Kadioglu et al. propose a method for fusing different types of BCI input modalities (i.e., EEG and gaze).
M-Estimation based subspace learning for brain computer interfaces (Kadioglu et al., 2018)
Kadioglu et al. (2018) present a solution for robust PCA (RPCA) of fully observed data with outlying samples based on M-estimation theory.
Language-model assisted and icon-based communication through a BCI with different presentation paradigms (Ahani et al., 2018)
Ahani et al. assess the ERP shape, classification accuracy, and typing performance of different BCI presentation paradigms on 10 healthy participants.
An event-driven AR-process model for EEG-based BCIs with rapid trial sequences (Gonzalez-Navarro et al., 2019)
Gonzalez-Navarro et al. used data from 10 healthy participants to fit and compare two models: the proposed sequence-based EEG model and the trial-based feature-class-conditional distribution model.
Building capacity in AAC (McNaughton et al., 2019)
McNaughton et al. describe strategies to build capacity and awareness in the AAC field to ensure appropriate AAC supports are provided.
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