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Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network
Our findings showed that EEG signals are possible to differentiate when subjects are presented with visual stimulus of different semantic categories and at an exemplar-level with a high classification accuracy; this demonstrates its viability to be applied it in a real-world BMI.
Prediction of Memory Retrieval Performance Using Ear-EEG Signals
These results showed that it is possible to predict performance of a memory task using ear-EEG signals and it could be used for predicting memory retrieval in a practical brain-computer interface.
Neural Oscillations for Encoding and Decoding Declarative Memory using EEG Signals
For decoding phase, only significant decreases of alpha power were observed over fronto-central area.
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