目的  针对传统心电图状态信息表征方法所存在的心脏疾病特征提示的敏感性不足、指标量化依赖主观判断、病发期存在心电波形无明显改变等临床局限，探讨心电混沌信号特征C0复杂度与急性冠脉综合征(ACS)的相关性，以寻求更好的ACS辅助检测方向。方法  以确定学习算法获取心电信号动力学数据，基于混沌学理论计算得出心电动力学数据的混沌特征指标C0复杂度，随机选择心电波形无明显改变的ACS患者30例和健康者30例的心电信号数据，对C0复杂度进行统计分析。结果  ACS患者心电动力学数据的C0复杂度与健康人间的差异有统计学意义(P<0.001)。结论  ACS患者与健康人群的心电动力学数据的C0复杂度差异有统计学意义，心电混沌信号特征C0复杂度可用于辅助检测ACS。

Objective  To explore the correlation between C0 complexity of ECG chaotic signal characteristics and acute coronary syndrome (ACS), and to find a better direction in auxiliary detection of ACS. Methods  The electrocardiographic dynamics data were obtained by definite learning algorithm, and the chaotic characteristic index C0 complexity of  electrocardiographic dynamics data was calculated based on chaos theory. The ECG with no significant change in ECG shape in 30 patients with ACS and 30 healthy subjects were randomly selected. The C0 complexity data of patients with ACS and healthy subjects were  analyzed. Results  The C0 complexity of ECG in patients with ACS was statistically significant compared with that of healthy individuals(P<0001). Conclusion  The C0 complexity of electrocardiographic dynamics data between patients with ACS and healthy people is statistically different, which has potential clinical value for auxiliary detection in patients with ACS.