三种不同的算法识别心房颤动患者在心电图无心房颤动阶段

N. Kikillus, G. Hammer, N. Lentz, F. Stockwald, A. Bolz
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引用次数: 23

摘要

本文介绍并比较了三种不同的方法来检测心房颤动的算法。这些算法中的每一个都可以识别患有心房颤动的患者,即使在ECG上没有可见的心房颤动。所有方法都基于rr区间;因此,只需要一个单通道ECG。这些算法已经使用MIT-BIH房颤数据库和MIT-BIH正常窦性心律数据库进行了测试。方法1的灵敏度为91.5%,特异度为96.9%。方法2的灵敏度为93.3%,特异性为92.8%;方法3的灵敏度为94.1%,特异性为93.4%。即使假定房颤负担为0%,灵敏度仍然令人满意(方法1、方法2和方法3的灵敏度分别为82.9%、96.3%和94.1%)。
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Three different algorithms for identifying patients suffering from atrial fibrillation during atrial fibrillation free phases of the ECG
The paper presents and compares three different methods to detect atrial fibrillation using algorithms. Each of these algorithms can identify patients suffering from atrial fibrillation even if there is no atrial fibrillation visible on the ECG. All methods are based on RR-intervals; thus, only a single channel ECG is required. These algorithms have been tested using the MIT-BIH atrial fibrillation database and the MIT-BIH normal sinus rhythm database. The sensitivity and specificity of method 1 is 91.5% and 96.9% respectively. Method 2 results in a sensitivity of 93.3% and a specificity of 92.8% and method 3 in a sensitivity of 94.1% and a specificity of 93.4%. Even if an atrial fibrillation burden of 0% is assumed, the sensitivity still proves satisfactory (sensitivity of method 1, 2 and 3 is 82.9%, 96.3% and 94.1%, respectively).
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