TY - GEN
T1 - A P300-based brain computer interface for smart home interaction through an ANFIS ensemble
AU - Achanccaray, David
AU - Flores, Christian
AU - Fonseca, Christian
AU - Andreu-Perez, Javier
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/23
Y1 - 2017/8/23
N2 - Adaptive neuro fuzzy Inference systems (ANFIS) has been applied in brain computer interfaces (BcI) in different ways such as mapping of P300 or fusing information from EEG channels and it has reached high classification accuracy. This work proposes a combination of ANFIS classifiers by voting for a single-trial detection of a P300 wave in a BCI, using four channels; five healthy subjects and three post-stroke patients have participated in this study, each participant performs 4 BCI sessions, crossvalidation is applied to evaluate the classifier performance. The results of average accuracy were greater than 75% for all subjects, similar results were gotten for healthy subjects and post-stroke patients, but the better classifiers for each subject have achieved accuracies greater than 80%.
AB - Adaptive neuro fuzzy Inference systems (ANFIS) has been applied in brain computer interfaces (BcI) in different ways such as mapping of P300 or fusing information from EEG channels and it has reached high classification accuracy. This work proposes a combination of ANFIS classifiers by voting for a single-trial detection of a P300 wave in a BCI, using four channels; five healthy subjects and three post-stroke patients have participated in this study, each participant performs 4 BCI sessions, crossvalidation is applied to evaluate the classifier performance. The results of average accuracy were greater than 75% for all subjects, similar results were gotten for healthy subjects and post-stroke patients, but the better classifiers for each subject have achieved accuracies greater than 80%.
KW - ANFIS
KW - Brain computer interface
KW - P300
UR - http://www.scopus.com/inward/record.url?scp=85030164760&partnerID=8YFLogxK
U2 - 10.1109/FUZZ-IEEE.2017.8015770
DO - 10.1109/FUZZ-IEEE.2017.8015770
M3 - Conference contribution
AN - SCOPUS:85030164760
T3 - IEEE International Conference on Fuzzy Systems
BT - 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Fuzzy Systems, FUZZ 2017
Y2 - 9 July 2017 through 12 July 2017
ER -