Eduardo Mazoni Andrade Marçal Mendes

The paper presents two EEG datasets for speech decoding, focusing on phoneme and word classification and articulatory properties, with conditions involving transcranial magnetic stimulation.

This paper describes a low-cost, open-source headstage system for scalable electrophysiological recordings from multiple brain regions using custom electrode arrays.

This paper explores methods to improve EEG speech decoding by combining transcranial magnetic stimulation with delay differential analysis.

This paper evaluates active probing in a neural mass model to detect early signs of seizures by analyzing feature changes in response to stimuli.

This paper evaluates three adaptive decomposition methods for EEG seizure detection and classification, finding similar high accuracy across methods with one achieving 98.2%.