Title :
The Finger Movement Identification Based on Fuzzy Clustering and BP Neural Network
Author :
Yu, Lanlan ; Meng, Tianxing ; Hu, Jian
Author_Institution :
Sch. of Electr. & Electron. Eng., Shandong Univ. of Technol., Zibo, China
Abstract :
The classification and identification technology plays an important role in the research of brain-computer interface (BCI) systems. In this paper, we do fuzzy clustering disposal for the multi-channel electroencephalogram (EEG) during finger movement at first according to event-related desynchronization phenomena (ERD) in the event-related EEG. Then we classify signal-trial EEG with the feature extracted from EEG based on common spatial subspace decomposition (CSSD) algorithm. The averaged classification accuracy achieves 94.58% in the course of testing on the data from four subjects. Experiment results show that the combination of fuzzy clustering and neural network can greatly improve the rate of identification for finger movement.
Keywords :
backpropagation; brain-computer interfaces; electroencephalography; feature extraction; fuzzy set theory; identification technology; medical signal processing; neural nets; pattern classification; pattern clustering; BP neural network; brain-computer interface system; event-related desynchronization phenomena; feature extraction; finger movement identification; fuzzy clustering; identification technology; multichannel electroencephalogram; spatial subspace decomposition algorithm; Brain computer interfaces; Clustering algorithms; Data mining; Electroencephalography; Feature extraction; Fingers; Fuzzy neural networks; Fuzzy set theory; Intelligent networks; Neural networks; BP network; finger movement identification; fuzzy clustering;
Conference_Titel :
Business Intelligence and Financial Engineering, 2009. BIFE '09. International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3705-4
DOI :
10.1109/BIFE.2009.16
