Brain-Computer Interface using Directional Auditory Perception

We investigate the potential of brain-computer interface (BCI) using electroencephalogram (EEG) induced by listening (or recalling) auditory stimuli of different directions. In the initial attempt, we apply a time series classification model based on deep learning to the EEG to demonstrate whether each EEG can be classified by recognizing binary (left or right) auditory directions. The results showed high classification accuracy when trained and tested on the same users. Discussion is provided to further explore this topic.