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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">February
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: April 30th, 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>
<meta content="text/html; charset=UTF-8"
http-equiv="content-type">
<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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