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Authors: Jordi Solé-Casals 1 ; François Vialatte 2 ; Zhe Chen 3 and Andrzej Cichocki 2

Affiliations: 1 University of Vic, Spain ; 2 RIKEN Brain Science Institute, Japan ; 3 Dept. of Brain and Cognitive Sciences, MIT, United States

ISBN: 978-989-8111-65-4

ISSN: 2184-4305

Keyword(s): EEG, Alzheimer disease, ICA, BSS, Feature extraction.

Related Ontology Subjects/Areas/Topics: Acoustic Signal Processing ; Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Informatics in Control, Automation and Robotics ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing ; Time and Frequency Response ; Time-Frequency Analysis

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 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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Paper citation in several formats:
Solé-Casals J.; Vialatte F.; Chen Z.; Cichocki A. and (2009). COHERENCY AND SHARPNESS MEASURES BY USING ICA ALGORITHMS - An Investigation for Alzheimer's Disease Discrimination.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009) ISBN 978-989-8111-65-4, pages 468-475. DOI: 10.5220/0001430904680475

@conference{biosignals09,
author={Jordi Solé{-}Casals and Fran\c{C}ois Vialatte and Zhe Chen and Andrzej Cichocki},
title={COHERENCY AND SHARPNESS MEASURES BY USING ICA ALGORITHMS - An Investigation for Alzheimer's Disease Discrimination},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)},
year={2009},
pages={468-475},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001430904680475},
isbn={978-989-8111-65-4},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2009)
TI - COHERENCY AND SHARPNESS MEASURES BY USING ICA ALGORITHMS - An Investigation for Alzheimer's Disease Discrimination
SN - 978-989-8111-65-4
AU - Solé-Casals, J.
AU - Vialatte, F.
AU - Chen, Z.
AU - Cichocki, A.
PY - 2009
SP - 468
EP - 475
DO - 10.5220/0001430904680475

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