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<p><font color="#3333ff"><b>Due to a number of
extension requests, the deadline is
extended to February 15th, 2019.</b></font></p>
<p><b>__________________________</b></p>
<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: <font color="#3333ff">February</font></u><u><font
color="#3333ff"> 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">February
15th, 2019</font></b><br>
Completion of first-round reviews: March 15th,
2019<br>
Submission deadline for revised papers: April
15th, 2019<br>
Final acceptance/rejection notification: May
15th, 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"
moz-do-not-send="true">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"
moz-do-not-send="true">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"
moz-do-not-send="true">larbi.boubchir@ai.univ-paris8.fr</a><br>
<br>
<blockquote type="cite"
cite="mid:3f21d3d9-7675-c2f8-283b-13bcc6181f5a@ai.univ-paris8.fr">
</blockquote>
<div class="moz-signature">-- <br>
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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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