Title
A novel stimulation for multi-class SSVEP-based brain-computer interface using patterns of time-varying frequencies.
Abstract
Steady-state visual evoked potential (SSVEP) has become one of the most widely employed modalities in online brain computer interface (BCI) because of its high signal-to-noise ratio. However, due to the limitations of brain physiology and the refresh rate of the display devices, the available stimulation frequencies that evoke strong SSVEPs are generally limited for practical applications. In this paper, we introduce a novel stimulation method using patterns of time-varying frequencies that can increase the number of visual stimuli with a fixed number of stimulation frequencies for use in multi-class SSVEP-based BCI systems. We then propose a probabilistic framework and investigate three approaches to detect different patterns of time-varying frequencies. The results confirmed that our proposed stimulation is a promising method for multi-class SSVEP-based BCI tasks. Our pattern detection approaches improved the detection performance significantly by extracting higher quality discriminative information from the input signal.
Year
DOI
Venue
2014
10.1109/EMBC.2014.6943543
EMBC
Keywords
Field
DocType
pattern detection approaches,medical signal detection,steady-state visual evoked potential,multiclass ssvep-based bci systems,display devices,electroencephalography,brain-computer interfaces,time-varying frequencies,high signal-to-noise ratio,medical signal processing,visual evoked potentials,brain physiology,online brain computer interface,brain,multiclass ssvep-based brain-computer interface,visual stimuli,probabilistic framework,probability
Computer vision,Computer science,Brain–computer interface,Speech recognition,Artificial intelligence,Stimulation
Conference
Volume
ISSN
Citations 
2014
1557-170X
1
PageRank 
References 
Authors
0.39
0
6
Name
Order
Citations
PageRank
Omid Dehzangi110.39
Viswam Nathan222.45
Chengzhi Zong310.39
Chang Lee410.72
Insoo Kim5143.34
Roozbeh Jafari698793.51