Preprocessing RR interval time series for heart rate variability analysis and estimates of standard deviation of RR intervals
Preprocessing RR interval time series for heart rate variability analysis and estimates of standard deviation of RR intervals
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DOI：
10.1016/j.cmpb.2006.05.002
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发表时间：
2006-07-01
影响因子：
6.1
通讯作者：
Thuraisingham, R. A.
中科院分区：
文献类型：
--
作者：
Thuraisingham, R. A.
心率变异性涉及对心跳间隔（称为 RR 间隔）的波动的分析。获得的长时间 RR 时间序列存在非平稳性和异位节拍的存在，这阻碍了有用统计信息的提取。该论文描述了一种基于小波的趋势消除技术和消除异位节拍的非线性滤波器。这试图纠正最近先进的心率工具包中观察到的局限性 [J. .尼斯卡宁，M.P.塔尔维宁，P.O.兰塔霍 P.A. Karjalainen，高级 HRV 分析软件，Comput。方法。程序。 Biomed.,76 (2004) 73-81] 预处理时。结果令人鼓舞。然后使用预处理的数据获得 15 名健康患者和 15 名充血性心力衰竭患者的 RR 间期时间序列 (SDRR) 标准差。结果证明了预处理的重要性。分析显示，与健康组相比，充血性心力衰竭患者的SDRR值较低。 (c) 2006 Elsevier Ireland Ltd. 保留所有权利。
Heart rate variability is concerned with the analysis of the fluctuations in the interval between heart beats known as RR intervals. The long time RR time series obtained suffer from non-stationarity and the presence of ectopic beats, which prevents extraction of useful statistical information. The paper describes a wavelet-based technique for trend removal and a nonlinear filter to remove ectopic beats. This attempts to correct the limitations observed in a recent advanced heart rate toolkit [J. .Niskanen, M.P. Tarvainen, P.O. Rantaaho P.A. Karjalainen, Software for advanced HRV analysis, Comput. Meth. Prog. Biomed.,76 (2004) 73-81] when preprocessing. The results are encouraging. The preprocessed data are then used to obtain the standard deviation of RR interval time series (SDRR) of 15 healthy patients and 15 patients suffering from congestive heart failure. The results demonstrate the importance of preprocessing. The analysis show that the SDRR values of congestive heart failure patients are depressed compared to the healthy group. (c) 2006 Elsevier Ireland Ltd. All rights reserved.