机构：[1]Beijing Key Laboratory of Trusted Computing Faculty of Information Technology, Beijing University of Technology Beijing 100124, China[2]National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Faculty of Information Technology, Beijing University of Technology Beijing 100124, China[3]Brain-inspired Intelligence and Clinical Translational Research Center/Department of Neurosurgery Xuanwu Hospital Capital Medical University, Beijing 100053, China神经科系统神经外科首都医科大学宣武医院[4]Beijing Key Laboratory of Trusted Computing Faculty of Information Technology, Beijing University of Technology Beijing 100124, China[5]College of Applied Sciences Beijing University of Technology, Beijing 100124, China
Two seizure prediction models are built based on a decision fusion strategy and residual network by using spatial coupling features and introducing an attention mechanism. First, eight frequency bands are filtered, and the correlation matrices are computed for each frequency of eighteen channels. Second, the eight 18x18 matrices are input to the residual module for classification, and the results are concatenated to form a vector. A fully connected layer is used for decision fusion. Third, to emphasize the coupling relationship among the different frequency bands, a cubic matrix formed by the eight 18x18 matrices is inputted to an attention network, resulting in the enhanced features. A seizure prediction model is thus proposed by combining the nine decisions. The performance of the model is compared with those from state-of-the-art methods, and the sensitivity of the proposed model is improved by 4.45%.
基金：
The rearch is partially sponsored by the National Natural
Science Foundation of China (No. 61672070), the Beijing
Municipal Natural Science Foundation (No. 4202025,
4162058), and the Beijing Municipal Education Commission
Project (No.KM201910005008).
语种：
外文
WOS：
第一作者：
第一作者机构：[1]Beijing Key Laboratory of Trusted Computing Faculty of Information Technology, Beijing University of Technology Beijing 100124, China
推荐引用方式(GB/T 7714)：
Lijuan Duan,Ying Xiao,Changming Wang,et al.Prediction of Seizure via Residual Networks Based on Decision Fusion[J].2020 13TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2020).2020,807-813.doi:10.1109/cisp-bmei51763.2020.9263544.
APA：
Lijuan Duan,Ying Xiao,Changming Wang,Yao Wang&Yuanhua Qiao.(2020).Prediction of Seizure via Residual Networks Based on Decision Fusion.2020 13TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2020),,
MLA：
Lijuan Duan,et al."Prediction of Seizure via Residual Networks Based on Decision Fusion".2020 13TH INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, BIOMEDICAL ENGINEERING AND INFORMATICS (CISP-BMEI 2020) .(2020):807-813
