Advanced EEG Sensing for Real-World Applications
A Special Issue of Sensors (ISSN 1424-8220) belonging to the section "Biomedical Sensors".
Deadline for manuscript submissions: 25 January 2027 | Viewed by 252
Editors
Interests: human augmentation; human mobility interaction; automotive in-car UX; brain machine interface
Special Issues, Collections and Topics in MDPI journals
Interests: medical AI; brain-computer interface; EEG signal processing; neuroengineering; digital healthcare; explainable AI
Special Issue Information
Dear Colleagues,
Recent advances in electroencephalography (EEG) sensing technologies, wearable neural interfaces, and artificial intelligence (AI) have accelerated the development of intelligent brain-monitoring systems for real-world applications. Modern EEG platforms, combined with advanced signal processing and AI-based neural decoding algorithms, enable continuous, noninvasive, and context-aware interpretation of brain activity in naturalistic and clinically relevant environments.
This Special Issue, “Advanced EEG Sensing for Real-World Applications,” aims to highlight recent developments in EEG sensing technologies, computational intelligence, and translational neuroengineering. We welcome original research articles and comprehensive reviews addressing wearable and dry-electrode EEG systems, multimodal biosignal integration, artifact reduction, deep learning, explainable AI, foundation models, and real-time neural decoding methods.
Particular areas of interest include cognitive and mental state monitoring, physiological state estimation (e.g., motion sickness, drowsiness, fatigue, etc.), pain and affective state assessment, neurorehabilitation, human–machine interaction, digital therapeutics, personalized healthcare, and brain–computer interface (BCI) applications in daily life environments.
This Special Issue aligns with the scope of Sensors by focusing on advanced sensing technologies, intelligent biomedical signal analysis, and practical translational applications of EEG-based systems for healthcare and human-centered technologies.
Prof. Dr. Jinung An
Dr. Minji Lee
Dr. Dong-Ok Won
Guest Editors
Manuscript Submission Information
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Keywords
- EEG
- wearable sensors
- artificial intelligence
- neural decoding
- brain–computer interface
- deep learning
- explainable AI
- foundation model
- digital healthcare
- neurotechnology
- human–machine interaction
- physiological state estimation
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