🧠 Electroencephalogram (EEG) Data Mining

               -- monitor patients’ real-time attention to track their recovery

" Get to know more about brain signal! "

_{Created by @Shuhui}

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Introduction

• We are trying to monitor patients’ real-time attention to track their recovery
• We design our own experiment paradigm, build data-preprocessing pipeline and train ML model!
• The search program is still in progress... If you have any good suggestion, feel free to contact me!

Environment

• Python == 3.8.0
• Keras == 2.6.0

Usage

To use model, place the contents of this folder in your PYTHONPATH environment variable.

Use models_of_Felix.py to try CNN-Attention-LSTM-ATTENTION model：

from models_of_Felix import ACRNN_4D

ACRNN_object = ACRNN_4D(input_shape, class_num)
model = ACRNN_object.build_model_withAttention()
model.compile(...)

Use test_EEGTCNET.py to try EEGNET-TCNET-FUSION model

How to preprocess EEG data?

You could find more details in preprocessedPipeline.py

How to do feature extraction?

About our experiment paradigm

Interested in our image generation program? Click here