Journal Menu► ▼ Journal Menu
Journal Browser► ▼ Journal Browser
Special Issue "Machine Learning for EEG Signal Processing"
A special issue of Computers (ISSN 2073-431X).
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 40585
Special Issue Editor
Interests: biomedical signal processing; EEG; image processing; machine learning; brain–computer interface; biometrics
Special Issues, Collections and Topics in MDPI journals
Special Issue in Electronics: Recent Advances in Biometrics and its Applications
Special Issue in Bioengineering: Bioengineering—Selected Papers from ICBET 2020 (2020 10th International Conference on Biomedical Engineering and Technology)
Special Issue in Applied Sciences: Advanced Machine Learning Algorithms for Biometrics and Its Applications
Special Issue in Bioengineering: IoT Technology in Bioengineering Applications
Special Issue in Electronics: Recent Advanced Signal and Image Processing Technologies in Biomedical Engineering
Special Issue Information
The 1st International Workshop on Machine Learning for EEG Signal Processing (MLESP 2018) will be held in Madrid, Spain, 3–6 December, 2018. The aim of this workshop is to present and discuss the recent advances in machine learning for EEG signal analysis and processing. For more information about the workshop, please use this link:
Selected papers which presented at the workshop are invited to submit their extended versions to this Special Issue of the journal Computers after the conference. Submitted papers should be extended to the size of regular research or review articles, with at least 40% extension of new results. All submitted papers will undergo our standard peer-review procedure. Accepted papers will be published in open access format in Computers and collected together in this Special Issue website. There are no page limitations for this journal.
We are also inviting original research work covering novel theories, innovative methods, and meaningful applications that can potentially lead to significant advances in EEG data analytics.
The main topics include, but are not limited to:
- EEG signal processing and analysis
- Time-frequency EEG signal analysis
- Signal processing for EEG Data
- EEG feature extraction and selection
- Machine learning for EEG signal processing
- EEG classification and clustering
- EEG abnormalities detection (e.g. Epileptic seizure, Alzheimer's disease, etc.)
- Machine learning in EEG Big Data
- Deep Learning for EEG Big Data
- Neural Rehabilitation Engineering
- Brain-Computer Interface
- Biometrics with EEG data
- Related applications
Dr. Larbi Boubchir
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com 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 submissions that pass pre-check are 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. Computers is an international peer-reviewed open access monthly 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 1600 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.
- Electroencephalography (EEG)
- Biomedical signal processing
- Machine learning
- Biomedical engineering