Paper Info
Title
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 low-and 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.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2911555
IEEE ACCESS
Keywords
Field
DocType
Electromechanical delay (EMD),heart rate variability (HRV),systolic period variability (SPV),diastolic period variability (DPV),dynamical patterns,noninvasive detection,coronary artery disease (CAD)
Coronary artery disease,Phonocardiogram,Sample entropy,Computer science,Heart rate variability,Internal medicine,Diastole,Pattern analysis,Cardiology,Standard deviation,Cardiac function curve,Distributed computing
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Yang Li1659125.00
Xinpei Wang2196.78
Changchun Liu3329.39
Liping Li417736.54
chang yan592.66
Lianke Yao621.40
Peng Li75910.17