Exploring inter-trial coherence for inner speech classification in EEG-based brain-computer interface.

This study contributes to
the advancement of EEG-based BCIs for inner speech classification by introducing a feature extraction methodology using ITC.
The obtained results, on par or superior to previous works, highlight the potential significance of this approach in improving the
accuracy of BCI systems. The exploration of this technique lays the groundwork for further research toward inner speech decoding.