对RR间期时间序列进行预处理，以进行心率变异性分析和RR间期标准差估计。
Preprocessing RR interval time series for heart rate variability analysis and estimates of standard deviation of RR intervals.
作者信息
Thuraisingham R A
机构信息
A, Eastwood, NSW, Australia.
出版信息
Comput Methods Programs Biomed. 2006 Jul;83(1):78-82. doi: 10.1016/j.cmpb.2006.05.002. Epub 2006 Jun 27.
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. Ranta-aho 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.
心率变异性涉及对心跳间隔波动的分析，这种波动以RR间期为人所知。所获得的长时间RR时间序列存在非平稳性和异位搏动，这阻碍了有用统计信息的提取。本文描述了一种基于小波的趋势去除技术和一种用于去除异位搏动的非线性滤波器。这试图纠正最近一个先进心率工具包[J.尼斯卡宁、M.P.塔尔瓦宁、P.O.兰塔 - 阿霍、P.A.卡尔亚莱宁，《用于高级心率变异性分析的软件》，《计算机方法与生物医学程序》，76(2004)73 - 81]在预处理时所观察到的局限性。结果令人鼓舞。然后，对15名健康患者和15名充血性心力衰竭患者的RR间期时间序列进行预处理后，用来获取RR间期的标准差（SDRR）。结果证明了预处理的重要性。分析表明，与健康组相比，充血性心力衰竭患者的SDRR值较低。
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