首页> 美国卫生研究院文献>Epilepsia Open >Ceribell EEG shortens seizure diagnosis and workforce time and is useful for COVID isolation

【2h】

Ceribell EEG shortens seizure diagnosis and workforce time and is useful for COVID isolation

机译：Ceribell EEG缩短了癫痫发作诊断和劳动力时间对Covid隔离有用

代理获取

本网站仅为用户提供外文OA文献查询和代理获取服务，本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文，但由于OA文献来源多样且变更频繁，仍可能出现获取不到、文献不完整或与标题不符等情况，如果获取不到我们将提供退款服务。请知悉。

页面导航

摘要
著录项
相似文献
相关主题

摘要

To determine whether the portable Ceribell® electroencephalograph (EEG) (Mountain View, CA) used for suspected status epilepticus (SE) can reduce time to diagnosis and on‐call workforce demands and whether it can be applied to patients in respiratory isolation.

机译：为了确定用于疑似状态癫痫癫痫的便携式ceribell®猫型脑电图（EEG）（山景，CA）可以减少诊断和随叫随到的劳动力需求的时间，以及是否可以应用于呼吸分离患者。

著录项

期刊名称 Epilepsia Open
作者
Marian P. LaMonte;
展开▼
作者单位

展开▼
年(卷),期 2021(6),2
年度 2021
页码 331–338
总页数 8
原文格式 PDF
正文语种
中图分类精神病学;
关键词

机译：Covid-19;脑电图;状态癫痫术;
入库时间 2022-08-21 12:25:03

相似文献

外文文献
中文文献
专利

1. Ceribell EEG shortens seizure diagnosis and workforce time and is useful for COVID isolation [J] . Marian P. LaMonte Epilepsia Open . 2021,第2期

机译：Ceribell EEG缩短了癫痫发作诊断和劳动力时间，可用于Covid隔离
2. Timely Diagnosis and Treatment Shortens the Time to Resolution of Coronavirus Disease (COVID-19) Pneumonia and Lowers the Highest and Last CT Scores From Sequential Chest CT [J] . AJR: American Journal of Roentgenology : Including Diagnostic Radiology, Radiation Oncology, Nuclear Medicine, Ultrasonography and Related Basic Sciences . 2020,第2期

机译：及时诊断和治疗缩短了冠状病毒疾病（Covid-19）肺炎的时间，并降低了顺序胸部CT的最高和最后CT分数
3. A novel real-time patient-specific seizure diagnosis algorithm based on analysis of EEG and ECG signals using spectral and spatial features and improved particle swarm optimization classifier [J] . NasehiS., PourghassemH. Computers in Biology and Medicine . 2012,第8期

机译：一种基于光谱和空间特征以及改进的粒子群优化分类器的基于EEG和ECG信号分析的新型实时患者特异性癫痫发作诊断算法
4. Classification of seizure and non-seizure activity in seizure patients using time-frequency domain processing of gamma band EEG signals [C] . Tanima Tasmin Chowdhury, Shaikh Anowarul Fattah, Celia Shahnaz International Conference on Advances in Electrical Engineering . 2017

机译：使用伽马带EEG信号的时频域处理对癫痫患者的癫痫发作和非癫痫发作活动进行分类
5. Design of a simulator for neonatal multichannel EEG: Application to time-frequency approaches for automatic artifact removal and seizure detection. [D] . Al-Sa'd, Mohamed Fathi. 2016

机译：新生儿多通道脑电图模拟器的设计：应用于时频方法以自动去除伪影和癫痫发作。
6. Long-Term V-EEG in Epilepsy: Chronological Distribution of Recorded Events Focused on the Differential Diagnosis of Epileptic Seizures and Psychogenic Non-Epileptic Seizures [O] . Fernando Vázquez-Sánchez, Beatriz García-López, Ana Isabel Gómez-Menéndez, 2021

机译：癫痫中的长期V-eeg：记录事件的时间顺序分布重点是癫痫发作和心理非癫痫发作的差异诊断
7. EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed TarekShahriar Abstract—An EMD-chaos based approach is proposed todiscriminate EEG signals corresponding to healthy persons,and epileptic patients during seizure-free intervals and seizureattacks. An electroencephalogram (EEG) is first empiricallydecomposed to intrinsic mode functions (IMFs). The nonlineardynamics of these IMFs are quantified in terms of the largestLyapunov exponent (LLE) and correlation dimension (CD).This chaotic analysis in EMD domain is applied to a large groupof EEG signals corresponding to healthy persons as well asepileptic patients (both with and without seizure attacks). It isshown that the values of the obtained LLE and CD exhibitfeatures by which EEG for seizure attacks can be clearlydistinguished from other EEG signals in the EMD domain.Thus, the proposed approach may aid researchers in developingeffective techniques to predict seizure activities. Index Terms—Electroencephalogram (EEG), empiricalmode decomposition (EMD), largest Lyapunov exponent (LLE),correlation dimension (CD), epileptic seizures. The Authors are with the Electrical and Electronic EngineeringDepartment, Bangladesh University of Engineering and Technology,Dhaka-1000, Bangladesh (e-mail: imamul@eee.buet.ac.bd) PDF Cite: S. M. Shafiul Alam,S. M. Shafiul Alam,Aurangozeb, and Syed Tarek Shahriar, "EEG Signal Discrimination using Non-linear Dynamics in the EMD Domain," International Journal of Computer and Electrical Engineering vol. 4, no. 3, pp. 326-330, 2012. PREVIOUS PAPER Perception of Emotions Using Constructive Learningthrough Speech NEXT PAPER Physical Layer Impairments Aware OVPN Connection Selection Mechanisms Copyright © 2008-2013. International Association of Computer Science and Information Technology Press (IACSIT Press) [O] . S. M. Shafiul Alam, Syed TarekShahriar 2012

机译：EEG信号在EMD域S. S. Shafiul Alam，S中的非线性动力学使用非线性动力学。 M. Shafiul Alam，Aurangozeb和Syed Tarekshahriar摘要 - 基于EMD Chaos的方法，提出了对应于健康人的EEG信号，癫痫发作期间的癫痫患者和Seizureattacks。脑电图（EEG）首先被凭经上分解为内在模式功能（IMF）。这些IMF的非线性动力学在最大范围的指数（LLE）和相关尺寸（CD）方面是量化的。本域中的混沌分析应用于与健康人相对应的大型脑电图（Asepileptic患者）（两者都有癫痫发作）。因此，所获得的LLE和CD表展的价值可以从EMD领域的其他EEG信号中清晰地区分脑电图的表达展示。本拟议的方法可以帮助研究人员以预测癫痫发作的癫痫发作技术。索引术语 - 脑电图（EEG），仿真态分解（EMD），最大的Lyapunov指数（LLE），相关维度（CD），癫痫发作。作者与电气电子和电子工程公司，孟加拉国工程和技术大学，孟加拉国达卡 - 1000（电子邮件：imamul@eee.buet.ac.bd）pdf cite：s. m. shafiul Alam，s。 M. Shafiul Alam，Aurangozeb和Syed Tarek Shahriar，“EEG信号歧视在EMD领域的非线性动态，”计算机电气工程卷国际杂志。 4，不。 3，pp。326-330,2012，上一篇论文对情绪的看法，使用建设性的学习言论下一篇论文物理层障碍意识到OVPN连接选择机制版权所有©2008-2013。国际计算机科学与信息技术协会出版社（IACSIT Press）

Ceribell EEG shortens seizure diagnosis and workforce time and is useful for COVID isolation

摘要

著录项

相似文献

相关主题

期刊订阅