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Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination

Coherency and sharpness measures by using ICA algorithms. An investigation for Alzheimer’s disease discrimination
 
Solé-Casals, Jordi ; Vialatte, François B. ; Chen, Zhe ; Cichocki, Andrej
2009

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Abstract

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 ...»»»»
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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Conference object

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(c) Springer (The original publication is available at www.springerlink.com)
 
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Citation:

Solé Casals, J., Vialatte, F., Chen, Z. & Cichocki, A. 2009, "COHERENCY AND SHARPNESS MEASURES BY USING ICA ALGORITHMS An Investigation for Alzheimer's Disease Discrimination", Biosignals 2009: Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing; 2nd International Conference on Bio-Inspired Systems and Signal Processing, eds. P. Encarnacao & A. Veloso, INSTICC-INST SYST TECHNOLOGIES INFORMATION CONTROL & COMMUNICATION, SETUBAL; AVENIDA D MANUEL L, 27A 2 ESQUERDO, SETUBAL, 2910-595, PORTUGAL, JAN 14-17, 2009, pp. 468.