About this Research Topic
This Research Topic aims to present rigorous, significant, and impactful studies that use advanced signal processing and machine learning algorithms to address issues impairing the usability of BCI out of the lab.
Experimental studies as well computational or theoretical works are both welcome. We accept both original articles and review papers. This includes, but is not limited to, algorithms and techniques dealing with noisy and non-stationary brain signals, user’s motion artifacts, long calibration time, variability in properties of brain signals across individuals or tasks, real-time BCI interactions, BCI high mental workload and user fatigue, accelerating learning and improving performance in short-term and long-term, multimodal and hybrid BCIs, new medical and non-medical applications of BCI, new BCI paradigms and new portable BCI devices.
Keywords: Brain-Computer Interface, Signal Processing, Machine Learning, Neurotechnology, Neuroergonomics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.