Abstract
Non-invasive brain-computer interfaces (BCIs) allow users to control external devices by their intentions. Currently, most BCI systems are synchronous, which means, they rely on cues or tasks to which a subject has to react. It would be more useful for users if they could control a device at their own will (i.e., asynchronous BCIs). However, previous asynchronous BCI systems that rely on non-invasive electroencephalogram (EEG) measurements, are not accurate and stable enough for real world applications. 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. In this study, we present a first report on an asynchronous multi-modal hybrid BCI, based on simultaneous EEG and near-infrared spectroscopy (NIRS) measurements and propose novel subject-dependent classification strategies for combining both measurements.
Original language | English |
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DOIs | |
Publication status | Published - 2014 |
Event | 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of Duration: 2014 Feb 17 → 2014 Feb 19 |
Other
Other | 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 |
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Country/Territory | Korea, Republic of |
City | Gangwon |
Period | 14/2/17 → 14/2/19 |
Keywords
- Asynchronous BCI
- Combined EEG-NIRS
- Hybrid Brain-Computer Interface
- Subject-dependent Classification
ASJC Scopus subject areas
- Human-Computer Interaction
- Human Factors and Ergonomics