Variability of Cardiac Electromechanical Delay With Application to the Noninvasive Detection of Coronary Artery Disease

Abstract

Heart rate variability (HRV), systolic period variability (SPV), and diastolic period variability (DPV) have shown potential for assessing cardiac function. It is unknown whether the time delay between the myocardial electrical and mechanical activities (i.e., electromechanical delay, EMD) also possesses variability, and if it does, whether this EMD variability (EMDV) could render additional value for cardiac function assessment. In this paper, we extracted the beat-to-beat EMD from 5-min simultaneously recorded electrocardiogram and phonocardiogram signals in 30 patients with coronary artery disease (CAD) and 30 healthy control subjects, and studied its variability using the same methods as applied for HRV including time-domain measures [mean and standard deviation (SD)], frequency-domain measures [normalized lowand high-frequency (LFn, HFn) and LF/HF)], and nonlinear measures [sample entropy (SampEn), permutation entropy (PE), and dynamical patterns]. In addition, we examined whether the addition of EMDV could offer improved performance for distinguishing between the two groups compared to using the HRV, SPV, and DPV features. Support vector machine with 10-fold cross-validation was used for classification. Results showed increased SD of SPV, increased mean, SD and decreased SampEn of EMDV in CAD patients. Besides, the dynamical pattern analysis showed that CAD patients had significantly increased fluctuated patterns and decreased monotonous patterns in EMDV. In particular, the addition of EMDV indices dramatically increased the classification accuracy from 0.729 based on HRV, SPV, and DPV features to 0.958. Our results suggest promising of the EMDV analysis that could potentially be helpful for detecting CAD noninvasively. INDEX TERMS Electromechanical delay (EMD), heart rate variability (HRV), systolic period variability (SPV), diastolic period variability (DPV), dynamical patterns, noninvasive detection, coronary artery disease (CAD). I. INTRODUCTION Electrocardiogram (ECG) and phonocardiogram (PCG) measurements are two commonly-used non-invasive and non-intrusive methods for diagnosing cardiac diseases. ECG reflects the cardiac electrical activity while PCG records heart sounds produced by myocardial mechanical The associate editor coordinating the review of this manuscript and approving it for publication was György Eigner. activities (i.e., contraction and relaxation). One cardiac cycle is composed of two mechanical intervals, namely, systolic period (SP) and diastolic period (DP). Previous studies have found reduced mean cardiac cycle (i.e., mean RR intervals in ECG) in diabetes [1] and patients with chronic congestive heart failure [2]. Besides, researchers also found that abnormal SP and DP could indicate mechanical abnormalities of ventricular function [3]. Prolonged SP and shortened DP were found in children with heart failure [4], [5], and the shortening

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