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

37 citations

5 papers

q-bio.NC2024★ 4 cited

Murine AI excels at cats and cheese: Structural differences between human and mouse neurons and their implementation in generative AIs

Rino Saiga, Kaede Shiga, Yo Maruta +19

Mouse and human brains have different functions that depend on their neuronal networks. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of…

eess.SP2020★ 37 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★ 6 cited

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…

cs.NI2020★ 23 cited

Cascaded WLAN-FWA Networking and Computing Architecture for Pervasive In-Home Healthcare

Sergio Martiradonna, Giulia Cisotto, Gennaro Boggia +3

Pervasive healthcare is a promising assisted-living solution for chronic patients. However, current cutting-edge communication technologies are not able to strictly meet the requir…

eess.IV2020★ 6 cited

Schizophrenia-mimicking layers outperform conventional neural network layers

Ryuta Mizutani, Senta Noguchi, Rino Saiga +4

We have reported nanometer-scale three-dimensional studies of brain networks of schizophrenia cases and found that their neurites are thin and tortuous compared to healthy controls…