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tm - Technisches Messen

Plattform für Methoden, Systeme und Anwendungen der Messtechnik

[TM - Technical Measurement: A Platform for Methods, Systems, and Applications of Measurement Technology
]

Editor-in-Chief: Puente León, Fernando / Zagar, Bernhard


IMPACT FACTOR 2018: 0.594

CiteScore 2018: 0.54

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Source Normalized Impact per Paper (SNIP) 2018: 0.563

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2196-7113
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Volume 83, Issue 2

Issues

Model assisted biosignal analysis of atrial electrograms

Modellbasierte Biosignalanalyse von atrialen Elektrogrammen

Olaf Dössel
  • Corresponding author
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Email
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Gustavo Lenis
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Axel Loewe
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Markus Rottmann
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Gunnar Seemann
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Tobias Oesterlein
  • Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2016-02-09 | DOI: https://doi.org/10.1515/teme-2015-0122

Abstract

Cardiologists measure electric signals inside the human heart aiming at a better diagnosis and optimized therapy of atrial arrhythmias like atrial flutter and atrial fibrillation. The catheters that are used for this purpose are improving: now they are able to pick up the electric signals at up to 64 positions inside the heart simultaneously. The patterns of electric depolarization are sometimes very simple, comparable to plane waves. But in case of patients with severe atrial arrhythmias they can be quite complex: U-turns around a line of block, ectopic centres, break throughs, reentry circuits, rotors, fractionated signals and chaotic patterns are often observed. Methods of biosignal analysis can support the cardiologists in classifying the signals and extract information of high diagnostic relevance. Computer models of the electrophysiology of the human heart can serve to design better algorithms for data analysis and to test algorithms, because the “ground truth” is known.

Zusammenfassung

Kardiologen messen oft elektrische Signale im Inneren des Herzens mit dem Ziel einer besseren Diagnose und Therapieplanung von atrialen Arrhythmien wie z. B. Vorhofflattern und Vorhofflimmern. Die Katheter, die hierbei zum Einsatz kommen, werden kontinuierlich verbessert. Heute können sie bis zu 64 elektrische Signale gleichzeitig im Herzen aufnehmen. Die Muster der Ausbreitung der elektrischen Depolarisation sind manchmal recht einfach, vergleichbar mit ebenen Wellen. Aber bei Patienten mit schweren Vorhofarrhythmien können sie auch sehr komplex sein: scharfe Kurven um Linien, welche die Erregungsausbreitung blockieren, ektope Zentren, Durchbrüche, Rückkopplungs-Kreise, Rotoren, fraktionierte Signale und chaotische Muster werden oft beobachtet. Mit Methoden der Biosignalverarbeitung können wir die Kardiologen dabei unterstützen, die Signale richtig zu klassifizieren und diagnostisch wichtige Informationen zu extrahieren. Computer-Modelle der Elektrophysiologie des menschlichen Herzens können dazu beitragen, neue und bessere Algorithmen für die Datenanalyse zu entwerfen und zu testen, da bei Computersimulationen die zugrundeliegende ,,Wahrheit“ bekannt ist.

Keywords: Biosignal analysis; electrocardiogram; atrial fibrillation; computer modelling

Schlagwörter: Biosignalanalyse; Elektrokardiogramm; Vorhofflimmern; Computer-Modellierung

About the article

Olaf Dössel

Olaf Dössel studied Physics at the University of Kiel, Germany, and made his PhD there. Then he became scientist and later head of the research group “Measurement Techniques” at Philips Research Laboratories in Hamburg. Since 1996 he is full Professor at Karlsruhe Institute of Technology (Technical University of Karlsruhe) and head of the Institute of Biomedical Engineering. His research interests are the electric signals of the heart, computer modelling of the heart, numerical field calculation in the human body and medical imaging.

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany

Gustavo Lenis

Gustavo Lenis studied Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Technical University of Karlsruhe). Now he is employed as a scientist at the Institute of Biomedical Engineering and PhD candidate. His main research interest is biosignal analysis of the electrocardiogram (ECG).

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany

Axel Loewe

Axel Loewe studied Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Technical University of Karlsruhe). Now he is employed as a scientist at the Institute of Biomedical Engineering and PhD candidate. His main research interest is computer modelling of the heart.

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany

Markus Rottmann

Markus Rottmann studied Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Technical University of Karlsruhe). Now he is employed as a scientist at the Institute of Biomedical Engineering and PhD candidate. His main research interest is biosignal analysis of electrogram and new catheter design.

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany

Gunnar Seemann

Gunnar Seemann studied Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Technical University of Karlsruhe) and made his PhD in 2005. Then he was employed as a chief scientist and lecturer at the Institute of Biomedical Engineering. His main research interest is computer modelling of the heart, starting with the ion-channels in the myocardial cells and ending at the electrogram, ECG and elastomechanical contraction of the heart.

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany

Tobias Oesterlein

Tobias Oesterlein studied Electrical Engineering and Information Technology at Karlsruhe Institute of Technology (Technical University of Karlsruhe). Now he is employed as a scientist at the Institute of Biomedical Engineering and PhD candidate. His main research interest is biosignal analysis of intracardiac multichannel electrogram data.

Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), Fritz-Haber-Weg 1, 76131 Karlsruhe, Germany


Revised: 2015-12-17

Accepted: 2015-12-18

Received: 2015-12-08

Published Online: 2016-02-09

Published in Print: 2016-02-28


Citation Information: tm - Technisches Messen, Volume 83, Issue 2, Pages 102–111, ISSN (Online) 2196-7113, ISSN (Print) 0171-8096, DOI: https://doi.org/10.1515/teme-2015-0122.

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