These algorithms are divided into two principal categories, supervised and unsupervised. While the former achieves higher accuracy, the latter is useful when ...
In unsupervised channel selection, the set of electrodes used are chosen without collecting any additional data. These channels are often chosen based on a ...
[PDF] An Unsupervised Channel-Selection Method for SSVEP ...
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An unsupervised algorithm for steady-state visual evoked potential (SSVEP)-based BCIs is introduced, which works in three steps: it selects multiple sets of ...
In our paper, we introduce an unsupervised algorithm for steady-state visual evoked potential (SSVEP)-based BCIs. Our algorithm works in three steps: (i) it ...
Webster et al. used an unsupervised channel selection method in an SSVEP based BCI with the majority voting of classification outputs obtained from each subset ...
Aug 1, 2023 · In this study, an unsupervised adaptive classification algorithm is designed based on the self-similarity of same-frequency signals.
Aug 1, 2023 · In this study, an unsupervised adaptive classification algorithm is designed based on the self-similarity of same-frequency signals.
User-specific channel selection method to improve SSVEP BCI decoding robustness against variable inter-stimulus distance. In Proceedings of the 2019 Ninth ...
We present a dynamic window-length classifier for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs)
The results suggest that BsCCA significantly improves the performance of SSVEP-based BCI compared to the state-of-the-art methods and can be usable in real ...