The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Towards Noninvasive Hybrid Brain–Computer Interfaces: Framework, Practice, Clinical Application, and Beyond
Open accessAbstract
In their early days, brain-computer interfaces (BCIs) were only considered as control channel for end users with severe motor impairments such as people in the locked-in state. But, thanks to the multidisciplinary progress achieved over the last decade, the range of BCI applications has been substantially enlarged. Indeed, today BCI technology cannot only translate brain signals directly into control signals, but also can combine such kind of artificial output with a natural muscle-based output. Thus, the integration of multiple biological signals for real-time interaction holds the promise to enhance a much larger population than originally thought end users with preserved residual functions who could benefit from new generations of assistive technologies. A BCI system that combines a BCI with other physiological or technical signals is known as hybrid BCI (hBCI). In this work, we review the work of a large scale integrated project funded by the European commission which was dedicated to develop practical hybrid BCIs and introduce them in various fields of applications. This article presents an hBCI framework, which was used in studies with nonimpaired as well as end users with motor impairments.
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Cites
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Cited by
Open Access Dataset for EEG+NIRS Single-Trial Classification
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Metadata
- Authors
- Muller-Putz, G., Leeb, R., Tangermann, M., Hohne, J., Kubler, A., Cincotti, F., Mattia, D., Rupp, R., Muller, K.-R., & Millan, J. D. R.
- Venue
- Proceedings of the IEEE
- Published
- 2015-06
- Volume
- 103
- Issue
- 6
- Pages
- 926-943
- ISSN
- 0018-9219 (ISSN-L)
- 1558-2256
- OpenAlex
- W1674182651
- Cited by
- 158
- References
- 11
- FWCI
- 12.54
- Type
- journal article
- Language
- en
- Open access
- bronze
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