Zobrazeno 1 - 10
of 176
pro vyhledávání: '"Cisotto, P."'
With the recent success of artificial intelligence in neuroscience, a number of deep learning (DL) models were proposed for classification, anomaly detection, and pattern recognition tasks in electroencephalography (EEG). EEG is a multi-channel time-
Externí odkaz:
http://arxiv.org/abs/2312.00799
Publikováno v:
Ziefle, M., Lozano, M.D., Mulvenna, M. (eds) Information and Communication Technologies for Ageing Well and e-Health. ICT4AWE 2023. Communications in Computer and Information Science, Springer
Electroencephalografic (EEG) data are complex multi-dimensional time-series that are very useful in many applications, from diagnostics to driving brain-computer interface systems. Their classification is still a challenging task, due to the inherent
Externí odkaz:
http://arxiv.org/abs/2312.09449
Autor:
Giulia Cisotto, Davide Chicco
Publikováno v:
PeerJ Computer Science, Vol 10, p e2256 (2024)
Electroencephalography (EEG) is a medical engineering technique aimed at recording the electric activity of the human brain. Brain signals derived from an EEG device can be processed and analyzed through computers by using digital signal processing,
Externí odkaz:
https://doaj.org/article/8e9c2e4c21354d4fbe589b70c5b35005
Publikováno v:
2021 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)
Motor imagery (MI)-based brain-computer interface (BCI) systems are being increasingly employed to provide alternative means of communication and control for people suffering from neuro-motor impairments, with a special effort to bring these systems
Externí odkaz:
http://arxiv.org/abs/2105.07917
Wireless body area networks (WBANs) are becoming increasingly popular as they allow individuals to continuously monitor their vitals and physiological parameters remotely from the hospital. With the spread of the SARS-CoV-2 pandemic, the availability
Externí odkaz:
http://arxiv.org/abs/2105.07037
Autor:
Cisotto, Giulia, Trentini, Andrea, Zoppis, Italo, Zanga, Alessio, Manzoni, Sara, Pietrabissa, Giada, Usubini, Anna Guerrini, Castelnuovo, Gianluca
As the worldwide population gets increasingly aged, in-home telemedicine and mobile-health solutions represent promising services to promote active and independent aging and to contribute to a paradigm shift towards patient-centric healthcare. In thi
Externí odkaz:
http://arxiv.org/abs/2102.08692
Publikováno v:
Social Sciences, Vol 13, Iss 9, p 489 (2024)
This study explores the motivations, choices, and constraints shaping tourism behavior among transgender individuals living in Italy. Employing a mixed-methods approach, the research begins with quantitative data collection and analyses, followed by
Externí odkaz:
https://doaj.org/article/15e74b52efe24f7e8194ba5cc1abcb2e
Autor:
Ruth Tamara Valencia-Portillo, José Angelo Lindoso, Beatriz Julieta Celeste, Amanda Azevedo Bittencourt, Maria Edileuza Felinto de Brito, Malcolm Scott Duthie, Jeffery Guderian, Jorge Guerra, Ana Lúcia Lyrio Oliveira, Steven Reed, Mussya Cisotto Rocha, Nicolle Tayná Santos, Fernando Tobias Silveira, Hiro Goto, Maria Carmen Arroyo Sanchez
Publikováno v:
PLoS ONE, Vol 19, Iss 6 (2024)
Externí odkaz:
https://doaj.org/article/b9d0328171204e269206f86305ad616f
Autor:
Cisotto, Giulia, Zanga, Alessio, Chlebus, Joanna, Zoppis, Italo, Manzoni, Sara, Markowska-Kaczmar, Urszula
Objective: To evaluate the impact on Electroencephalography (EEG) classification of different kinds of attention mechanisms in Deep Learning (DL) models. Methods: We compared three attention-enhanced DL models, the brand-new InstaGATs, an LSTM with a
Externí odkaz:
http://arxiv.org/abs/2012.01074
Autor:
Cisotto, Giulia
Publikováno v:
2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Recent evidence has revealed cross-frequency coupling and, particularly, phase-amplitude coupling (PAC) as an important strategy for the brain to accomplish a variety of high-level cognitive and sensory functions. However, decoding PAC is still chall
Externí odkaz:
http://arxiv.org/abs/2011.06878