用符号相对熵量化涉及股权的心跳非线性动力学
Symbolic relative entropy in quantifying nonlinear dynamics of equalities-involved heartbeats
摘要：
在心率等状态非线性动力学分析中，提出了一种有效的非线性复杂性参数--符号相对熵，用于度量符号序列的概率发散性。由于信号采集分辨率的限制，离散心跳中的相等状态并不罕见，更重要的是，相等状态包含潜在的重要心脏调节信息，这些信息被一些混沌确定性参数和时间不对称测量所忽略。与相等状态相关的符号化相对熵满足心跳非线性动力学复杂性检测的要求，对某些不考虑相等性的非线性动力学参数具有优势。心脏活动的研究表明，最高的概率分歧的健康年轻人的心率，并强调事实，心脏疾病和老龄化降低非线性动力学复杂性的心率。
英文摘要：
Symbolic relative entropy, an efficient nonlinear complexity parameter measuring probabilistic divergences of symbolic sequences, is proposed in our nonlinear dynamics analysis of heart rates considering equal states. Equalities are not rare in discrete heartbeats because of the limits of resolution of signals collection, and more importantly equal states contain underlying important cardiac regulation information which is neglected by some chaotic deterministic parameters and temporal asymmetric measurements. The relative entropy of symbolization associated with equal states has satisfied nonlinear dynamics complexity detections in heartbeats and shows advantages to some nonlinear dynamics parameters without considering equalities. Researches on cardiac activities suggest the highest probabilistic divergence of the healthy young heart rates and highlight the facts that heart diseases and aging reduce the nonlinear dynamical complexity of heart rates.
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