11 citations · 13 across the 7 of their papers we have counts for
4 papers · 1 filter
Combining Euclidean Alignment and Data Augmentation for BCI decoding
Gustavo H. Rodrigues, Bruno Aristimunha, Sylvain Chevallier +1
Automated classification of electroencephalogram (EEG) signals is complex due to their high dimensionality, non-stationarity, low signal-to-noise ratio, and variability between sub…
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark
Sylvain Chevallier, Igor Carrara, Bruno Aristimunha +6
Objective. This study conduct an extensive Brain-computer interfaces (BCI) reproducibility analysis on open electroencephalography datasets, aiming to assess existing solutions and…
Geometric Neural Network based on Phase Space for BCI-EEG decoding
Igor Carrara, Bruno Aristimunha, Marie-Constance Corsi +3
Objective: The integration of Deep Learning (DL) algorithms on brain signal analysis is still in its nascent stages compared to their success in fields like Computer Vision. This i…
A Systematic Evaluation of Euclidean Alignment with Deep Learning for EEG Decoding
Bruna Junqueira, Bruno Aristimunha, Sylvain Chevallier +1
Electroencephalography (EEG) signals are frequently used for various Brain-Computer Interface (BCI) tasks. While Deep Learning (DL) techniques have shown promising results, they ar…