Identification of epilepsy from intracranial EEG signals by using different neural network models

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 机器人应用与理论组

	Identification of epilepsy from intracranial EEG signals by using different neural network models
	Gong C(龚晨)1,3; Zhang XX(张肖雄)2; Niu YY(牛云云)3
刊名	Computational Biology and Chemistry
	2020
页码	107310
英文摘要	In this work, a framework is provided for identifying intracranialf propagation and feedback neural networks. The performance of 5 different data sets combination classififications is studied using the probabilistic neural network (PNN), learning vector quantization neural network (LVQ) and Elman neural network (ENN). Different feature combinations serve as the input vectors of the classififiers to obtain the best outcomes. It has been found that PNN has less running time and provides better classification accuracy (CA) than ENN and LVQ classifers for all 5 classification problems. It is worth noticing that the CA for the C-D classification task, which shows the status of pre-ictal versus post-ictal, has been greatly improved, and reached 83.13%. Hence, the epilepsy iEEG signals pattern recognition based on DWT statistical features using the PNN classifier is more suitable for forming a reliable, automatic classification system in order to assist doctors in diagnosis.
语种	英语
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/52200]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
作者单位	1.Institute of Automation, Chinese Academy of Sciences 2.School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China 3.School of Information Engineering, China University of Geosciences in Beijing, Beijing 100083, China
推荐引用方式 GB/T 7714	Gong C,Zhang XX,Niu YY. Identification of epilepsy from intracranial EEG signals by using different neural network models[J]. Computational Biology and Chemistry,2020:107310.
APA	Gong C,Zhang XX,&Niu YY.(2020).Identification of epilepsy from intracranial EEG signals by using different neural network models.Computational Biology and Chemistry,107310.
MLA	Gong C,et al."Identification of epilepsy from intracranial EEG signals by using different neural network models".Computational Biology and Chemistry (2020):107310.