Thuraisingham R A
1A, Russell Street, Eastwood, NSW 2122, Australia.
J Arrhythm. 2016 Feb;32(1):57-61. doi: 10.1016/j.joa.2015.08.006. Epub 2015 Nov 3.
Knowledge of the onset of atrial fibrillation (AF) episodes in patients with paroxysmal atrial fibrillation (PAF) will enable them to better manage this condition. Current advances in mobile technology allow RR interval data to be obtained in real time. An analysis technique using RR interval data is presented with a view to alert a subject before a PAF episode.
The method is based on a time series of standard deviation and 0.99 quantile values of the spectral entropy, constructed from RR data. The RR data are taken from three time periods. The first time period has no occurrences of AF for 45 min to either side of the time period. The second time period just precedes an AF attack. Both of these are of thirty minutes duration. The third time period of approximately 5 min follows the second, and is when AF occurs.
Twenty-two PAF subjects were studied and in all cases there was a steady increase in the values of these indices as the onset of the AF attack approached.
This method of analysis of RR interval data shows potential use to alert a PAF subject before the onset of an AF episode.
了解阵发性心房颤动（PAF）患者心房颤动（AF）发作的情况将使他们能够更好地管理这种疾病。移动技术的当前进展允许实时获取RR间期数据。提出了一种使用RR间期数据的分析技术，旨在在PAF发作前提醒受试者。
该方法基于从RR数据构建的频谱熵的标准差和0.99分位数的时间序列。RR数据取自三个时间段。第一个时间段在该时间段两侧各45分钟内没有AF发作。第二个时间段恰好在AF发作之前。这两个时间段均为30分钟。第三个时间段约5分钟，紧随第二个时间段之后，是AF发生的时间。
对22名PAF受试者进行了研究，在所有情况下，随着AF发作的临近，这些指标的值都稳步增加。
这种RR间期数据分析方法显示出在AF发作前提醒PAF受试者的潜在用途。
