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...

AI-based Denoising of Head Impact Kinematics Measurements with Convolutional Neural Network for Traumatic Brain Injury Prediction

Information Science, Artificial Intelligence, Medicine, Neurosurgery, Life Sciences, Bioengineering,
AI   Convolutional Neural Network   Head Impact   Traumatic Brain Injury   Denoising   Kinematics Measurements  

Research and Application of Denoising Head Impact Kinematics Measurement Based on Convolutional Neural Networks Research Background Mild Traumatic Brain Injury (MTBI) is a global health threat. Humans often face the risk of MTBI in situations such as falls, traffic accidents, and sports. According to statistics, there were over 27 million brain inj...

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network for Online Attention Decoding

An Intersubject Brain-Computer Interface Based on Domain-Adversarial Training of Convolutional Neural Network for Online Attention Decoding

Information Science, Artificial Intelligence, Medicine, Neurology, Life Sciences, Bioengineering,
Brain-Computer Interface   Attention Decoding   Domain-Adversarial Training   Convolutional Neural Network   EEG Signals   Online Experiments   Intersubject Variability  

Cross-Subject Brain-Computer Interface: Real-time Attention Decoding Based on Domain-Adversarial Training with Convolutional Neural Networks Academic Background Attention decoding plays a crucial role in our daily lives and its implementation based on electroencephalogram (EEG) has garnered extensive attention. However, due to significant inter-ind...