首页> 外文期刊>Epilepsy research >Seizure detection using digital trend analysis: Factors affecting utility.
【24h】

Seizure detection using digital trend analysis: Factors affecting utility.

机译:使用数字趋势分析检测癫痫发作:影响效用的因素。

获取原文
获取原文并翻译 | 示例
           

摘要

BACKGROUND: EEG monitoring is important for the early detection of seizures during the course of critical illness. However, the logistics of real time EEG interpretation is challenging for the neurophysiology and critical care medicine teams. This study evaluated factors affecting the utility of digital trend analysis (DTA) for rapid seizure identification in children. METHODS: digital EEG files of seizures in critically ill children were retrieved for DTA. The envelop trend (ET) and compressed spectral array (CSA) were applied to the raw EEG data and presented to an experienced and inexperienced user for interpretation who were blinded to conventional EEG findings. The EEG findings with and without presence of seizures and features of seizures were analyzed. RESULTS: we found that a number of factors affected accurate seizure detection including factors related to interpreter's experiences, display size and type of DTA methods used for analysis in addition to baseline EEG findings. ET was more dependent on user experience, furthermore, display size and multimodal DTA application (CSA and ET combined) increased the sensitivity of seizure detection for the experienced user compared to inexperience users. The artifacts were reported as seizures regardless of experience without presence of conventional EEG recording. The maximum spike amplitude, seizure duration, and seizure frequency were other important determinants for accuracy. Electrographic seizures with shorter duration were better detected by ET, and the maximum spike amplitude was important for both the ET and CSA. Repetitive seizures are readily detected by both digital trending methods. Artifacts may be reported as seizures regardless of experience if conventional EEG recording is not available for the interpretation. CONCLUSION: DTA applied to the raw EEG data does produce a graphic display that facilitates identification of seizures. The actual characteristics of the electrographic seizure may predict which DTA method is better and the overall accuracy of seizure detection may increase when multimodal trending is used simultaneously. Application of DTA alone with display of conventional EEG is beneficial for rapid interpretation of EEG findings regardless of experience.
机译:背景:脑电图监测对于在危重病过程中早期发现癫痫发作很重要。然而,对于神经生理学和重症监护医学团队而言,实时脑电图解释的后勤工作具有挑战性。这项研究评估了影响数字趋势分析(DTA)在儿童快速发作识别中的效用的因素。方法:重症儿童癫痫发作的数字脑电图文件被检索为DTA。包络趋势(ET)和压缩频谱阵列(CSA)应用于原始EEG数据,并提供给经验丰富且经验不足的用户进行解释,而这些用户对常规EEG发现不了解。分析有无癫痫发作和癫痫发作特征的脑电图结果。结果:我们发现许多因素影响准确的癫痫发作检测,其中包括与口译人员的经历,显示大小和用于分析的DTA方法类型有关的因素,以及基线脑电图结果。 ET更加依赖于用户体验,此外,与没有经验的用户相比,显示器的尺寸和多模式DTA应用(CSA和ET的结合)提高了有经验的用户癫痫发作检测的敏感性。在没有常规脑电图记录的情况下,无论经验如何,都将这些伪影报告为癫痫发作。最大尖峰幅度,癫痫发作持续时间和癫痫发作频率是准确性的其他重要决定因素。通过ET可以更好地检测出持续时间较短的电图发作,并且最大尖峰幅度对于ET和CSA都很重要。两种数字趋势方法都容易检测出重复性癫痫发作。如果没有常规的EEG记录可用于解释,则不论经验如何,都可以将伪影报告为癫痫。结论:将DTA应用于原始EEG数据确实会产生图形显示,有助于识别癫痫发作。当同时使用多峰趋势时,电子照相癫痫发作的实际特征可以预测哪种DTA方法更好,并且癫痫发作检测的总体准确性可能会提高。无论经验如何,单独使用DTA并显示常规EEG都有助于快速解释EEG发现。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号