Abstract
Over the past years, steady-state visual evoked potentials (SSVEP) has been widely used in brain-computer interfaces (BCIs) due to its high efficiency, robustness and noninvasive. The supervised SSVEP detector attracted the attention of researchers for its high information transfer rate (ITR). However, the tedious training process restricted its extensive application. This study proposed a low-training cost SSVEP detector with a dynamic window strategy. By this method, the users only need to collect 40-s training data and can achieve a high performance. A 40-target data set was employed to evaluate the performance of the proposed method. The results indicated that the proposed method can achieve 177.5 bits/min ITR, which is 11.2% higher than filter bank canonical correlation analysis with dynamic window (FBCCA-DW).
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