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Current Directions in Biomedical Engineering

Joint Journal of the German Society for Biomedical Engineering in VDE and the Austrian and Swiss Societies for Biomedical Engineering

Editor-in-Chief: Dössel, Olaf

Editorial Board: Augat, Peter / Buzug, Thorsten M. / Haueisen, Jens / Jockenhoevel, Stefan / Knaup-Gregori, Petra / Kraft, Marc / Lenarz, Thomas / Leonhardt, Steffen / Malberg, Hagen / Penzel, Thomas / Plank, Gernot / Radermacher, Klaus M. / Schkommodau, Erik / Stieglitz, Thomas / Urban, Gerald A.

CiteScore 2018: 0.47

Source Normalized Impact per Paper (SNIP) 2018: 0.377

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Analysis and classification of ECG-waves and rhythms using circular statistics and vector strength

Jan-Dirk Janßen
  • Corresponding author
  • Technische Hochschule Mittelhessen, Dept. Life Science Engineering, Wiesenstr. 14, D-35390 Gießen, Germany
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/ Thomas Schanze
Published Online: 2017-09-07 | DOI: https://doi.org/10.1515/cdbme-2017-0020


The most common way to analyse heart rhythm is to calculate the RR-interval and the heart rate variability. For further evaluation, descriptive statistics are often used. Here we introduce a new and more natural heart rhythm analysis tool that is based on circular statistics and vector strength. Vector strength is a tool to measure the periodicity or lack of periodicity of a signal. We divide the signal into non-overlapping window segments and project the detected R-waves around the unit circle using the complex exponential function and the median RR-interval. In addition, we calculate the vector strength and apply circular statistics as wells as an angular histogram on the R-wave vectors. This approach enables an intuitive visualization and analysis of rhythmicity. Our results show that ECG-waves and rhythms can be easily visualized, analysed and classified by circular statistics and vector strength.

Keywords: circular statistics; vector strength; heart rate variability; ECG classification

About the article

Published Online: 2017-09-07

Citation Information: Current Directions in Biomedical Engineering, Volume 3, Issue 2, Pages 91–94, ISSN (Online) 2364-5504, DOI: https://doi.org/10.1515/cdbme-2017-0020.

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©2017 Jan-Dirk Janßen et al., published by De Gruyter, Berlin/Boston. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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