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The Use of Sequential RR Distributions to Detect Atrial Fibrillation Episodes in Very Long Term ECG Monitoring

机译:使用顺序RR分布在非常长期的心电图监测中检测心房颤动剧集

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The Sequential RR Distribution (SRRD) is introduced as a diagnostic tool for AF detection and classification. SRRD is obtained by computing consecutive RR histogram distributions in successive temporal windows and plotting them prospectically the validation of SRRD for AF detection was performed using the MIT AF database. A interactive graphic interface was developed to navigate in the SRRD and to manually annotate the onset and offset of the AF episodes. Two expert cardiologists were trained to evaluate the SRRD using an home-made database. They were asked to annotate AF events in the MIT database using RR distributions (without accessing the ECG). The results were: episodes sensitivity 97%, episode P+ 78%, duration sensitivity 98%, duration P+ 95%. These results show that sequential RR histogram distributions are accurate enough to allow the detection of AF events without the need of viewing the ECG signal.
机译:序列RR分布(SRRD)被引入为AF检测和分类的诊断工具。通过计算连续的时间窗口中的连续RR直方图分布来获得SRRD,并通过MIT AF数据库进行术语绘制SRRD的SRRD验证。开发了一个交互式图形界面以在SRRD中导航,并手动注释AF剧集的开始和偏移量。培训了两个专家的心脏病学家使用自制数据库来评估SRRD。被要求使用RR发行版(无需访问ECG)向MIT数据库中注释AF事件。结果是:发作灵敏度97%,第P + 78%,持续时间灵敏度98%,持续时间P + 95%。这些结果表明,顺序RR直方图分布足以足以允许检测AF事件而不需要查看ECG信号。

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