Motor Imagery EEG Signal Recognition Based on ACVAE and CNN-LSTM

• Published in: 2024 International Conference on Electronic Engineering and Information Systems (EEISS) pp. 197 - 202
• Main Authors: Hu, Cunlin, Ye, Ye, Li, Jian, Wang, Hongliang, Zhou, Tao, Xie, Nenggang
• Format: Conference Proceeding
• Language: English
• Published: IEEE 13.01.2024
• Subjects: Accuracy; Convolutional Neural Network; Data augmentation; EEG recognition; Electroencephalography; Long Short-Term Memory; Motors; Neural networks; Pattern recognition; Training data; Variational Autoencoder

Hybrid neural networks are able to capture the time-dependency of electroencephalography (EEG) signals, and can therefore effectively perform pattern recognition of motor imagery EEG signals. However, a sufficiently large amount of training data is required to achieve optimal results, so it is neces...