Abstract
Brain-computer interface (BCI) is a rapidly evolving technology that has the potential to widely influence research, clinical and recreational use. Non-invasive BCI approaches are particularly common as they can impact a large number of participants safely and at a relatively low cost. Where traditional non-invasive BCIs were used for simple computer cursor tasks, it is now increasingly common for these systems to control robotic devices for complex tasks that may be useful in daily life. In this review, we provide an overview of the general BCI framework as well as the various methods that can be used to record neural activity, extract signals of interest, and decode brain states. In this context, we summarize the current state-of-the-art of non-invasive BCI research, focusing on trends in both the application of BCIs for controlling external devices and algorithm development to optimize their use. We also discuss various open-source BCI toolboxes and software, and describe their impact on the field at large.
Original language | English |
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Pages (from-to) | 1-25 |
Number of pages | 25 |
Journal | IEEE Reviews in Biomedical Engineering |
DOIs | |
Publication status | Accepted/In press - 2024 |
Keywords
- BCI
- Brain-computer interface
- Decoding
- deep learning
- Electrodes
- Electroencephalography
- electroencephalography
- manifold classification
- motor imagery
- motor-related cortical potentials
- Motors
- neural decoding
- neurotechnology
- Recording
- robotic arm
- Robots
- Task analysis
- transfer learning
ASJC Scopus subject areas
- Biomedical Engineering