Advancing Signal Processing and Analytics of EEG Signals
A special issue of Signals (ISSN 2624-6120).
Deadline for manuscript submissions: 31 August 2024 | Viewed by 26014
Special Issue Editors
Interests: biomedical signal processing; machine learning; biomedical informatics
Special Issue Information
Dear Colleagues,
As one of the oldest clinical tools for measuring brain physiology, electroencephalography (EEG) has been adopted in a wide spectrum of brain research, such as clinical and psychiatric studies, psychology and neuroscience, brain–computer interface, and so on. Despite significant advancements in EEG research in recent decades, there is still room for improvement on processing approaches and computational methods to improve EEG signal quality and make new discoveries.
This Special Issue of Signals aims to communicate technological and methodological innovations toward knowledge discovery using EEG.
Suitable topics include but are not limited to the following:
- Development of novel biomedical signal processing techniques or approaches to improve EEG signal quality;
- Application of cutting-edge AI, machine learning, or deep learning algorithms to advance EEG-related research;
- Improvements to the performance of EEG-based brain–computer interfaces;
- Biomarker discovery in EEG associated with infant/child brain development;
- Methodological innovation to facilitate endpoint detection or prediction using EEG, e.g., seizure detection and person identification;
- Advances in the understanding of complex brain networks through computational neuroscience using EEG.
Dr. Ran Xiao
Dr. Quanying Liu
Guest Editors
Manuscript Submission Information
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Keywords
- signal processing
- artificial intelligence
- machine learning
- deep learning
- brain–computer interface (BCI)
- developmental EEG
- computational neuroscience
- brain networks
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