Title :
Towards Noninvasive Hybrid Brain–Computer Interfaces: Framework, Practice, Clinical Application, and Beyond
Author :
Muller-Putz, Gernot ; Leeb, Robert ; Tangermann, Michael ; Hohne, Johannes ; Kubler, Andrea ; Cincotti, Febo ; Mattia, Donatella ; Rupp, Rudiger ; Muller, Klaus-Robert ; Del R Millan, Jose
Author_Institution :
Lab. of Brain-Comput. Interfaces, Graz Univ. of Technol., Graz, Austria
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.
Keywords :
assisted living; brain-computer interfaces; electroencephalography; medical disorders; medical signal processing; muscle; prosthetics; BCI system; BCI technology; European commission; artificial output; assistive technologies; control channel; control signals; end users; hBCI framework; locked-in state; multidisciplinary progress; multiple biological signal integration; natural muscle-based output; noninvasive hybrid brain-computer interfaces; physiological signals; practical hybrid BCI; preserved residual functions; real-time interaction; severe motor impairments; technical signals; Assistive technology; Bayes methods; Brain-computer interfaces; Computer interfaces; Electroencephalography; Electromyography; Electronic mail; Neuroprosthesis; Assistive technology; communication; electroencephalogram; hybrid brain–computer interface (hBCI); hybrid brain???computer interface (hBCI); neuroprosthesis;
Journal_Title :
Proceedings of the IEEE
DOI :
10.1109/JPROC.2015.2411333