README.md

Abstract

Objective : To classify EEG signals into 7 classes (6 movement classes + rest class) using deep learning models.

Classification Paradigm :

• mov vs mov : Multiclass classification of 6 movement classes vs rest
• mov vs rest : Binary classification of 6 movement classes vs rest

Dataset

• Dataset can be downloaded from http://bnci-horizon-2020.eu/database/data-sets [25].

Dataset description :

Fig 1 : Six movement classes shown

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References

[1] Ofner, P., Schwarz, A., Pereira, J., & Müller-Putz, G. R. (2017). Upper limb movements can be decoded from the time-domain of low-frequency EEG. PloS one, 12(8), e0182578.
[2] van Noord, K., Wang, W., & Jiao, H. (2021, November). Insights of 3d input cnn in eeg-based emotion recognition. In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 212-215). IEEE.

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