基于心电动力学李雅普诺夫指数的急性心肌梗死辅助筛查研究

Study on Auxiliary Screening of Acute Myocardial Infarction Based on Electrocardiographic Lyapunov Index

目的心电图作为常见的心脏疾病检测手段,是基于心电信号的状态信息表征进行诊断。心电图在指标量化方面依赖主观判断,若未发病时表征不明显,其用作急性心肌梗死等心脏疾病的筛查时敏感性存在不足。为寻求更好的途径,本文结合心电动力学理论和混沌学理论算法(即基于心电动力学李雅普诺夫指数的方法取得特征值进行指标量化)进行急性心肌梗死辅助筛查的研究。方法具体是截取心电信号的ST-T敏感段心电信号数字信号,依据确定学习理论将心电数据转化为更敏感的心电动力学数据,再运用混沌学理论计算心电动力学李雅普诺夫指数特征值,取得蕴含心电动力学敏感信息的量化指标,以30名健康人和30例急性心肌梗死患者作为对象进行验证性研究。结果急性心肌梗死患者的心电动力学李雅普诺夫指数特征值普遍高于健康人的心电动力学李雅普诺夫指数特征值,二者相比较差异具有统计学意义。结论基于心电动力学李雅普诺夫指数特征值的量化信息对于急性心肌梗死的辅助筛查具有潜在的临床价值。

Objective Electrocardiogram(ECG),as a common detection method for heart diseases,is based on the state information representation of ECG signals.In terms of index quantification,it depends on subjective judgment,and the representation is not obvious when it is not attacked.Therefore,the sensitivity of ECG in screening for acute myocardial infarction and other heart diseases is insufficient.In order to find a better way,this paper studies the auxiliary screening of acute myocardial infarction by combining the theory of cardiac electrodynamics and chaos theory algorithm(the method based on the Lyapunov index of cardiac electrodynamics to obtain the characteristic value for index quantification).Methods Specifically,it intercepts the digital signal of ST-T sensitive segment of ECG signal,transforms the ECG data into more sensitive ECG dynamic data according to the deterministic learning theory,and then calculates the characteristic value of the Lyapunov index of ECG dynamics by using chaos theory,and obtains the quantitative index containing the sensitive information of ECG dynamics.30 healthy people and 30 patients with acute myocardial infarction are taken as the quantitative indicators object to conduct a confirmatory study.Results The characteristic values of the Lyapunov index of Electro cardiodynamics in patients with acute myocardial infarction were generally higher than those in healthy people,and the difference was statistically significant.Conclusion The quantitative information based on the eigenvalues of the electrokinetic Lyapunov index has potential clinical value for the auxiliary screening of acute myocardial infarction.