Concept
brain-computer interface
Variants
Brain-machine Interfaces, Brain-computer Interfaces
Parents
11.5K
Publications
642.4K
Citations
29.1K
Authors
4.9K
Institutions
EEG-based Motor Imagery BCI
1992 - 2003
During this period, Brain-Computer Interface research emphasized EEG-based motor imagery as the central control signal enabling online decoding and real-time communication from imagined movements. Researchers pursued multimodal data fusion, combining EEG/MEG with MRI constraints and surface Laplacians to tackle the inverse problem and enhance spatial localization. Online processing and pattern recognition matured through neural networks, parallel computations, hidden Markov models, and optimized spatial filters for robust single-trial EEG classification.
• Brain-Computer Interface (BCI) research saw a shift toward multimodal data fusion for brain-source localization, combining EEG/MEG with MRI constraints and surface Laplacians to tackle the inverse problem and boost spatial precision [3], [4], [17].
• Brain-Computer Interface (BCI) research increasingly relied on Motor imagery as primary control signals, enabling online classification and real-time communication through imagined movements; papers show left/right/foot and multi-class schemes [18], [15], [20], [19].
• Brain-Computer Interface (BCI) implementations based on event-related potentials (ERPs) and electrocorticography (ECoG) and visually-evoked responses; these ERPs/ECoG patterns form the basis for direct interfaces [6], [7], [11].
• Brain-Computer Interface (BCI) pattern recognition and online processing: neural networks, parallel implementations, hidden Markov models, and spatial filters for single-trial EEG classification and real-time decision making [5], [10], [12], [19].
Open-Platform Noninvasive Brain-Computer Interface
2004 - 2010
Hybrid Multimodal EEG-NIRS BCI
2011 - 2017
End-to-End Deep BCI
2018 - 2024