...
首页> 外文期刊>Physiological measurement >RS slope detection algorithm for extraction of heart rate from noisy, multimodal recordings
【24h】

RS slope detection algorithm for extraction of heart rate from noisy, multimodal recordings

机译:RS斜率检测算法,可从嘈杂的多模式记录中提取心率

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

Current gold-standard algorithms for heart beat detection do not work properly in the case of high noise levels and do not make use of multichannel data collected by modern patient monitors. The main idea behind the method presented in this paper is to detect the most prominent part of the QRS complex, i.e. the RS slope. We localize the RS slope based on the consistency of its characteristics, i.e. adequate, automatically determined amplitude and duration. It is a very simple and non-standard, yet very effective, solution. Minor data pre-processing and parameter adaptations make our algorithm fast and noise-resistant. As one of a few algorithms in the PhysioNet/Computing in Cardiology Challenge 2014, our algorithm uses more than two channels (i.e. ECG, BP, EEG, EOG and EMG). Simple fundamental working rules make the algorithm universal: it is able to work on all of these channels with no or only little changes. The final result of our algorithm in phase III of the Challenge was 86.38 (88.07 for a 200 record test set), which gave us fourth place. Our algorithm shows that current standards for heart beat detection could be improved significantly by taking a multichannel approach. This is an open-source algorithm available through the PhysioNet library.
机译:在高噪声水平下,当前用于心跳检测的金标准算法无法正常工作,并且无法利用现代患者监护仪收集的多通道数据。本文介绍的方法背后的主要思想是检测QRS复杂度的最突出部分,即RS斜率。我们基于其特性的一致性(即适当的,自动确定的幅度和持续时间)来定位RS斜率。这是一个非常简单,非标准但非常有效的解决方案。较小的数据预处理和参数调整使我们的算法快速且抗噪声。作为PhysioNet / Computing in Cardiology Challenge 2014中的几种算法之一,我们的算法使用了两个以上的渠道(即ECG,BP,EEG,EOG和EMG)。简单的基本工作规则使该算法具有通用性:无需任何更改或只需很少的更改,它就能在所有这些通道上工作。在挑战的第三阶段,我们算法的最终结果是86.38(对于200条记录的测试集为88.07),这使我们排名第四。我们的算法表明,采用多通道方法可以显着改善当前的心跳检测标准。这是可通过PhysioNet库获得的开源算法。

著录项

相似文献

  • 外文文献
  • 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