基于IRC算法的癫痫脑电相关性分析

Ting Sun, Xin Zou, Chuchu Ding, Jiafei Dai, Jin Li, Jun Wang, F. Hou
{"title":"基于IRC算法的癫痫脑电相关性分析","authors":"Ting Sun, Xin Zou, Chuchu Ding, Jiafei Dai, Jin Li, Jun Wang, F. Hou","doi":"10.1109/ICISCAE.2018.8666912","DOIUrl":null,"url":null,"abstract":"In this paper, the correlation analysis of EEG signals and ECG signals between epileptic and normal population was carried out based on the improved synchronization algorithm IRC based on Kendall. In clinical animal experiments, it was found that when the epilepsy sample attacks, irregular heart rate changes often occur. In this experiment, an improved IRC algorithm was used to analyze the correlation between EEG signals and ECG signals to study whether the correlation between epilepsy patients was different from that of normal people. Experimental results show that using the IRC algorithm based on Kendall improvement can significantly distinguish the correlation between EEG signals and ECG signals in the left forehead and left anterior temporal regions of normal and epileptic populations, and further study on the correlation between brain and heart in epileptic patients.","PeriodicalId":129861,"journal":{"name":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of Epilepsy EEG and ECG Correlation Based on IRC Algorithm\",\"authors\":\"Ting Sun, Xin Zou, Chuchu Ding, Jiafei Dai, Jin Li, Jun Wang, F. Hou\",\"doi\":\"10.1109/ICISCAE.2018.8666912\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the correlation analysis of EEG signals and ECG signals between epileptic and normal population was carried out based on the improved synchronization algorithm IRC based on Kendall. In clinical animal experiments, it was found that when the epilepsy sample attacks, irregular heart rate changes often occur. In this experiment, an improved IRC algorithm was used to analyze the correlation between EEG signals and ECG signals to study whether the correlation between epilepsy patients was different from that of normal people. Experimental results show that using the IRC algorithm based on Kendall improvement can significantly distinguish the correlation between EEG signals and ECG signals in the left forehead and left anterior temporal regions of normal and epileptic populations, and further study on the correlation between brain and heart in epileptic patients.\",\"PeriodicalId\":129861,\"journal\":{\"name\":\"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCAE.2018.8666912\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information Systems and Computer Aided Education (ICISCAE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCAE.2018.8666912","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文基于改进的基于Kendall的同步算法IRC,对癫痫人群与正常人群的脑电信号和心电信号进行相关性分析。在临床动物实验中发现,当癫痫样本发作时,经常出现不规则的心率变化。本实验采用改进的IRC算法分析脑电图信号与心电信号之间的相关性,研究癫痫患者与正常人之间的相关性是否存在差异。实验结果表明,利用基于Kendall改进的IRC算法可以明显区分正常人群和癫痫人群左前额和左颞叶前区脑电信号与心电信号的相关性,进一步研究癫痫患者脑与心的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Epilepsy EEG and ECG Correlation Based on IRC Algorithm
In this paper, the correlation analysis of EEG signals and ECG signals between epileptic and normal population was carried out based on the improved synchronization algorithm IRC based on Kendall. In clinical animal experiments, it was found that when the epilepsy sample attacks, irregular heart rate changes often occur. In this experiment, an improved IRC algorithm was used to analyze the correlation between EEG signals and ECG signals to study whether the correlation between epilepsy patients was different from that of normal people. Experimental results show that using the IRC algorithm based on Kendall improvement can significantly distinguish the correlation between EEG signals and ECG signals in the left forehead and left anterior temporal regions of normal and epileptic populations, and further study on the correlation between brain and heart in epileptic patients.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信