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Grouping similar seismocardiographic signals using respiratory information

机译:使用呼吸信息将相似的心电图信号分组

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Seismocardiography (SCG) offers a potential noninvasive method for cardiac monitoring. Quantification of the effects of different physiological conditions on SCG can lead to enhanced understanding of SCG genesis, and may explain how some cardiac pathologies may affect SCG morphology. In this study, the effect of the respiration on the SCG signal morphology is investigated. SCG, ECG, and respiratory flow rate signals were measured simultaneously in 7 healthy subjects. Results showed that SCG events tended to have two slightly different morphologies. The respiratory flow rate and lung volume information were used to group the SCG events into inspiratory/expiratory groups or low/high lung-volume groups, respectively. Although respiratory flow information could separate similar SCG events into two different groups, the lung volume information provided better grouping of similar SCGs. This suggests that variations in SCG morphology may be due, at least in part, to changes in the intrathoracic pressure or heart location since those parameters correlates more with lung volume than respiratory flow. Categorizing SCG events into different groups containing similar events allows more accurate estimation of SCG features, and better signal characterization, and classification.
机译:地震心动图(SCG)为心脏监测提供了一种潜在的无创方法。量化不同生理状况对SCG的影响可以增强对SCG起源的理解,并可以解释某些心脏病理如何影响SCG形态。在这项研究中,研究了呼吸作用对SCG信号形态的影响。在7位健康受试者中同时测量了SCG,ECG和呼吸流速信号。结果表明,SCG事件倾向于具有两种略有不同的形态。呼吸流速和肺活量信息分别用于将SCG事件分为吸气/呼气组或低/高肺活量组。尽管呼吸流量信息可以将相似的SCG事件分为两个不同的组,但是肺体积信息可以更好地将相似的SCG分组。这表明SCG形态的变化可能至少部分是由于胸腔内压力或心脏位置的变化所致,因为这些参数与肺活量的相关性要比呼吸流量更大。将SCG事件分类到包含相似事件的不同组中,可以更准确地估计SCG功能,并更好地进行信号表征和分类。

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