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• W1794901300 abstract "An asynchronous brain-computer interface (BCI) is one of the crucial challenges in biomedical signal processing. In asynchronous BCIs, a state when a user does not intend to input commands needs to be distinguished from a state when he/she does. These states are called non-control (NC) state and intentional control (IC) state respectively. In this paper, a new phase-based method to discriminate between IC/NC states for steady-state visual evoked potential (SSVEP) based asynchronous BCIs is proposed. The method has a two-step tree structure: in the first step, a SSVEP frequency is recognized with canonical correlation analysis (CCA), and in the next step, the state of a user is detected as IC or NC with a classifier such as SVM using phase information. The proposed method was tested on six healthy subjects and has been proved to be reliable in terms of sensitivity and specificity." @default.
• W1794901300 created "2016-06-24" @default.
• W1794901300 creator A5024355727 @default.
• W1794901300 creator A5059015629 @default.
• W1794901300 date "2015-04-01" @default.
• W1794901300 modified "2023-09-26" @default.
• W1794901300 title "Phase-based detection of intentional state for asynchronous brain-computer interface" @default.
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• W1794901300 doi "https://doi.org/10.1109/icassp.2015.7178081" @default.
• W1794901300 hasPublicationYear "2015" @default.
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