35 citations · 81 across the 7 of their papers we have counts for
7 papers
A multi-artifact EEG denoising by frequency-based deep learning
Matteo Gabardi, Aurora Saibene, Francesca Gasparini +2
Electroencephalographic (EEG) signals are fundamental to neuroscience research and clinical applications such as brain-computer interfaces and neurological disorder diagnosis. Thes…
An experimental protocol to access immersiveness in video games
Marika Malaspina, Jessica Amianto Barbato, Marco Cremaschi +3
In the video game industry, great importance is given to the experience that the user has while playing a game. In particular, this experience benefits from the players' perceived…
Inner speech recognition through electroencephalographic signals
Francesca Gasparini, Elisa Cazzaniga, Aurora Saibene
This work focuses on inner speech recognition starting from EEG signals. Inner speech recognition is defined as the internalized process in which the person thinks in pure meanings…
The evolution of AI approaches for motor imagery EEG-based BCIs
Aurora Saibene, Silvia Corchs, Mirko Caglioni +1
The Motor Imagery (MI) electroencephalography (EEG) based Brain Computer Interfaces (BCIs) allow the direct communication between humans and machines by exploiting the neural pathw…
Novel EEG-based BCIs for Elderly Rehabilitation Enhancement
Aurora Saibene, Francesca Gasparini, Jordi Solé-Casals
The ageing process may lead to cognitive and physical impairments, which may affect elderly everyday life. In recent years, the use of Brain Computer Interfaces (BCIs) based on Ele…
Benchmark dataset of memes with text transcriptions for automatic detection of multi-modal misogynistic content
Francesca Gasparini, Giulia Rizzi, Aurora Saibene +1
In this paper we present a benchmark dataset generated as part of a project for automatic identification of misogyny within online content, which focuses in particular on memes. Th…
Genetic algorithm for feature selection of EEG heterogeneous data
Aurora Saibene, Francesca Gasparini
The electroencephalographic (EEG) signals provide highly informative data on brain activities and functions. However, their heterogeneity and high dimensionality may represent an o…