首页> 外文会议>2014 IEEE Conference on Biomedical Engineering and Sciences >Toolkit for extracting electrocardiogram signals from scanned trace reports
【24h】

Toolkit for extracting electrocardiogram signals from scanned trace reports

机译:从扫描的跟踪报告中提取心电图信号的工具包

获取原文
获取原文并翻译 | 示例

摘要

Cardiovascular disease (CVD) is the leading cause of death throughout the world. Since electrocardiogram-reports (ECG) have a great CVD predicting potential, the demand for their real-time analysis is high. Although algorithms are present to perform analysis, most countries still use analogue acquisition systems that can only output a printed trace. It is necessary to extract the signal from these printouts to perform analysis. With time, as the reports pile up and the trace fades from the printout, the task becomes increasingly difficult. The method presented specifically focuses on extracting signals from faded traces. Due to the large variability of scans, it is difficult to automate this task completely. In this paper, we propose several tools for ECG extraction while maintaining a minimum user involvement requirement. The proposed method was tested on a dataset of 550 trace snippets and comparative analysis shows an average accuracy of 96%.
机译:心血管疾病(CVD)是全世界的主要死亡原因。由于心电图报告(ECG)具有很大的CVD预测潜力,因此对其实时分析的需求很高。尽管存在执行分析的算法,但大多数国家/地区仍使用只能输出打印轨迹的模拟采集系统。有必要从这些打印输出中提取信号以进行分析。随着时间的流逝,随着报告的堆积和打印输出的痕迹逐渐消失,任务变得越来越困难。提出的方法特别着重于从褪色的迹线中提取信号。由于扫描的差异很大,因此很难完全自动执行此任务。在本文中,我们提出了几种用于ECG提取的工具,同时保持了最低的用户参与要求。该方法在550条迹线摘要的数据集上进行了测试,比较分析显示平均准确性为96%。

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