Analysis of heart rate dynamics based on nonlinear lagged returned map for sudden cardiac death prediction in cardiovascular patients

Abstract

Sudden cardiac death (SCD) generally applied to an unpredicted death from a cardiovascular cause in a subject with or without preexisting heart disease. The main goal of this study was analyzing the Electrocardiogram (ECG) signal to design an algorithm to predict SCD risk. In this paper, ECG signals of 23 subjects (13 males, 8 females and 2 unknown), ranging from 17 to 89 years old necessary for the research were obtained from the Physionet database. For this purpose, we developed a new method to predict SCD, a 10-min prior heart attack using the return map. The aim of this study is a novel method based on Lag return map for in control patients and SCD classes. Return map with six different lags (1–6) was constructed in two-time intervals. After that, the non-linear features that include SD1, SD2, SD1/SD2 for each Lag was measured. The result shows that the rate of changes in SD1 and SD1/SD2 with increasing lags were increased significantly but in SD2 with increasing lags was decreased in two intervals. Statistical analysis indicates that return map parameters show changes in the transition to death episode (p < 0.05). Besides, there were significant changes (p < 0.01) in closer segments to death. In conclusion, it will be possible to predict SCD based on the nonlinear feature that can alarm doctors of an imminent SCD, helping them provide timely treatments that can increase the survival rate of patients and thus reduce the mortality rate.