[Eeglablist] CFP: Special Issue on "Advances in Artificial Intelligence and Machine Learning for BCI/BMI"

Larbi Boubchir boubchir at ai.univ-paris8.fr
Fri Jun 12 03:22:59 PDT 2020


*Special Issue on "Advances in Artificial Intelligence and Machine 
Learning for BCI/BMI"*

Journal: Bioengineering (ISSN 2306-5354).
Deadline for manuscript submissions: 31 December 2020.
URL:https://urldefense.com/v3/__https://www.mdpi.com/journal/bioengineering/special_issues/AI_BCI__;!!Mih3wA!RGILxaGOLLq5tw56Sx5bbEOZabheg6lh1SkEAo1So2MhlV0124_rEt66A2Ls1lfszpC9TA$ 
Flyer: 
https://urldefense.com/v3/__https://www.mdpi.com/journal/bioengineering/special_issue_flyer_pdf/AI_BCI/web__;!!Mih3wA!RGILxaGOLLq5tw56Sx5bbEOZabheg6lh1SkEAo1So2MhlV0124_rEt66A2Ls1ldA4jaGbg$ 

Dear colleagues,

The brain–computer interface (BCI), also called the brain–machine 
interface (BMI), is an emerging technology involving software and 
hardware communication systems allowing the use of brain activity to 
control external devices such as computers, robots, and machines. BCI 
systems translate the activity of the brain to conduct an action or a 
command that will be executed by the external device. Artificial 
intelligence (AI)/machine learning (ML) has received great attention for 
the development of BCI applications to solve difficult problems in 
several domains, in particular, medical and robotic fields. AI/ML has 
since become the most efficient tool for BCI systems. This Special Issue 
aims to solicit original research papers as well as review articles 
focusing on recent advances in AI/ML for BCI research.

The main topics include, but are not limited to, the following:

     - Brain–computer interface (BCI)/Brain–machine interface (BMI)
     - Artificial intelligence in BCI/BMI
     - Machine learning in BCI/BMI
     - Deep learning in BCI/BMI
     - Brain signal processing for BCI/BMI
     - Neurofeedback
     - Neural Rehabilitation Engineering
     - Related applications

Assoc. Prof. Dr. Larbi Boubchir
Prof. Dr. Yuling Yan
Guest Editors

*Manuscript Submission Information*

Manuscripts should be submitted online at https://urldefense.com/v3/__http://www.mdpi.com__;!!Mih3wA!RGILxaGOLLq5tw56Sx5bbEOZabheg6lh1SkEAo1So2MhlV0124_rEt66A2Ls1lchBYRl3w$  by registering 
and logging in to this website. Once you are registered, click here to 
go to the submission form. Manuscripts can be submitted until the 
deadline. All papers will be peer-reviewed. Accepted papers will be 
published continuously in the journal (as soon as accepted) and will be 
listed together on the special issue website. Research articles, review 
articles as well as short communications are invited. For planned 
papers, a title and short abstract (about 100 words) can be sent to the 
Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be 
under consideration for publication elsewhere (except conference 
proceedings papers). All manuscripts are thoroughly refereed through a 
single-blind peer-review process. A guide for authors and other relevant 
information for submission of manuscripts is available on the 
Instructions for Authors page. Bioengineering is an international 
peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a 
manuscript. The Article Processing Charge (APC) for publication in this 
open access journal is 1000 CHF (Swiss Francs). Submitted papers should 
be well formatted and use good English. Authors may use MDPI's English 
editing service prior to publication or during author revisions.

*Special Issue Editors:*

Assoc. Prof. Dr. Larbi Boubchir (larbi.boubchir at ai.univ-paris8.fr)
Guest Editor
LIASD research Lab., University of Paris 8, France
Interests: biomedical signal processing; EEG; image processing; machine 
learning; brain–computer interface; biometrics

Prof. Dr. Yuling Yan (yyan1 at scu.edu)
Guest Editor
Department of Bioengineering, Santa Clara University, USA
Interests: biosignal processing; bioimaging; AI-assisted disease 
classification; laryngeal dynamics and physiology; biomedical 
visualization; brain-computer interface




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