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A parametric model approach for quantification of short term QT variability uncorrelated with heart rate variability

机译:与心率变异性不相关的短期QT变异性量化的参数模型方法

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In this work we propose to assess the relation between HRV and QTV measured by an automatic delineator. A low order linear autoregressive model on RR versus QT interactions was used to explore short term relations and quantify the fractions of QTV correlated and not correlated with HRV. Power spectral density measures were estimated from the total QTV and from the two separated fractions using the proposed model. Simulated RR and QT series were used to quantify the error bounds associated to the method performance. ECG records of young normal subjects were processed to obtain the RR and QT series. The high QTV fraction not correlated with RR found in these records (over 40% in 98% of the segments) indicates that an important part of QTV can be driven by other factors rather than by heart rate, and may contain complementary information.
机译:在这项工作中,我们建议评估自动轮廓仪测量的HRV和QTV之间的关系。使用RR与QT相互作用的低阶线性自回归模型来探索短期关系,并量化与HRV相关和不相关的QTV的比例。使用建议的模型,从总QTV和两个分离的馏分中估算出功率谱密度测量值。模拟的RR和QT系列用于量化与方法性能相关的误差范围。处理年轻正常受试者的心电图记录以获得RR和QT系列。高QTV分数与这些记录中发现的RR不相关(98%的片段中超过40%)表明QTV的重要部分可能由其他因素而非心率驱动,并且可能包含补充信息。

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