Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-Temporal Complexity

doi:10.1155/2017/5674392

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中国科学院分子影像重点实验室

	Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-Temporal Complexity
	Zhu, Xinzhong 1,2,3; Xu, Huiying 3; Zhao, Jianmin 3; Tian, Jie2
刊名	COMPLEXITY
	2017
DOI	10.1155/2017/5674392
文献子类	Article
英文摘要	Epilepsy is a group of neurological disorders characterized by epileptic seizures, wherein electroencephalogram (EEG) is one of the most common technologies used to diagnose, monitor, and manage patients with epilepsy. A large number of EEGs have been recorded in clinical applications, which leads to visual inspection of huge volumes of EEG not routinely possible. Hence, automated detection of epileptic seizure has become a goal of many researchers for a long time. A novel method is therefore proposed to construct a patient-specific detector based on spatial-temporal complexity analysis, involving two commonly used entropy-based complexity analysis methods, which are permutation entropy (PE) and sample entropy (SE). The performance of spatial-temporal complexity method is evaluated on a shared dataset. Results suggest that the proposed epilepsy detectors achieve promising performance: the average sensitivities of PE and SE in 23 patients are 99% and 96.6%, respectively. Moreover, both methods can accurately recognize almost all the seizure-free EEG. The proposed method not only obtains a high accuracy rate but also meets the real-time requirements for its application on seizure detection, which suggests that the proposed method has the potential of detecting epileptic seizures in real time.
WOS关键词	PERMUTATION ENTROPY ; SAMPLE ENTROPY ; APPROXIMATE ENTROPY ; ABSENCE SEIZURES ; TIME-SERIES ; BRAIN ; CHAOS
WOS研究方向	Mathematics ; Science & Technology - Other Topics
语种	英语
WOS记录号	WOS:000419499600001
资助机构	Opening Fund of Zhejiang Provincial Top Key Discipline of Computer Science and Technology at Zhejiang Normal University
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/21933]
专题	自动化研究所_中国科学院分子影像重点实验室
作者单位	1.Xidian Univ, Sch Life Sci & Technol, Xian, Shaanxi, Peoples R China 2.Chinese Acad Sci, CAS Key Lab Mol Imaging, Inst Automat, Beijing, Peoples R China 3.Zhejiang Normal Univ, Coll Math Phys & Informat Engn, Jinhua, Zhejiang, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Xinzhong,Xu, Huiying,Zhao, Jianmin,et al. Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-Temporal Complexity[J]. COMPLEXITY,2017.
APA	Zhu, Xinzhong,Xu, Huiying,Zhao, Jianmin,&Tian, Jie.(2017).Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-Temporal Complexity.COMPLEXITY.
MLA	Zhu, Xinzhong,et al."Automated Epileptic Seizure Detection in Scalp EEG Based on Spatial-Temporal Complexity".COMPLEXITY (2017).