DocumentCode :
3575638
Title :
Adaptive strategy for time window length in SSVEP-based brain-computer interface
Author :
Yu Zhang ; Hehe Ma ; Jing Jin ; Xingyu Wang
Author_Institution :
Key Lab. for Adv. Control & Optimization for Chem. Processes, East China Univ. of Sci. & Technol., Shanghai, China
fYear :
2014
Firstpage :
140
Lastpage :
143
Abstract :
Most of the existed methods for steady-state visual evoked potential (SSVEP) recognition require a specified time window length (TWL) to estimate the dominant frequency components in EEG signals. Typically, the TWL is manually predetermined and then fixed during running of the SSVEP-based brain-computer interface (BCI), which may not give the optimal information transfer rate (ITR). This study proposes an adaptive strategy and integrates it into multivariate synchronization index for SSVEP recognition with the automatically determined TWL. The optimal TWL is adaptively selected according to the estimated synchronization index, which provides the relatively higher ITR for the SSVEP recognition than a fixed TWL does. Experimental results evaluated on nine healthy subjects demonstrated effectiveness of the proposed adaptive strategy for the TWL in SSVEP-based BCI.
Keywords :
brain-computer interfaces; electroencephalography; medical signal detection; synchronisation; visual evoked potentials; BCI; EEG signals; ITR; SSVEP recognition; SSVEP-based brain-computer interface; adaptive strategy; information transfer rate; multivariate synchronization index; steady-state visual evoked potential; time window length; Accuracy; Brain-computer interfaces; Correlation; Electroencephalography; Frequency synchronization; Indexes; Synchronization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
Type :
conf
DOI :
10.1109/ICMC.2014.7231535
Filename :
7231535
Link To Document :
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