EEG Denoising

3 papers with code • 0 benchmarks • 0 datasets

This task has no description! Would you like to contribute one?

Most implemented papers

EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising

ncclabsustech/EEGdenoiseNet 24 Sep 2020

Here, we present EEGdenoiseNet, a benchmark EEG dataset that is suited for training and testing deep learning-based denoising models, as well as for performance comparisons across models.

Improved robust weighted averaging for event-related potentials in EEG

Kotrix/ImprovedRWA Biocybernetics and Biomedical Engineering 2019

The areas of improvement include significantly lower averaging error (45% lower RMSE and 37% lower maximum difference than for original implementation) and increased robustness to local minima, strong outliers and corrupted epochs common to real-life EEG signals, especially from low-cost devices.

Embedding Decomposition for Artifacts Removal in EEG Signals

ncclabsustech/deepseparator 2 Dec 2021

DeepSeparator employs an encoder to extract and amplify the features in the raw EEG, a module called decomposer to extract the trend, detect and suppress artifact and a decoder to reconstruct the denoised signal.