Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/72343
Title: Computational intelligence in multi-channel EEG signal analysis
Authors: Prochazka, Ales
Mudrova, Martina
Vysata, Oldrich
Grafova, Lucie
Suarez Araujo, Carmen Paz 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Feature-extraction
Ica
Wavelets
Issue Date: 2012
Project: Diseño y Evaluación de Herramientas Computacionales Inteligentes de Ayuda Al Diagnostico y Pronostico Del Deterioro Cognitivo, Enfermedad de Alzheimer y Otras Demencias. Implantación en Telemedicina. 
Journal: Studies in Computational Intelligence 
Conference: 14th IEEE International Conference on Intelligent Engineering Systems 
Abstract: Computational intelligence and signal analysis of multi-channel data form an interdisciplinary research area based upon general digital signal processing methods and adaptive algorithms. The chapter is restricted to their use in biomedicine and particularly in electroencephalogram signal processing to find specific components of such multi-channel signals. Methods presented include signal de-noising, evaluation of their fundamental components and segmentation based upon feature detection in time-frequency and time-scale domains using both the discrete Fourier transform and the discrete wavelet transform. Resulting pattern vectors are then classified by self-organizing neural networks using a specific statistical criterion proposed to evaluate distances of individual feature vector values from corresponding cluster centers. Results achieved are compared for different data sets and selected mathematical methods to detect segments features. Proposed methods verified in the MATLAB environment using distributed data processing are accompanied by the appropriate graphical user interface that enables convenient and user friendly time-series processing.
URI: http://hdl.handle.net/10553/72343
ISBN: 978-3-642-23228-2
ISSN: 1860-949X
DOI: 10.1007/978-3-642-23229-9_17
Source: Recent Advances In Intelligent Engineering Systems [ISSN 1860-949X], v. 378, p. 361-381, (2012)
Appears in Collections:Actas de congresos
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