Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim Choo Min, Suri Jasjit S
Department of ECE, Ngee Ann Polytechnic, 535 Clementi Road, Singapore, Singapore 599 489.
Med Biol Eng Comput. 2006 Dec;44(12):1031-51. doi: 10.1007/s11517-006-0119-0. Epub 2006 Nov 17.
Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.
心率变异性（HRV）是对调节心脏正常节律的多种生理因素的可靠反映。事实上，它们提供了一种观察交感神经系统和副交感神经系统之间相互作用的有力手段。研究表明，产生该信号的结构不仅简单呈线性，还涉及非线性因素。心率（HR）是一个非平稳信号；其变化可能包含当前疾病的指标，或关于即将发生的心脏疾病的警示。这些指标可能随时出现，也可能在一天中的特定时间段随机出现。研究和查明数小时内收集的大量数据中的异常情况既费力又耗时。因此，心率变异性分析（即时心率与时间轴的关系）已成为评估自主神经系统活动的一种常用非侵入性工具。基于计算机的分析工具可用于深入研究一整天内的数据，这在诊断中非常有用。因此，利用计算机提取和分析的HRV信号参数在诊断中非常有用。在本文中我们讨论了HRV的各种应用以及用于分析HRV的不同线性、频域、小波域和非线性技术。
