Oct 23, 2021 · In this paper, a graph convolutional network (GCN) based on functional connectivity was proposed to decode the motor intention of four fine ...
In this paper, a graph convolutional network (GCN) based on functional connectivity was proposed to decode the motor intention of four fine parts movements ( ...
A graph convolutional network (GCN) based on functional connectivity was proposed to decode the motor intention of four fine parts movements and achieved a ...
Oct 25, 2021 · Decoding brain intention from noninvasively measured neural signals has recently been a hot topic in brain-computer interface (BCI).
Mar 28, 2024 · GCNS-net: a graph convolutional neural network approach for decoding time-resolved EEG motor imagery signals. ... Recognition of single upper limb ...
Missing: Connectivity. | Show results with:Connectivity.
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity. 2021, International Journal of Neural Systems.
Motor Intention Decoding from the Upper Limb by Graph Convolutional Network Based on Functional Connectivity ... network (GCN) based on functional connectivity ...
Significance: This paper discussed four types of MI according to three aspects under two modes and classed them by combining graph Fourier transform and CFC.
[25] utilized an end-to-end deep convolutional neural network to decode the movement intention of hand opening and closing under focused and distracted ...
Significance. This paper discussed four types of MI according to three aspects under two modes and classed them by combining graph Fourier transform and CFC.