Acharya U Rajendra, Kannathal N, Krishnan S M
Department of ECE, Ngee Ann Polytechnic, Singapore 599 489.
Physiol Meas. 2004 Oct;25(5):1139-51. doi: 10.1088/0967-3334/25/5/005.
The electrocardiogram is a representative signal containing information about the condition of the heart. The shape and size of the P-QRS-T wave, the time intervals between its various peaks, etc may contain useful information about the nature of disease affecting the heart. However, the human observer cannot directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the heart rate variability signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. The HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially nonstationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. This paper deals with the analysis of eight types of cardiac abnormalities and presents the ranges of linear and nonlinear parameters calculated for them with a confidence level of more than 90%.
心电图是一种代表信号，包含有关心脏状况的信息。P-QRS-T波的形状和大小、其各个波峰之间的时间间隔等可能包含有关影响心脏疾病性质的有用信息。然而，人类观察者无法直接监测这些细微细节。此外，由于生物信号具有高度主观性，症状可能在时间尺度上随机出现。因此，使用计算机提取和分析的心率变异性信号参数在诊断中非常有用。心率变异性（HRV）分析已成为评估自主神经系统活动的一种流行的非侵入性工具。HRV分析基于这样一种概念，即快速波动可能特别反映交感神经和迷走神经活动的变化。研究表明，产生信号的结构不仅简单线性，还涉及非线性因素。这些信号本质上是非平稳的；可能包含当前疾病的指标，甚至是关于即将发生疾病的警告。这些指标可能随时存在，也可能在时间尺度上随机出现。然而，研究和查明在数小时内收集的大量数据中的异常情况既费力又耗时。本文探讨了八种心脏异常情况的分析，并给出了计算出的线性和非线性参数范围，其置信水平超过90%。
