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

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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.

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Abbreviations

BLPF:

Butterworth low pass filter

BPNN:

Backpropagation neural network

DBNN:

Decisionbased neural network

DFA:

Detrended fluctuation analysis

ECG:

Electrocardiography

FFT analysis:

Fast Fourier transform

HF:

High frequency

HRV:

Heart rate variability

KNN:

K-nearest neighbour

LF:

Low frequency

LFP:

Low-frequency power

LMS:

Least mean square

MNN:

Mean of all NN intervals

MRI:

Magnetic resonance imaging

PD2i:

Point correlation dimension

PNN:

Probabilistic neural network

PNN50:

Probability the difference of successive intervals be more than 50 ms

RMSSD:

Root mean square of the successive differences

RRI:

The interval between R waves in the ECG

RQA:

Recurrence quantification analysis

SCD:

Sudden cardiac death

SD1:

Standard deviations one

SD2:

Standard deviations two

SDANN:

Standard deviation of the mean of sinus R–R intervals

SDNN:

Standard deviation of the NN intervals

SDSD:

Standard deviation of successive differences

STD:

Standard deviation

SVM:

Support vector machine

TF:

Time–frequency

VF:

Ventricular fibrillation

VFib:

Ventricular fibrillation

VFL:

Ventricular flutter

VT:

Ventricular tachyarrhythmia

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Authors and Affiliations

  1. Department of Biomedical Engineering, Faculty of Health, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran

    Farangis Sajadi Moghadam, Mohammad Karimi Moridani & Yasaman Jalilehvand

  2. Islamic Azad University of Medical Sciences, Shariati St., Tehran, Iran

    Mohammad Karimi Moridani

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  1. Farangis Sajadi Moghadam
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  2. Mohammad Karimi Moridani
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Correspondence to Mohammad Karimi Moridani.

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Moghadam, F.S., Moridani, M.K. & Jalilehvand, Y. Analysis of heart rate dynamics based on nonlinear lagged returned map for sudden cardiac death prediction in cardiovascular patients. Multidim Syst Sign Process 32, 693–714 (2021). https://doi.org/10.1007/s11045-020-00755-8

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