English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Classifying cardiac biosignals using ordinal pattern statistics and symbolic dynamics

Parlitz, U., Berg, S., Luther, S., Schirdewan, A., Kurths, J., & Wessel, N. (2012). Classifying cardiac biosignals using ordinal pattern statistics and symbolic dynamics. Computers in Biology and Medicine (Elmsford, NY), 42(3), 319-327. doi:10.1016/j.compbiomed.2011.03.017.

Item is

Files

show Files

Locators

show
hide
Locator:
Link (Any fulltext)
Description:
-

Creators

show
hide
 Creators:
Parlitz, Ulrich1, Author              
Berg, Sebastian1, Author              
Luther, Stefan1, Author              
Schirdewan, A., Author
Kurths, J., Author
Wessel, N., Author
Affiliations:
1Research Group Biomedical Physics, Max Planck Institute for Dynamics and Self-Organization, Max Planck Society, ou_2063288              

Content

show
hide
Free keywords: ECG classification, Heart rate variability, Ordinal pattern statistics, Permutation index, Symbolic dynamics
 Abstract: The performance of (bio-)signal classification strongly depends on the choice of suitable features (also called parameters or biomarkers). In this article we evaluate the discriminative power of ordinal pattern statistics and symbolic dynamics in comparison with established heart rate variability parameters applied to beat-to-beat intervals. As an illustrative example we distinguish patients suffering from congestive heart failure from a (healthy) control group using beat-to-beat time series. We assess the discriminative power of individual features as well as pairs of features. These comparisons show that ordinal patterns sampled with an additional time lag are promising features for efficient classification.

Details

show
hide
Language(s): eng - English
 Dates: 2012-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1016/j.compbiomed.2011.03.017
BibTex Citekey: parlitz_classifying_2012
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Computers in Biology and Medicine (Elmsford, NY)
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York : Pergamon
Pages: - Volume / Issue: 42 (3) Sequence Number: - Start / End Page: 319 - 327 Identifier: ISSN: 0010-4825
CoNE: https://pure.mpg.de/cone/journals/resource/954925392327