您的账号已在其他设备登录,您当前账号已强迫下线,
如非您本人操作,建议您在会员中心进行密码修改

确定
收藏 | 浏览6

The electrocardiogram (ECG) is a highly complex, dynamic and stochastic phenomenon. Although it provides a valuable, noninvasive and rapid means of assessing cardiac state and its change, uncertainties in its measurement and variation in the underlying electrophysiology that generates the ECG make difficult further improvement in its reliability for detecting and monitoring cardiac pathologies and conditions. This article reviews the sources of variability and uncertainty in ECG measurement and interpretation, revisits some old ideas for dealing with them, and proposes some novel directions for improving accuracy of ECG assessment and interpretation. We shall explore relative information content of lead systems, representation of ECG signals and patterns, and estimation of ECG distributions from limited lead systems. In addition, we will compare strategies for measuring ECG information and suggest new paradigms for feature extraction that reduce the sensitivity of assessment accuracy to intrinsic and extrinsic measurement errors. Finally, we review the importance of including dynamic information in ECG assessment, both for interpreting current cardiac state as well as for monitoring its change and significance.

作者:R L, Lux

来源:Journal of electrocardiology 2000 年 33 Suppl卷

知识库介绍

临床诊疗知识库该平台旨在解决临床医护人员在学习、工作中对医学信息的需求,方便快速、便捷的获取实用的医学信息,辅助临床决策参考。该库包含疾病、药品、检查、指南规范、病例文献及循证文献等多种丰富权威的临床资源。

详细介绍
热门关注
免责声明:本知识库提供的有关内容等信息仅供学习参考,不代替医生的诊断和医嘱。

收藏
| 浏览:6
作者:
R L, Lux
来源:
Journal of electrocardiology 2000 年 33 Suppl卷
The electrocardiogram (ECG) is a highly complex, dynamic and stochastic phenomenon. Although it provides a valuable, noninvasive and rapid means of assessing cardiac state and its change, uncertainties in its measurement and variation in the underlying electrophysiology that generates the ECG make difficult further improvement in its reliability for detecting and monitoring cardiac pathologies and conditions. This article reviews the sources of variability and uncertainty in ECG measurement and interpretation, revisits some old ideas for dealing with them, and proposes some novel directions for improving accuracy of ECG assessment and interpretation. We shall explore relative information content of lead systems, representation of ECG signals and patterns, and estimation of ECG distributions from limited lead systems. In addition, we will compare strategies for measuring ECG information and suggest new paradigms for feature extraction that reduce the sensitivity of assessment accuracy to intrinsic and extrinsic measurement errors. Finally, we review the importance of including dynamic information in ECG assessment, both for interpreting current cardiac state as well as for monitoring its change and significance.