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• W2057285738 abstract "In this paper, a method for detection of steady-state visual evoked potentials in a non-invasive, multiple channel, asynchronous brain–computer interface is proposed. It is based on the canonical correlation analysis spatial filter for identifying optimal weighted combinations of electrode signals, followed by a cluster analysis of its coefficients for a fast and accurate SSVEP detection. High information transfer rates can be achieved after a short calibration session. The proposed algorithm, a standard spectrum analysis approach, and two competitive spatial filtering and detection methods were evaluated in a series of experiments with the use of data from 21 subjects. The obtained results showed a significant improvement in classification accuracy and in an average detection time for a large group of users." @default.
• W2057285738 created "2016-06-24" @default.
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• W2057285738 date "2014-03-01" @default.
• W2057285738 modified "2023-09-26" @default.
• W2057285738 title "Cluster analysis of CCA coefficients for robust detection of the asynchronous SSVEPs in brain–computer interfaces" @default.
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• W2057285738 doi "https://doi.org/10.1016/j.bspc.2013.11.003" @default.
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