Multifractal Detrended Fluctuation Analysis of Congestive Heart Failure Disease Based on Constructed Heartbeat Sequence

Shan Li

doi:10.1109/access.2020.3037080

Abstract

Heart rate variability (HRV) can be used as a common detection method for congestive heart failure (CHF). Existing researches regarding HRV, including both linear indicators and nonlinear characteristics, are mostly based on the RR intervals of the ECG signal. This article proposed a sequence that can reflect the regulation of sympathetic and parasympathetic nerve on heart rate, and on this basis, conducted multifractal detrended fluctuation analysis (MFDFA). We extracted multifractal features to quantitatively compare the complexity of proposed sequence between the healthy and CHF groups. Results showed that abnormal physiological and pathological conditions due to the weakening of autonomic nerve control can reduce the complexity of the heartbeat signal. Estimate the separation performance of all features, the best discrimination is obtained for the area under the mass index spectrum S1 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">τ</sub> as providing 100% accuracy in separating the Healthy Young and CHF groups, and 90.93% separation accuracy between the Healthy Elderly and CHF groups. This work provide a good basis for the diagnosis of CHF with a novel perspective.

Highlights

Congestive heart failure (CHF) refers to a pathological state due to the decrease in systolic and diastolic functions of the heart, which in turn cannot meet the needs of systemic tissue metabolism [1]
Heart rate variability (HRV) conventionally refers to the fluctuation of time intervals between adjacent heartbeats, which is generated by the dual modulation of sinus node by the sympathetic and parasympathetic nervous system (SNS & PNS) [7]–[9]
The increase in sympathetic tension is often associated with the occurrence of severe arrhythmia, at which time HRV will reduce to a certain extent

Summary

INTRODUCTION

Congestive heart failure (CHF) refers to a pathological state due to the decrease in systolic and diastolic functions of the heart, which in turn cannot meet the needs of systemic tissue metabolism [1]. The increase in parasympathetic tone can improve the threshold of arrhythmia, thereby reducing the occurrence of arrhythmia At this time, HRV appears as a certain increase. RR Interval (s) ECG Amplitude (mv) signals like heartbeat, nonlinear dynamic parameters are more effective than time-frequency analysis methods. We will propose a sequence that helps reflect the alternation of the increase and decrease of heart rate due to the sympathetic and parasympathetic nerve regulation, which will provide powerful diagnostic basis for predicting the physiological and pathological changes. We adopted the MFDFA method to analyze the heartbeat signal of CHF patients, and the specific process is as follows: Based on the regulation of heart rate by the autonomic nerve, we first constructed a sequence, that is, the monotonous increase to monotonous decrease amplitude ratios as derived from RR intervals.

METHODS AND RESULT

PREPROCESSING

METHODS

RESULTS

Findings

DISCUSSION