TY - GEN
T1 - Bringing BCI into everyday life
T2 - 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
AU - Brandl, Stephanie
AU - Höhne, Johannes
AU - Muller, Klaus Robert
AU - Samek, Wojciech
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/1
Y1 - 2015/7/1
N2 - Bringing Brain-Computer Interfaces (BCIs) into everyday life is a challenge because an out-of-lab environment implies the presence of variables that are largely beyond control of the user and the software application. This can severely corrupt signal quality as well as reliability of BCI control. Current BCI technology may fail in this application scenario because of the large amounts of noise, nonstationarity and movement artifacts. In this paper, we systematically investigate the performance of motor imagery BCI in a pseudo realistic environment. In our study 16 participants were asked to perform motor imagery tasks while dealing with different types of distractions such as vibratory stimulations or listening tasks. Our experiments demonstrate that standard BCI procedures are not robust to theses additional sources of noise, implicating that methods which work well in a lab environment, may perform poorly in realistic application scenarios. We discuss several promising research directions to tackle this important problem.
AB - Bringing Brain-Computer Interfaces (BCIs) into everyday life is a challenge because an out-of-lab environment implies the presence of variables that are largely beyond control of the user and the software application. This can severely corrupt signal quality as well as reliability of BCI control. Current BCI technology may fail in this application scenario because of the large amounts of noise, nonstationarity and movement artifacts. In this paper, we systematically investigate the performance of motor imagery BCI in a pseudo realistic environment. In our study 16 participants were asked to perform motor imagery tasks while dealing with different types of distractions such as vibratory stimulations or listening tasks. Our experiments demonstrate that standard BCI procedures are not robust to theses additional sources of noise, implicating that methods which work well in a lab environment, may perform poorly in realistic application scenarios. We discuss several promising research directions to tackle this important problem.
UR - http://www.scopus.com/inward/record.url?scp=84940397941&partnerID=8YFLogxK
U2 - 10.1109/NER.2015.7146600
DO - 10.1109/NER.2015.7146600
M3 - Conference contribution
AN - SCOPUS:84940397941
T3 - International IEEE/EMBS Conference on Neural Engineering, NER
SP - 224
EP - 227
BT - 2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PB - IEEE Computer Society
Y2 - 22 April 2015 through 24 April 2015
ER -