ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

ADFCNN: Attention-Based Dual-Scale Fusion Convolutional Neural Network for Motor Imagery Brain–Computer Interface

Information Science, Automation, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
Attention   Dual-Scale Fusion   Convolutional Neural Network   Motor Imagery   Brain-Computer Interface   EEG   Self-Attention Mechanism  

Brain-Computer Interface (BCI) has emerged as an enhanced communication and control technology in recent years. In BCI based on electrophysiological characteristics (such as Electroencephalogram, EEG), Motor Imagery (MI) is an important branch that decodes users’ motor intentions for use in clinical rehabilitation, intelligent wheelchair control, c...

An Attention-Based Deep Learning Approach for Sleep Stage Classification with Single-Channel EEG

Engineering, Electrical Engineering, Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology,
Attention   Deep Learning   Sleep Stage   Single-Channel EEG   Feature Extraction   Automatic Classification   Temporal Dependencies  

The IEEE “Transactions on Neural Systems and Rehabilitation Engineering” published a paper titled “Sleep Stage Classification Using Attention-Based Deep Learning for Single-Channel EEG” in Volume 29, 2021. The author of the article include Emadeldeen Edele, Zhenghua Chen, Chengyu Liu, Min Wu, Chee-Keong Kwoh, Xiaoli Li, and Cuntai Guan. The main go...