Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results

This paper presents a new application for analyzing electroencephalogram (EEG) signals. The signals are pre-filtered through MATLAB's EEGLAB tool. The created application performs a convolution between the original EEG signal and a complex Morlet wavelet. As a final result, the application s...

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Main Authors: José Humberto Trueba Perdomo, Ignacio Herrera Aguilar, Francesca Gasparini
Format: Article
Language:English
Published: Universidad de Guadalajara 2019-10-01
Series:ReCIBE
Subjects:
Online Access:http://recibe.cucei.udg.mx/revista/es/vol8-no2/biomedica01.pdf
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spelling doaj-b9b9d53e019445d38b3ed3c9fd2bc1082020-11-25T02:46:18ZengUniversidad de GuadalajaraReCIBE2007-54482007-54482019-10-0182119Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary resultsJosé Humberto Trueba Perdomo0Ignacio Herrera Aguilar1Francesca Gasparini2Electronics Department, Mexico National Institute of Technology/Orizaba Institute of Technology. Oriente 9, 94320 Orizaba, MexicoElectronics Department, Mexico National Institute of Technology/Orizaba Institute of Technology. Oriente 9, 94320 Orizaba, MexicoDepartment of Informatics, Systems, and Communication, University of Milano Bicocca. Viale Sarca 336, 20126 Milano, ItalyThis paper presents a new application for analyzing electroencephalogram (EEG) signals. The signals are pre-filtered through MATLAB's EEGLAB tool. The created application performs a convolution between the original EEG signal and a complex Morlet wavelet. As a final result, the application shows the signal power value and a spectrogram of the convoluted signal. Moreover, the created application compares different EEG channels at the same time, in a fast and straightforward way, through a time and frequency analysis. Finally, the effectiveness of the created application was demonstrated by performing an analysis of the alpha signals of healthy subjects, one signal created by the subject with eyes closed and the other, with which it was compared, was created by the same subject with eyes open. This also served to demonstrate that the power of the alpha band of the closed-eyed signal is higher than the power of the open-eyed signal. http://recibe.cucei.udg.mx/revista/es/vol8-no2/biomedica01.pdf: applicationwaveletelectroencephalogramsignalanalysis
collection DOAJ
language English
format Article
sources DOAJ
author José Humberto Trueba Perdomo
Ignacio Herrera Aguilar
Francesca Gasparini
spellingShingle José Humberto Trueba Perdomo
Ignacio Herrera Aguilar
Francesca Gasparini
Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
ReCIBE
: application
wavelet
electroencephalogram
signal
analysis
author_facet José Humberto Trueba Perdomo
Ignacio Herrera Aguilar
Francesca Gasparini
author_sort José Humberto Trueba Perdomo
title Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
title_short Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
title_full Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
title_fullStr Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
title_full_unstemmed Development of an EEG signal analysis application through a convolution of a complex Morlet wavelet: preliminary results
title_sort development of an eeg signal analysis application through a convolution of a complex morlet wavelet: preliminary results
publisher Universidad de Guadalajara
series ReCIBE
issn 2007-5448
2007-5448
publishDate 2019-10-01
description This paper presents a new application for analyzing electroencephalogram (EEG) signals. The signals are pre-filtered through MATLAB's EEGLAB tool. The created application performs a convolution between the original EEG signal and a complex Morlet wavelet. As a final result, the application shows the signal power value and a spectrogram of the convoluted signal. Moreover, the created application compares different EEG channels at the same time, in a fast and straightforward way, through a time and frequency analysis. Finally, the effectiveness of the created application was demonstrated by performing an analysis of the alpha signals of healthy subjects, one signal created by the subject with eyes closed and the other, with which it was compared, was created by the same subject with eyes open. This also served to demonstrate that the power of the alpha band of the closed-eyed signal is higher than the power of the open-eyed signal.
topic : application
wavelet
electroencephalogram
signal
analysis
url http://recibe.cucei.udg.mx/revista/es/vol8-no2/biomedica01.pdf
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