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<p><b>Special Issue on Advances in EEG Signal Processing and
Machine Learning for Epileptic Seizure Detection and
Prediction</b></p>
<b>Journal of Biomedical Research </b><br>
<u>Submission deadline: </u><u><font color="#3333ff">January
15th, 2019</font></u><b> </b><br>
<p>Epilepsy is the most common neurological disorder of the brain
that affects people worldwide at any age from newborn to adult.
It is characterized by recurrent seizures, which are brief
episodes of signs or symptoms due to abnormal excessive or
synchronous neuronal activity in the brain. The
electroencephalogram, or EEG, is a physiological method to
measure and record the electrical activities generated by the
brain from electrodes placed on the surface of the scalp. EEG
has become the most used signal for detecting and predicting
epileptic seizures. Machine learning for EEG signal processing
constitute an important area of artificial intelligence dealing
with the setting up of automated computer-aided systems allowing
to help the medical staff, e.g. neurophysiologists, for
detecting and predicting epileptic seizure activities from EEG
signals. It offers solutions to difficult biomedical engineering
problems related to detecting and predicting EEG Epileptic
seizures.</p>
In the light of the rapid development of machine learning tools
for signal processing, this special issue aims to solicit original
research papers as well as review articles focusing on recent
advances in EEG signal processing and machine learning for
Epileptic seizure detection and prediction.<br>
Topics of interest should be related to Epileptic seizure
detection and/or prediction, and include (but are not limited to)
the following:<br>
- EEG signal processing<br>
- Time-frequency EEG signal analysis<br>
- Non-stationary EEG signal analysis<br>
- EEG feature extraction and selection<br>
- Machine learning for EEG signals<br>
- EEG classification and clustering<br>
- Deep learning for EEG<br>
- EEG Big Data<br>
- EEG-based BCI (Brain-Computer Interface)<br>
- Internet of things for prediction<br>
- EEG-based computer-aideddiagnosis systems<br>
- Related applications<br>
<br>
<b>Important Dates:</b><br>
Submission deadline: <b><font color="#3333ff">January 15th, 2019</font></b><br>
Completion of first-round reviews: February 15th, 2019<br>
Submission deadline for revised papers: March 15th, 2019<br>
Final acceptance/rejection notification: March30th, 2019<br>
Publication: May 2019<b><br>
</b><br>
<b>Submission Guidelines:</b><br>
- All submissions have to be prepared according to the Guide for
Authors as published in the Journal Web Site: <a
class="moz-txt-link-freetext" href="http://www.jbr-pub.org.cn">http://www.jbr-pub.org.cn</a><br>
- Submissions should be sent through: <a
class="moz-txt-link-freetext"
href="https://mc03.manuscriptcentral.com/jbrint">https://mc03.manuscriptcentral.com/jbrint</a><br>
- Authors should select the acronym "Special Issue: <font
color="#3333ff"><b>AESPMLESDP</b></font>" as the article type,
from the manuscript type menu during the submission process.<br>
<br>
<b>Guest Editor:</b><br>
Dr. Larbi Boubchir, Associate Professor, LIASD research Lab. -
University of Paris 8, France <br>
Email: <a class="moz-txt-link-abbreviated"
href="mailto:larbi.boubchir@ai.univ-paris8.fr">larbi.boubchir@ai.univ-paris8.fr</a><br>
<br>
<blockquote type="cite"
cite="mid:3f21d3d9-7675-c2f8-283b-13bcc6181f5a@ai.univ-paris8.fr">
</blockquote>
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<title></title>
<small><span style="color: rgb(102, 102, 102);">_____________________________________________________</span><br
style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">Larbi Boubchir, PhD,
SMIEEE</span><br style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">Associate Professor</span><br
style="color: rgb(102, 102, 102);">
<br style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">LIASD - University of
Paris 8</span><br style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">2 rue de la Liberté,
93526 Saint-Denis, France</span><br style="color: rgb(102,
102, 102);">
<span style="color: rgb(102, 102, 102);">Tel. (+33) 1 49 40 67
95</span><br style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">Email. <a
class="moz-txt-link-abbreviated"
href="mailto:larbi.boubchir@ai.univ-paris8.fr"
moz-do-not-send="true">larbi.boubchir@ai.univ-paris8.fr</a></span><br
style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);"><a
class="moz-txt-link-freetext"
href="http://www.ai.univ-paris8.fr/~boubchir/"
moz-do-not-send="true">http://www.ai.univ-paris8.fr/~boubchir/</a></span><br
style="color: rgb(102, 102, 102);">
<span style="color: rgb(102, 102, 102);">_____________________________________________________</span></small><br>
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