Jordi; Vialatte, François B.; Chen, Zhe; Cichocki, Andrej
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Otros autores:
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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 |
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Notas:
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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. |
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Materia(s):
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Derechos:
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(c) Springer (The original publication is available at www.springerlink.com)
Tots els drets reservats
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Tipo de documento:
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Objeto de conferencia |
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Editor:
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Springer
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