Brain wave classification using long short-term memory network based OPTICAL predictor

S Kumar, A Sharma, T Tsunoda - Scientific reports, 2019 - nature.com
Brain-computer interface (BCI) systems having the ability to classify brain waves with greater
accuracy are highly desirable. To this end, a number of techniques have been proposed …

BCI‐Based Rehabilitation on the Stroke in Sequela Stage

Y Miao, S Chen, X Zhang, J **, R Xu, I Daly… - Neural …, 2020 - Wiley Online Library
Background. Stroke is the leading cause of serious and long‐term disability worldwide.
Survivors may recover some motor functions after rehabilitation therapy. However, many …

Motor imagery EEG classification based on ensemble support vector learning

J Luo, X Gao, X Zhu, B Wang, N Lu, J Wang - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective: Brain-computer interfaces build a communication
pathway from the human brain to a computer. Motor imagery-based electroencephalogram …

Selective multi–view time–frequency decomposed spatial feature matrix for motor imagery EEG classification

T Luo - Expert Systems with Applications, 2024 - Elsevier
Decoding brain activity from non-invasive motor imagery electroencephalograph (MI-EEG)
has garnered significant attentions for brain-computer interface (BCI) and brain disorders …

Multimodal data analysis of epileptic EEG and rs-fMRI via deep learning and edge computing

MP Hosseini, TX Tran, D Pompili, K Elisevich… - Artificial Intelligence in …, 2020 - Elsevier
Background and objective Multimodal data analysis and large-scale computational
capability is entering medicine in an accelerative fashion and has begun to influence …

Global research on artificial intelligence-enhanced human electroencephalogram analysis

X Chen, X Tao, FL Wang, H **e - Neural Computing and Applications, 2022 - Springer
The application of artificial intelligence (AI) technologies in assisting human
electroencephalogram (EEG) analysis has become an active scientific field. This study aims …