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Found 4 papers, 1 papers with code
Advancing Brain-Computer Interface System Performance in Hand Trajectory Estimation with NeuroKinect
Our model demonstrates strong correlations between predicted and actual hand movements, with mean Pearson correlation coefficients of 0. 92 ($\pm$0. 015), 0. 93 ($\pm$0. 019), and 0. 83 ($\pm$0. 018) for the X, Y, and Z dimensions.
An F-ratio-Based Method for Estimating the Number of Active Sources in MEG
Overall, when tuned for optimal selection of thresholds, our method offers researchers a precise tool to estimate the true number of active brain sources and accurately model brain function.
Adaptive area-preserving parameterization of open and closed anatomical surfaces
In this work, we propose adaptive area-preserving parameterization methods for simply-connected open and closed surfaces with the target of the parameterization being a spherical cap.
Source Aware Deep Learning Framework for Hand Kinematic Reconstruction using EEG Signal
The ability to reconstruct the kinematic parameters of hand movement using non-invasive electroencephalography (EEG) is essential for strength and endurance augmentation using exosuit/exoskeleton.
