用一种新的心跳间期小波分析方法鉴别健康与病态心脏自主神经系统
Discrimination of the Healthy and Sick Cardiac Autonomic Nervous System by a New Wavelet Analysis of Heartbeat Intervals
摘要：
我们证明，它是可能的区分与健康受试者和患者之间的各种功能障碍的心脏神经系统的RR间期的多分辨率小波变换的方式完全确定。我们重复了Thurner等人对不同主题的研究。我们表明，重建系列使用过滤器，丢弃小波系数与更高的尺度，使人们能够分类的方法，否则是不确定的个人。我们建议在$\sim 0.035$范围内（对于上述滤波器），滤波重建RR间期时间序列的标准差的界定诊断值，低于该值的个体处于风险中。
英文摘要：
We demonstrate that it is possible to distinguish with a complete certainty between healthy subjects and patients with various dysfunctions of the cardiac nervous system by way of multiresolutional wavelet transform of RR intervals. We repeated the study of Thurner et al on different ensemble of subjects. We show that reconstructed series using a filter which discards wavelet coefficients related with higher scales enables one to classify individuals for which the method otherwise is inconclusive. We suggest a delimiting diagnostic value of the standard deviation of the filtered, reconstructed RR interval time series in the range of $\sim 0.035$ (for the above mentioned filter), below which individuals are at risk.
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