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Extraction and Quantification Clusters of Three-Dimensional Lorenz Plots.

Min Hu1, Weixing Han2, Jun Liu3

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Studies in Health Technology and Informatics
|January 4, 2018
PubMed
Summary

The three-dimensional Lorenz plot (3DLP) effectively identifies cardiac arrhythmias using RR-interval data. This method accurately distinguishes abnormal heart rhythms, aiding in diagnosis and potentially offering prognostic insights.

Keywords:
ArrhythmiaElectrocardiographyPrognosis

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • The Lorenz plot (LP) is a visualization tool for analyzing electrocardiogram (ECG) signals and heart rate variability.
  • Analyzing long-time ECG signals, particularly RR-interval time series, is crucial for diagnosing cardiac arrhythmias.
  • Premature complexes in ECG data present a challenge for traditional analysis methods.

Purpose of the Study:

  • To develop and evaluate a three-dimensional Lorenz plot (3DLP) method for analyzing RR-interval time series.
  • To accurately differentiate between normal and abnormal cardiac rhythm patterns, specifically eccentric clusters (ECs) indicative of arrhythmias.
  • To assess the diagnostic capability of 3DLP for identifying ventricular extrasystoles.

Main Methods:

  • Constructed 3D LPs using three successive RR intervals (X, Y, Z axes) from 50 Holter records.
  • Applied stereographic projection along the space diagonal to the 3D LPs.
  • Utilized dot radii and azimuth frequency distribution to distinguish and identify eccentric clusters (ECs).
  • Analyzed polar coordinates (radius and angle) of transformed 3DLP data.

Main Results:

  • The 3DLP method distinguished eccentric clusters (ECs) from centric clusters with 94 ± 6.0% accuracy.
  • Eccentric scatter-dots were identified by azimuth frequency distribution with 93 ± 13.3% accuracy.
  • A specific angular threshold (APF < -2.8°) in CPN ECs supported ventricular extrasystoles diagnosis with high sensitivity (1.0) and specificity (0.92).

Conclusions:

  • Transformed polar coordinates of 3DLP effectively extract and quantify clusters for arrhythmia diagnosis.
  • The 3DLP method demonstrates high accuracy in identifying cardiac arrhythmias and distinguishing premature complexes.
  • This approach may offer additional prognostic information beyond arrhythmia diagnosis.