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20182021
most citedDeep learning-based classification of fine hand movements from low frequency EEG

37 citations · 63 across the 5 of their papers we have counts for

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eess.SP20201 cited

Comparison of Attention-based Deep Learning Models for EEG Classification

Giulia Cisotto, Alessio Zanga, Joanna Chlebus +3

Objective: To evaluate the impact on Electroencephalography (EEG) classification of different kinds of attention mechanisms in Deep Learning (DL) models. Methods: We compared three…

eess.SP202037 cited

Deep learning-based classification of fine hand movements from low frequency EEG

Giulia Bressan, Selina C. Wriessnegger, Giulia Cisotto

The classification of different fine hand movements from EEG signals represents a relevant research challenge, e.g., in brain-computer interface applications for motor rehabilitati…

eess.SP2020

REPAC: Reliable estimation of phase-amplitude coupling in brain networks

Giulia Cisotto

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…

eess.SP2019

Deep Learning Techniques for Improving Digital Gait Segmentation

Matteo Gadaleta, Giulia Cisotto, Michele Rossi +3

Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously limited to specialist centres a…

eess.SP2019

Performance Requirements of Advanced Healthcare Services over Future Cellular Systems

Giulia Cisotto, Edoardo Casarin, Stefano Tomasin

The fifth generation (5G) of communication systems has ambitious targets of data rate, end-to-end latency, and connection availability, while the deployment of a new flexible netwo…

eess.SP2019

Comparison About EEG Signals Processing in BCI Applications

Giulia Cisotto, Silvano Pupolin, Francesco Piccione

In the context of a Brain Computer Interface platform implemented for the arm rehabilitation of mildly impaired stroke patients, two methods of EEG signals processing are compared…