Abstract
Non-invasive brain-computer interfaces (BCIs) allow users to control external devices by their intentions. Nevertheless, most current BCI systems rely on cues or tasks to which the subject has to react (i.e., synchronous BCIs). Such systems have limited applications in the real world. It is more desirable for the user to decide himself, when he likes to control a device. However, these so-called asynchronous BCI systems, that rely on electroencephalogram (EEG) measurements show the demand for higher accuracy and stability. Previously, hybrid BCI systems, relying on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements, have been shown to increase the classification performance of (synchronous) motor imagery (MI) tasks. Here we present the first asynchronous hybrid BCI with encouraging results.
Original language | English |
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Pages | 511-515 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2013 |
Event | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 - Naha, Okinawa, Japan Duration: 2013 Nov 5 → 2013 Nov 8 |
Other
Other | 2013 2nd IAPR Asian Conference on Pattern Recognition, ACPR 2013 |
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Country/Territory | Japan |
City | Naha, Okinawa |
Period | 13/11/5 → 13/11/8 |
Keywords
- Asynchronous BCI
- Combined EEG-NIRS
- Hybrid Brain-Computer Interfacing
- Multi-class Classification
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition