Electroencephalogram (EEG) signals are effective tools towards seizure analysis where one
of the most important challenges is accurate detection of seizure events and brain regions in …

To develop an efficient brain–computer interface (BCI) system, electroencephalography
(EEG) measures neuronal activities in different brain regions through electrodes. Many EEG …

The growth of databases in the healthcare domain opens multiple doors for machine
learning and artificial intelligence technology. Many medical devices are available in the …

Graph theory analysis, as a mathematical tool, has been widely employed in studying the
connectivity of the brain to explore the structural organization. Through the computation of …

In this article, we propose a sparse spectra graph convolutional network (SSGCNet) for
epileptic electroencephalogram (EEG) signal classification. The goal is to develop a …

Epilepsy is one of the most common neurological diseases. Clinically, epileptic seizure
detection is usually performed by analyzing electroencephalography (EEG) signals. At …

The problem of automatic analysis and processing of electroencephalogram (EEG) signals
has been an attractive but a quite difficult research subject with many potential clinical …

Advances in next-generation metagenome sequencing have the potential to revolutionize
the point-of-care diagnosis of novel pathogen infections, which could help prevent potential …

Photoplethysmography (PPG) signals play an important role for automatic measurement of
pulse rate, blood pressure, non-invasive blood glucose level and respiration rate. Most of …

可视图是将时间序列转换成复杂网络的重要方法之一, 也是连接非线性信号分析和复杂网络之间
的全新视角, 在经济金融, 生物医学, 工业工程等领域均应用广泛. 可视图的拓扑结构继承了原始 …