Beiträge in Tagungsbänden:
M. Bachler, M. Hörtenhuber, C. Mayer, A. Holzinger, S. Wassertheurer:
"Entropy-Based Data Mining on the Example of Cardiac Arrhythmia Suppression";
in: "The 2014 International Conference on Brain Informatics and Health",
D. Slezak, A. Tan, J. F. Peters, L. Schwabe (Hrg.);
herausgegeben von: The University of Warsaw;
Springer International Publishing Switzerland,
Zürich,
2014,
ISBN: 978-3-319-09890-6,
S. 574
- 585.
Kurzfassung englisch:
Abstract. Heart rate variability (HRV) is the variation of the time interval between consecutive heartbeats and depends on the extrinsic regulation of the heart rate. It can be quantified using nonlinear methods such as entropy measures, which determine the irregularity of the time intervals.
In this work, approximate entropy (ApEn), sample entropy (SampEn),
fuzzy entropy (FuzzyEn) and fuzzy measure entropy (FuzzyMEn) were
used to assess the effects of three different cardiac arrhythmia suppressing drugs on the HRV after a myocardial infarction.
Schlagworte:
Data Mining, Entropy, Heart Rate Variability, Cardiac Arrhythmia Suppression.
"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)
http://dx.doi.org/10.1007/978-3-319-09891-3
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.