[Eeglablist] [Deadline Extended] Special Issue on EEG Signal Processing and Machine Learning for Epileptic Seizure Detection and Prediction

Larbi Boubchir boubchir at ai.univ-paris8.fr
Tue Jan 15 03:41:21 PST 2019

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Please disseminate this CFP to your colleagues and contacts.

*Due to a number of extension requests, the deadline is extended to 
February 15th, 2019.*


*Special Issue on Advances in EEG Signal Processing and Machine Learning 
for Epileptic Seizure Detection and Prediction*

*Journal of Biomedical Research *
_Submission deadline: February__15th, 2019_**

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 

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.
Topics of interest should be related to Epileptic seizure detection 
and/or prediction, and include (but are not limited to) the following:
- EEG signal processing
- Time-frequency EEG signal analysis
- Non-stationary EEG signal analysis
- EEG feature extraction and selection
- Machine learning for EEG signals
- EEG classification and clustering
- Deep learning for EEG
- EEG Big Data
- EEG-based BCI (Brain-Computer Interface)
- Internet of things for prediction
- EEG-based computer-aideddiagnosis systems
- Related applications

*Important Dates:*
Submission deadline: *February 15th, 2019*
Completion of first-round reviews: March 15th, 2019
Submission deadline for revised papers: April 15th, 2019
Final acceptance/rejection notification: May 15th, 2019
Publication: May 2019*
*Submission Guidelines:*
- All submissions have to be prepared according to the Guide for Authors 
as published in the Journal Web Site: http://www.jbr-pub.org.cn
- Submissions should be sent through: 
- Authors should select the acronym "Special Issue: *AESPMLESDP*" as the 
article type, from the manuscript type menu during the submission process.

*Guest Editor:*
Dr. Larbi Boubchir, Associate Professor, LIASD research Lab. - 
University of Paris 8, France
Email: larbi.boubchir at ai.univ-paris8.fr

Larbi Boubchir, PhD, SMIEEE
Associate Professor

LIASD - University of Paris 8
2 rue de la Liberté, 93526 Saint-Denis, France
Tel. (+33) 1 49 40 67 95
Email. larbi.boubchir at ai.univ-paris8.fr
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