A5101916594- EEG and Brain-Computer Interfaces
- Brain Tumor Detection and Classification
- ECG Monitoring and Analysis
- Blind Source Separation Techniques
- Functional Brain Connectivity Studies
Shandong University
2023-2025
Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment of epilepsy. Currently, methods using Convolutional Neural Network (CNN) primarily focus on local features EEG, making it challenging to simultaneously capture the spatial temporal from multi-channel EEGs identify preictal state effectively. In order extract inherent relationships among while obtaining their correlations, this study proposed an...
Epilepsy is a chronic neurological disease associated with abnormal neuronal activity in the brain. Seizure detection algorithms are essential reducing workload of medical staff reviewing electroencephalogram (EEG) records. In this work, we propose novel automatic epileptic EEG method based on Stockwell transform and Transformer. First, S-transform applied to original segments, acquiring accurate time-frequency representations. Subsequently, obtained matrices grouped into different rhythm...
International Journal of Neural SystemsAccepted Papers No AccessEfficient Seizure Detection by Complementary Integration Convolutional Network and Vision TransformeJiaqi Wang, Haotian Li, Chuanyu Weisen Lu, Zhouhao Cui, Xiangwen Zhong, Shuhao Ren, Zhida Shang, Weidong ZhouJiaqi Li Search for more papers this author , Lu Cui Zhong Ren Shang Zhou https://doi.org/10.1142/S0129065725500236Cited by:0 (Source: Crossref) PreviousNext AboutFiguresReferencesRelatedDetailsPDF/EPUB ToolsAdd to...
A real-time and reliable automatic detection system for epileptic seizures holds significant value in assisting physicians with rapid diagnosis treatment of epilepsy. Aiming to address this issue, a novel lightweight model called Convolutional Neural Network-Reformer (CNN-Reformer) is proposed seizure on long-term EEG. The CNN-Reformer consists two main parts: the Data Reshaping (DR) module Efficient Attention Concentration (EAC) module. This framework reduces network parameters while...