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Tipologia Anno Titolo Titolo inglese Autore File
Lauree magistrali 2023 THINKING OUT LOUD: UNVEILING BRAIN OSCILLATIONS IN VOWEL AND SEMANTIC DECODING. THINKING OUT LOUD: UNVEILING BRAIN OSCILLATIONS IN VOWEL AND SEMANTIC DECODING. Abstract: This study explores the neural mechanisms underlying imagined speech and its potential for brain-computer interface (BCI) applications, particularly for individuals with severe communication impairments. Using EEG and a novel deep learning model, we aimed to decode linguistic components from imagined speech, focusing on vowels and semantic categories. Our model, which integrates convolutional and recurrent neural network architectures, was validated through the classification of imagined speech, overt speech, and silence, achieving a significant accuracy of 81.76%. High accuracy was also obtained in vowel classification during imagined speech (92.06%) and in semantic categorization (84.88%), surpassing previous studies. We further investigated the role of different EEG frequency bands—Alpha, Beta, Gamma, and High Gamma—in imagined speech decoding. The results indicate that the Beta and Alpha bands are most effective for decoding, offering reliable neural signal representations. By improving the capacity to classify imagined speech and identifying the most effective EEG frequency bands for decoding, these findings lay the groundwork for more refined and accessible BCI applications in the future. VALES CORTINA, IBON
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