12 citations · 49 across the 7 of their papers we have counts for
5 papers · 1 filter
Implementation of tools for lessening the influence of artifacts in EEG signal analysis
Mario Molina-Molina, Lorenzo J. Tardon, Ana M. Barbancho +1
This manuscript describes and implementation of scripts of code aimed at reducing the influence of artifacts, specifically focused on ocular artifacts, in the measurement and proce…
Energy-based features and bi-LSTM neural network for EEG-based music and voice classification
Isaac Ariza, Ana M. Barbancho, Lorenzo J. Tardon +1
The human brain receives stimuli in multiple ways; among them, audio constitutes an important source of relevant stimuli for the brain regarding communication, amusement, warning,…
Enhanced average for event-related potential analysis using dynamic time warping
Mario Molina, Lorenzo J. Tardon, Ana M. Barbancho +2
Electroencephalography (EEG) provides a way to understand, and evaluate neurotransmission. In this context, time-locked EEG activity or event-related potentials (ERPs) are often us…
Bi-LSTM neural network for EEG-based error detection in musicians' performance
Isaac Ariza, Lorenzo J. Tardon, Ana M. Barbancho +2
Electroencephalography (EEG) is a tool that allows us to analyze brain activity with high temporal resolution. These measures, combined with deep learning and digital signal proces…
Preprocessing for lessening the influence of eye artifacts in eeg analysis
Alejandro Villena, Lorenzo J. Tardon, Isabel Barbancho +3
We dealt with the problem of artifacts in eeg signals in relation to the usage of lengthy trials. Specifically, we considered eye artifacts found in eeg signals,their influence in…