Multi-task Heterogeneous Ensemble Learning-based Cross-subject EEG Classification in Stroke Patients

Multi-task Heterogeneous Ensemble Learning-based Cross-subject EEG Classification in Stroke Patients

Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology,
stroke   electroencephalography   motor imagery   cross-subject training   multi-task heterogeneous ensemble learning  

Background Introduction Motor Imagery (MI) refers to performing activities through imagination without actual muscle movement. This paradigm is widely used in Brain-Computer Interface (BCI) to decode brain activities into control commands for external devices. Specifically, Electroencephalography (EEG) is widely used in BCI due to its relative affo...

Multi-Feature Attention Convolutional Neural Network for Motor Imagery Decoding

Engineering, Electrical Engineering, Information Science, Automation, Artificial Intelligence, Medicine, Medical Laboratory Science, Neurology, Life Sciences, Bioengineering,
multi-feature attention   convolutional neural networks   motor imagery   brain-computer interface   lightweight model  

Brain-Computer Interface (BCI) is a communication method that connects the nervous system to the external environment. Motor Imagery (MI) is the cornerstone of BCI research, referring to the internal rehearsal before physical execution. Non-invasive techniques such as Electroencephalography (EEG) can record neural activities with high temporal reso...

EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding

EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding

Engineering, Electrical Engineering, Information Science, Artificial Intelligence, Medicine, Neurology,
brain-computer interface   motor imagery   attention collapse   temporal convolution network   transfer learning  

Research Background Brain-Computer Interface (BCI) technology enables direct communication between the brain and external devices. It is widely used in fields such as human-computer interaction, motor rehabilitation, and healthcare. Common BCI paradigms include steady-state visual evoked potentials (SSVEP), P300, and motor imagery (MI). Among these...

Wavelet-Based Temporal-Spectral-Attention Correlation Coefficient for Motor Imagery EEG Classification

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence, Medicine, Basic Medical Sciences, Neurology, Medical Imaging, Life Sciences, Bioengineering,
brain-computer interface   motor imagery   EEG channel attention   temporal-spectral attention   wavelet transform   correlation coefficient  

Brain-Computer Interface (BCI) technology has rapidly developed in recent years and is considered a cutting-edge technology that allows external devices to be controlled directly by the brain without the need for peripheral nerves and muscles. Particularly in the application of Motor Imagery Electroencephalography (MI-EEG), BCI technology has shown...

Motor Cortex Retains and Reorients Neural Dynamics During Motor Imagery

Medicine, Basic Medical Sciences, Neurology, Life Sciences, Biophysics,
motor cortex   motor imagery   neural dynamics   covert motor imagery   neural subspaces  

Academic News Report Background The motor cortex has long been the focus of research on motor control, mainly studying its role in active motor execution. However, even in the absence of actual motor output, the motor cortex also activates during motor imagery. Previous behavioral and imaging studies have confirmed this phenomenon, but how the spec...