...
首页> 外文期刊>BioMed research international >Validation of New and Existing Decision Rules for the Estimation of Beat-to-Beat Pulse Transit Time
【24h】

Validation of New and Existing Decision Rules for the Estimation of Beat-to-Beat Pulse Transit Time

机译:验证估算节拍脉冲过境时间的新和现有决策规则

获取原文
获取原文并翻译 | 示例

摘要

Pulse transit time (PTT) is a pivotal marker of vascular stiffness. Because the actual PTT duration in vivo is unknown and the complicated variation in waveform may occur, the robust determination of characteristic point is still a very difficult task in the PTT estimation. Our objective is to devise a method for real-time estimation of PTT duration in pulse wave. It has an ability to reduce the interference caused by both high- and low-frequency noise. The reproducibility and performance of these methods are assessed on both artificial and clinical pulse data. Artificial data are generated to investigate the reproducibility with various signal-to-noise ratios. For all artificial data, the mean biases obtained from all methods are less than 1 ms; collectively, this newly proposed method has minimum standard deviation (SD, <1 ms). A set of data from 33 participants together with the synchronously recorded continuous blood pressure data are used to investigate the correlation coefficient (CC). The statistical analysis shows that our method has maximum values of mean CC (0.5231), sum of CCs (17.26), and median CC (0.5695) and has the minimum SD of CCs (0.1943). Overall, the test results in this study indicate that the newly developed method has advantages over traditional decision rules for the PTT measurement.
机译:脉冲传输时间(PTT)是血管刚度的枢轴标记。因为体内实际PTT持续时间未知并且可能发生波形的复杂变化,所以特征点的鲁棒确定在PTT估计中仍然是一个非常困难的任务。我们的目的是设计一种用于脉搏波中PTT持续时间的实时估计的方法。它有能力降低由高频和低频噪声引起的干扰。在人工和临床脉冲数据上评估这些方法的再现性和性能。生成人工数据以研究具有各种信噪比的再现性。对于所有人工数据,从所有方法获得的平均偏差小于1毫秒;统称,这种新的方法具有最小标准偏差(SD,<1 ms)。来自33名参与者的一组数据与同步录制的连续血压数据一起用于研究相关系数(CC)。统计分析表明,我们的方法具有平均Cc(0.5231)的最大值,CCS和17.26)和中值CC(0.5695),具有CCS的最小SD(0.1943)。总体而言,该研究中的测试结果表明,新开发的方法具有对PTT测量的传统决策规则的优势。

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