Andrés Felipe Soler

Automatic Sleep Stage Classification with Optimized Selection of EEG Channels

This paper presents an ensemble algorithm that automatically classifies sleep stages using an optimized minimal number of EEG channels, achieving high accuracy with only 3 channels.

Automated methodology for optimal selection of the minimum electrode subset for accurate EEG source estimation based on Genetic Algorithm optimization

This paper optimizes EEG electrode selection using a genetic algorithm to maintain high localization accuracy with fewer electrodes.

Low-Density EEG for Neural Activity Reconstruction Using Multivariate Empirical Mode Decomposition

This paper improves neural activity reconstruction from low-density EEG using Multivariate Empirical Mode Decomposition (MEMD) and shows significant error reduction in both real and simulated data.