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Algorithms for detecting atrial arrhythmias from discriminatory signatures of ventricular cycle lengths
Algorithms for detecting atrial arrhythmias from discriminatory signatures of ventricular cycle lengths
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机译:从心室周期长度的鉴别特征中检测房性心律失常的算法
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摘要
Detection of arrhythmias is facilitated using irregularity of ventricular beats measured by delta-RR (RR) intervals that exhibit discriminatory signatures when plotted in a Lorenz scatter-plot. An AF signature metric is established characteristic of episodes of AF that exhibit highly scattered (sparse) distributions or formations of 2-D data points. An AFL signature metric is established characteristic of episodes of AFL that exhibit a highly concentrated (clustered) distribution or formation of 2-D data points. A set of heart beat interval data is quantified to generate highly scattered (sparse) formations as a first discrimination metric and highly concentrated (clustered) distributions or formations as a second discrimination metric. The first discrimination metric is compared to the AF signature metric, and/or the second discrimination metric is compared to the AFL signature metric. AF or HFL is declared if the first discrimination metric satisfies either one of the AF signature metric.
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