首页> 外文会议>Annual International Conference of the IEEE Engineering in Medicine and Biology Society >Neural Respiratory Drive Estimation in Respiratory sEMG with Cardiac Arrhythmias
【24h】

Neural Respiratory Drive Estimation in Respiratory sEMG with Cardiac Arrhythmias

机译:呼吸性sEMG伴心律失常的神经呼吸驱动估计

获取原文

摘要

Neural respiratory drive as measured by the electromyography allows the study of the imbalance between the load on respiratory muscles and its capacity. Surface respiratory electromyography (sEMG) is a non-invasive tool used for indirectly assessment of NRD. It also provides a way to evaluate the level and pattern of respiratory muscle activation. The prevalence of electrocardiographic activity (ECG) in respiratory sEMG signals hinders its proper evaluation. Moreover, the occurrence of abnormal heartbeats or cardiac arrhythmias in respiratory sEMG measures can make even more challenging the NRD estimation. Respiratory sEMG can be evaluated using the fixed sample entropy (fSampEn), a technique which is less affected by cardiac artefacts. The aim of this work was to investigate the performance of the fSampEn, the root mean square (RMS) and the average rectified value (ARV) on respiratory sEMG signals with supraventricular arrhythmias (SVA) for NRD estimation. fSampEn, ARV and RMS parameters increased as the inspiratory load increased during the test. fSampEn was less influenced by ECG with SVAs for the NRD estimation showing a greater response to respiratory sEMG, reflected with a higher percentage increase with increasing load (228 % total increase, compared to 142 % and 135 % for ARV and RMS, respectively).
机译:通过肌电图测量的神经呼吸驱动器可以研究呼吸肌肉的负荷与其容量之间的不平衡。表面呼吸肌电图(sEMG)是一种用于间接评估NRD的非侵入性工具。它还提供了一种评估呼吸肌激活水平和方式的方法。呼吸sEMG信号中心电图活动(ECG)的流行阻碍了其正确评估。此外,呼吸sEMG措施中异常心跳或心律不齐的发生可能使NRD估计更具挑战性。可以使用固定样本熵(fSampEn)评估呼吸sEMG,该技术受心脏伪影的影响较小。这项工作的目的是调查fSampEn,均方根(RMS)和平均整流值(ARV)在呼吸性sEMG信号伴室上性心律失常(SVA)的NRD评估中的性能。 fSampEn,ARV和RMS参数随着测试过程中吸气负荷的增加而增加。 fSampEn受带有SVA的ECG的影响较小,用于NRD估算,显示对呼吸sEMG的响应更大,反映出随着负荷增加而增加的百分比更高(总增加228%,而ARV和RMS分别为142%和135%)。

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