ambitious-octopus/MI-EEG-1D-CNN

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and a limited number of EEG channels. Paper: https://doi.org/10.1088/1741-2552/ac4430

PythonGPL-3.0

Issues

Question about the train_test_spliter
#22 opened 2 years ago by zewail-liu
15
Question consultation
#25 opened a year ago by yaolp123
1
Questions about the operation of script train_d.py and train_e.py
#23 opened 2 years ago by HUAjijiji
1
Installing the packages with the environment YML
#20 opened 2 years ago by lopezjuanma96
3
Questions about the SavedModel
#24 opened 2 years ago by 1MrDark
0
A problem with the path to manually download the dataset
#21 opened 2 years ago by HUAjijiji
3
Test #2
#19 opened 2 years ago by ambitious-octopus
0
To-Dos week April 26th
#9 opened 3 years ago by stefano-bargione
0
LSTM single-subject approach
#17 opened 3 years ago by ambitious-octopus
2
Test
#18 opened 2 years ago by ambitious-octopus
4
Original HopefullNet Architecture
#16 opened 2 years ago by ambitious-octopus
0
Theoretical aspects, open discussion
#13 opened 3 years ago by ambitious-octopus
0
2 second window, changelog
#15 opened 3 years ago by ambitious-octopus
13
ICA on Real Movement
#2 opened 3 years ago by ambitious-octopus
0
New strategy for real time classification
#10 opened 3 years ago by ambitious-octopus
0
Prediction Time
#12 opened 2 years ago by ambitious-octopus
0
ICA on Imagery movement
#1 opened 3 years ago by ambitious-octopus
0