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...

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke through EMG-Driven Robot Hand Training: Insights from Dynamic Causal Modeling

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke through EMG-Driven Robot Hand Training: Insights from Dynamic Causal Modeling

Engineering, Electrical Engineering, Information Science, Automation, Medicine, Basic Medical Sciences, Neurology, Medical Imaging, Life Sciences, Bioengineering,
EMG-driven   robot hand training   stroke rehabilitation   neural networks   dynamic causal modeling   upper limb function recovery  

Revealing the Neuromechanism of Interhemispheric Balance Restoration in Chronic Stroke Patients through EMG-driven Robot Hand Training: Insights from Dynamic Causal Modeling Stroke is a common cause of disability, with most stroke survivors suffering from upper limb paralysis. The consequences of upper limb functional impairment can persist for ove...

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...

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...