… maps are fused, and the deep convolutional neural network (DCNN) is used to classify and
… Multichannel EEG-EMG coupling analysis using a variable scale symbolic transfer entropy …

… classify OR classification OR detect OR detection OR predict OR prediction OR estimate OR
estimation … Fusion of heart rate variability and pulse rate variability for emotion recognition …

现有自动睡眠分期算法存在模型参数量多、 训练耗时长导致分期效率不佳的问题。 本文使用单
通道脑电信号， 提出一种基于迁移学习（ TL） 的随机深度（ SD） 残差网络（ ResNet） 自动睡眠分期…

… interface system for simultaneous detection and classification of fusion EEG signals [ J ]. …
Toward a compact hybrid braincomputer interface (BCI): performance evaluation of multi-class …

… general principles, stimulation paradigms, experimental results, advantages and applications
of the latest hBCI system, we find that using hBCI technology can improve the classification …

… Motion sensorbased assessment of Parkinson's disease motor symptoms during leg agility
tests: Results from levodopa challenge[J]. IEEE Journal of Biomedical and Health Informatics, …

… traditional principal components analysis-Softmax (PCA–Softmax) model. Finally, the
experimental results showed that the learning model had a good classification for the recognition …