• 综合
  • 标题
  • 关键词
  • 摘要
  • 学者
  • 期刊-刊名
  • 期刊-ISSN
  • 会议名称
搜索

作者:

Yuan, Ye (Yuan, Ye.) | Xun, Guangxu (Xun, Guangxu.) | Jia, Kebin (Jia, Kebin.) (学者:贾克斌) | Zhang, Aidong (Zhang, Aidong.)

收录:

EI Scopus

摘要:

Epileptic seizure detection has gained increasing attention in clinical therapy. Scalp electroencephalogram (EEG) analysis is a common way to capture brain abnormality for seizure onset detection. This paper presents a novel context-learning based approach using multi-feature fusion to compensate for incomplete description of single feature in epileptic EEG signals. First, EEG scalogram sequence is generated using wavelet transform to represent the time-frequency information. Second, three sets of EEG context features are unsupervisedly learned in parallel by using global principal component analysis (GPCA), stacked denoising autoencoders (SDAEs) and EEG embeddings, respectively. Finally, the multi-features are concatenated into a fixed-length feature vector for seizure classification. The experimental results conducted on two real EEG datasets demonstrate that the proposed cross-patient learning model is able to extract meaningful context features from different perspectives, and hence can detect the onset of epileptic seizure effectively. © 2017 IEEE.

关键词:

Bioinformatics Electroencephalography Learning systems Neurodegenerative diseases Neurophysiology Wavelet transforms

作者机构:

  • [ 1 ] [Yuan, Ye]Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Yuan, Ye]Beijing Laboratory of Advanced Information Networks, Beijing, China
  • [ 3 ] [Yuan, Ye]College of Information and Communication Engineering, Beijing University of Technology, Beijing, China
  • [ 4 ] [Xun, Guangxu]Department of Computer Science and Engineering, State University of New York at Buffalo, NY, United States
  • [ 5 ] [Jia, Kebin]Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China
  • [ 6 ] [Jia, Kebin]Beijing Laboratory of Advanced Information Networks, Beijing, China
  • [ 7 ] [Jia, Kebin]College of Information and Communication Engineering, Beijing University of Technology, Beijing, China
  • [ 8 ] [Zhang, Aidong]Department of Computer Science and Engineering, State University of New York at Buffalo, NY, United States

通讯作者信息:

电子邮件地址:

查看成果更多字段

相关关键词:

相关文章:

来源 :

年份: 2017

卷: 2017-January

页码: 694-699

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 22

ESI高被引论文在榜: 0 展开所有

万方被引频次:

中文被引频次:

近30日浏览量: 2

归属院系:

在线人数/总访问数:104/3602025
地址:北京工业大学图书馆(北京市朝阳区平乐园100号 邮编:100124) 联系我们:010-67392185
版权所有:北京工业大学图书馆 站点建设与维护:北京爱琴海乐之技术有限公司