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Abstract 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<0001). 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.
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