Title :
A Novel Mechanism to Fuse Various Sub-Aspect Brain-Computer Interface (BCI) Systems with PSO for Motor Imagery Task
Author :
Chin-Teng Lin;Tsung-Yu Hsieh;Yu-Ting Liu;Shang-Lin Wu;Yang-Yin Lin
Author_Institution :
Inst. of Electr. Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
In this study, we develop a novel multi-fusion brain-computer interface (BCI) system based on a fuzzy neural network (FNN) and information fusion approaches to cope with a classification task for identifying right/left hand motor imagery. In the proposed system, we utilize a filter bank and sub-band common spatial pattern (SBCSP) to extract features from raw EEG data. A self-organizing neural fuzzy inference network (SONFIN) is then applied for a recognition task. In order to improve the classification performance, we form a committee of networks and employ fuzzy integral (FI) to attain a joint decision. To further optimize the fusion approaches, a particle swarm optimization (PSO) algorithm is exploited to globally update parameters used in the fusion stage. In consequence, our experimental result shows that the proposed fuzzy fusion system possesses superior performance compared to other comparative models.
Keywords :
"Electroencephalography","Feature extraction","Fuzzy neural networks","Classification algorithms","Filter banks","Fuzzy logic","Neural networks"
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
DOI :
10.1109/SMC.2015.559