Spatiotemporal representation of cardiac vectorcardiogram (VCG) signals

Hui Yang,Satish Ts Bukkapatnam,Ranga Komanduri

doi:10.1186/1475-925x-11-16

Hui Yang, Satish Ts Bukkapatnam + Show 1 more

Open Access

https://doi.org/10.1186/1475-925x-11-16

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Abstract

BackgroundVectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns.Materials and methodsWe present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG) through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility.ResultsIn this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC), myocardial infarction (MI), atrial fibrillation (AF) and bundle branch block (BBB). The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80) of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368) of MI subjects are found to remain in Octant 6 and the rest (68.21%) spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more.ConclusionsSpatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac pathological patterns and enhance the automatic assessment of cardiovascular diseases.

Highlights

Vectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body
Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac pathological patterns and enhance the automatic assessment of cardiovascular diseases
We extracted the recurrence qTuhaenrteifliactaivtieonersrtoartiissticcaslcfourla8te0dhaesal txhtyruecoÀnxtrposelusdoa n=dxtcruaelÞc,uwlahteedrethxetrureeilsattihvee errors. quantifier computed from the VCG state space, and xpseudo is from the lagreconstructed pseudo state space

Summary

Introduction

Vectorcardiogram (VCG) signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. This is especially so because timedomain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Much of that information is redundant and even in that, only a small fraction of the data is used in the analysis by the physicians based on experience, expertise, and oftentimes on the memorization of ECG signals for different cardiac disorders This is a difficult task and cardiologists are constantly looking for more accurate and effective alternatives. We propose a new dynamic display of VCG to characterize both spatial and temporal patterns of cardiac electrical activities as an alternative for the conventional 12-lead ECG

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