Embedding Decomposition for Artifacts Removal in EEG Signals

12/02/2021
by   JunJie Yu, et al.
0

Electroencephalogram (EEG) recordings are often contaminated with artifacts. Various methods have been developed to eliminate or weaken the influence of artifacts. However, most of them rely on prior experience for analysis. Here, we propose an deep learning framework to separate neural signal and artifacts in the embedding space and reconstruct the denoised signal, which is called DeepSeparator. 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. Besides, DeepSeparator can extract the artifact, which largely increases the model interpretability. The proposed method is tested with a semi-synthetic EEG dataset and a real task-related EEG dataset, suggesting that DeepSeparator outperforms the conventional models in both EOG and EMG artifact removal. DeepSeparator can be extended to multi-channel EEG and data of any length. It may motivate future developments and application of deep learning-based EEG denoising. The code for DeepSeparator is available at https://github.com/ncclabsustech/DeepSeparator.

READ FULL TEXT

page 6

page 11

research
09/24/2022

Removal of Ocular Artifacts in EEG Using Deep Learning

EEG signals are complex and low-frequency signals. Therefore, they are e...
research
11/22/2020

Deep Learning in EEG: Advance of the Last Ten-Year Critical Period

Deep learning has achieved excellent performance in a wide range of doma...
research
02/18/2021

Edge Sparse Basis Network: An Deep Learning Framework for EEG Source Localization

EEG source localization is an important technical issue in EEG analysis....
research
06/01/2022

Speech Artifact Removal from EEG Recordings of Spoken Word Production with Tensor Decomposition

Research about brain activities involving spoken word production is cons...
research
03/19/2019

Machine Learning for removing EEG artifacts: Setting the benchmark

Electroencephalograms (EEG) are often contaminated by artifacts which ma...

Please sign up or login with your details

Forgot password? Click here to reset