颈动脉内膜切除术后脑电图定量变化与缺血的相关性

V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran
{"title":"颈动脉内膜切除术后脑电图定量变化与缺血的相关性","authors":"V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran","doi":"10.1109/SPMB55497.2022.10014953","DOIUrl":null,"url":null,"abstract":"Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.","PeriodicalId":261445,"journal":{"name":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Quantitative EEG Changes in Carotid Endarterectomy Correlated with Ischemia\",\"authors\":\"V. Pedapati, K. Du, A. Mina, A. Bradley, J. Espino, K. Batmanghelich, P. Thirumala, S. Visweswaran\",\"doi\":\"10.1109/SPMB55497.2022.10014953\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.\",\"PeriodicalId\":261445,\"journal\":{\"name\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPMB55497.2022.10014953\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPMB55497.2022.10014953","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

术中连续监测脑电图(EEG)在颈动脉内膜切除术(CEA)中被常规用于检测脑缺血[1]。视觉观察到的与缺血相关的脑电图变化包括同侧快速频率振幅的下降或同侧慢频率活动的增加。在文献中,显著的脑电图变化被定义为α频段的幅度下降50%或以上,或者θ或δ频段的活动增加50%或以上[2],[3]。与原始脑电相比,定量脑电参数可以增强视觉脑电回顾。QEEG参数通过对原始EEG信号进行傅里叶变换得到功率谱[4]。QEEG参数的例子包括delta、theta、alpha、beta、gamma功率值、alpha功率与delta功率比(ADR)、beta功率与delta功率比(BDR)、alpha- + beta功率与delta- + theta功率比(ABDTR)、频谱边缘频率90% (SEF90)和幅值集成EEG (aEEG)。QEEG参数在相对较少的CEA患者中检测缺血方面已经有研究[5]。在这项研究中,我们报告了大量接受CEA并进行脑电图监测的患者的QEEG参数分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Quantitative EEG Changes in Carotid Endarterectomy Correlated with Ischemia
Continuous intraoperative monitoring with electroencephalography (EEG) is routinely used in carotid endarterectomy (CEA) to detect cerebral ischemia [1]. Visually observed changes in EEG related to ischemia include an ipsilateral decrease in amplitude of faster frequencies or an ipsilateral increase in activity of slower frequencies. In the literature, significant EEG change has been defined as a decrease in the amplitude in the alpha frequency band by 50% or greater or an increase in activity in the theta or delta frequency band by 50% or greater [2], [3]. Compared to raw EEG, quantitative EEG (QEEG) parameters can enhance visual EEG review. QEEG parameters are derived by applying Fourier transformation to raw EEG signals to generate power spectra [4]. Examples of QEEG parameters include delta, theta, alpha, beta, gamma power values, alpha power to delta power ratio (ADR), beta power to delta power ratio (BDR), alpha-plus-beta power to delta-plus-theta power ratio (ABDTR), spectral edge frequency 90% (SEF90) and amplitude-integrated EEG (aEEG). QEEG parameters have been previously investigated in detecting ischemia in a relatively small number of patients undergoing CEA [5]. In this study, we report on the analyses of QEEG parameters in a large population of patients who underwent CEA with EEG monitoring.
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
期刊最新文献
Calibration of Automatic Seizure Detection Algorithms Detecting Human Posterior Lens Surface Topographical Changes During Accommodation Gene Regulatory Network Inference through Link Prediction using Graph Neural Network Analysis of Interpretable Handwriting Features to Evaluate Motoric Patterns in Different Neurodegenerative Diseases An LSTM-based Recurrent Neural Network for Neonatal Sepsis Detection in Preterm Infants
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1