In this section
@article{Xu:2016:10.1109/TNSRE.2016.2523565,
author = {Xu, R and Jiang, N and Dosen, S and Lin, C and Mrachacz-Kersting, N and Dremstrup, K and Farina, D},
doi = {10.1109/TNSRE.2016.2523565},
journal = {IEEE Trans Neural Syst Rehabil Eng},
pages = {901--910},
title = {Endogenous Sensory Discrimination and Selection by a Fast Brain Switch for a High Transfer Rate Brain-Computer Interface.},
url = {http://dx.doi.org/10.1109/TNSRE.2016.2523565},
volume = {24},
year = {2016}
}
TY - JOUR
AB - In this study, we present a novel multi-class brain-computer interface (BCI) for communication and control. In this system, the information processing is shared by the algorithm (computer) and the user (human). Specifically, an electro-tactile cycle was presented to the user, providing the choice (class) by delivering timely sensory input. The user discriminated these choices by his/her endogenous sensory ability and selected the desired choice with an intuitive motor task. This selection was detected by a fast brain switch based on real-time detection of movement-related cortical potentials from scalp EEG. We demonstrated the feasibility of such a system with a four-class BCI, yielding a true positive rate of ∼ 80% and ∼ 70%, and an information transfer rate of ∼ 7 bits/min and ∼ 5 bits/min, for the movement and imagination selection command, respectively. Furthermore, when the system was extended to eight classes, the throughput of the system was improved, demonstrating the capability of accommodating a large number of classes. Combining the endogenous sensory discrimination with the fast brain switch, the proposed system could be an effective, multi-class, gaze-independent BCI system for communication and control applications.
AU - Xu,R
AU - Jiang,N
AU - Dosen,S
AU - Lin,C
AU - Mrachacz-Kersting,N
AU - Dremstrup,K
AU - Farina,D
DO - 10.1109/TNSRE.2016.2523565
EP - 910
PY - 2016///
SP - 901
TI - Endogenous Sensory Discrimination and Selection by a Fast Brain Switch for a High Transfer Rate Brain-Computer Interface.
T2 - IEEE Trans Neural Syst Rehabil Eng
UR - http://dx.doi.org/10.1109/TNSRE.2016.2523565
UR - https://www.ncbi.nlm.nih.gov/pubmed/26849869
VL - 24
ER -