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Towards robust estimation of systolic time intervals using head-to-foot and dorso-ventral components of sternal acceleration signals

机译:使用胸骨加速度信号的头到脚和背腹分量对收缩期间隔进行鲁棒估计

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Continuous measurement of cardiac time intervals throughout normal activities of daily living is of interest for both chronic disease management and preventive wellness monitoring. Systolic time intervals in particular - i.e., pre-ejection period (PEP) and left ventricular ejection time (LVET) - have been shown to be relevant to assessing myocardial health and performance, but are challenging to measure with wearable sensors. In this paper, we present novel methods for estimating PEP and LVET from a single three-axis accelerometer placed at the sternum, based on the measurement of cardiogenic vibrations: seismocardiography (SCG) and ballistocardiography (BCG). Although such signals have been examined in the existing literature, the analysis and interpretation has focused mainly on the dorso-ventral components only in the context of systolic time interval estimation. In this paper, we find that features extracted from the head-to-foot accelerations yield better correlations to PEP measured from impedance cardiogram (ICG) than standard approaches based on dorso-ventral components. Additionally, we examine the effects of postural variations on the correlation between PEP estimated from accelerometer and ICG signals and also on correlation between LVET estimated from both sensors. We determine that such correlations are robust to postural changes. Based on these findings, we anticipate that wearable, accelerometer based vibration measurements from standing subjects can be used for robust systolic time interval estimation in a variety of ubiquitous cardiovascular health and fitness sensing applications.
机译:对于慢性疾病管理和预防性健康监测而言,在日常生活的正常活动中连续测量心脏时间间​​隔是很重要的。尤其是心脏收缩的时间间隔-即射血前期(PEP)和左心室射血时间(LVET)-与评估心肌健康和性能有关,但是使用可穿戴式传感器进行测量具有挑战性。在本文中,我们根据心源性振动的测量值,从位于胸骨的单个三轴加速度计中估算PEP和LVET的新方法:地震心动图(SCG)和心动描记法(BCG)。尽管在现有文献中已经检查了这种信号,但是仅在收缩期间隔估计的背景下,分析和解释主要集中在背腹成分上。在本文中,我们发现从头到脚加速度提取的特征与从阻抗心电图(ICG)测得的PEP的相关性比基于背腹成分的标准方法更好。此外,我们检查了姿势变化对加速度计和ICG信号估计的PEP之间的相关性以及两个传感器估计的LVET之间的相关性的影响。我们确定这样的相关性对于姿势变化是鲁棒的。基于这些发现,我们预计来自站立受试者的可穿戴式,基于加速度计的振动测量结果可用于各种无处不在的心血管健康和健身传感应用中的可靠的收缩时间间隔估计。

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