Benchmarks
Greatest papers with code
Decoding P300 Variability using Convolutional Neural Networks
Frontiers in Human Neuroscience 2019
• vlawhern/arl-eegmodels
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Deep convolutional neural networks (CNN) have previously been shown to be useful tools for signal decoding and analysis in a variety of complex domains, such as image processing and speech recognition.
Deep learning with convolutional neural networks for EEG decoding and visualization
PLEASE READ AND CITE THE REVISED VERSION at Human Brain Mapping: http://onlinelibrary. wiley. com/doi/10. 1002/hbm. 23730/full Code available here: https://github. com/robintibor/braindecode
Subject-Aware Contrastive Learning for Biosignals
• zacharycbrown/ssl_baselines_for_biosignal_feature_extraction
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Datasets for biosignals, such as electroencephalogram (EEG) and electrocardiogram (ECG), often have noisy labels and have limited number of subjects (<100).
ANOMALY DETECTION DATA AUGMENTATION EEG EEG DECODING SELF-SUPERVISED LEARNING TIME SERIES
Decoding kinetic features of hand motor preparation from single‐trial EEG using convolutional neural networks
• ragatti/STSnet
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These results show that movement speed and force can be accurately predicted from single‐trial EEG, and that the prediction strategies may provide useful neurophysiological information about motor preparation.
CLASSIFICATION EEG EEG DECODING TIME SERIES TIME SERIES CLASSIFICATION