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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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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