Abstract
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.
| Original language | English |
|---|---|
| Article number | 7109824 |
| Pages (from-to) | 926-943 |
| Number of pages | 18 |
| Journal | Proceedings of the IEEE |
| Volume | 103 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2015 Jun 1 |
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Keywords
- Assistive technology
- communication
- electroencephalogram
- hybrid brain-computer interface (hBCI)
- neuroprosthesis
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Towards noninvasive hybrid brain-computer interfaces : Framework, practice, clinical application, and beyond. / Müller-Putz, Gernot; Leeb, Robert; Tangermann, Michael; Höhne, Johannes; Kübler, Andrea; Cincotti, Febo; Mattia, Donatella; Rupp, Rüdiger; Muller, Klaus; Millán, José Del R.
In: Proceedings of the IEEE, Vol. 103, No. 6, 7109824, 01.06.2015, p. 926-943.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Towards noninvasive hybrid brain-computer interfaces
T2 - Framework, practice, clinical application, and beyond
AU - Müller-Putz, Gernot
AU - Leeb, Robert
AU - Tangermann, Michael
AU - Höhne, Johannes
AU - Kübler, Andrea
AU - Cincotti, Febo
AU - Mattia, Donatella
AU - Rupp, Rüdiger
AU - Muller, Klaus
AU - Millán, José Del R
PY - 2015/6/1
Y1 - 2015/6/1
N2 - 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.
AB - 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.
KW - Assistive technology
KW - communication
KW - electroencephalogram
KW - hybrid brain-computer interface (hBCI)
KW - neuroprosthesis
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U2 - 10.1109/JPROC.2015.2411333
DO - 10.1109/JPROC.2015.2411333
M3 - Article
VL - 103
SP - 926
EP - 943
JO - Proceedings of the IEEE
JF - Proceedings of the IEEE
SN - 0018-9219
IS - 6
M1 - 7109824
ER -