Complexity analysis of 24 hours heart rate variability time series

We propose to study the heart rate variability (HRV) time series complexity by computing the Lempel Ziv complexity measure. LZ is sensitive to the rate of pattern recurrences in a time series. Analysis considers 24 h HRV time series of healthy subjects and patients with cardiovascular diseases. Anal...

Full description

Saved in:
Bibliographic Details
Published in:Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) Vol. 2; pp. 3956 - 3959
Main Authors: Ferrario, M., Signorini, M.G., Cerutti, S.
Format: Conference Proceeding Journal Article
Language:English
Published: United States IEEE 2004
Subjects:
Algorithmic complexity
Analytical models
Cardiovascular diseases
Computational modeling
Heart rate variability
Lempel Ziv complexity
Pathology
Probability
Signal analysis
Signal processing
Time measurement
Time series analysis
ISBN:9780780384392, 0780384393
ISSN:1557-170X
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We propose to study the heart rate variability (HRV) time series complexity by computing the Lempel Ziv complexity measure. LZ is sensitive to the rate of pattern recurrences in a time series. Analysis considers 24 h HRV time series of healthy subjects and patients with cardiovascular diseases. Analysis with simulated signals show the LZ measure can vary depending on the adopted coding process. The binary coding, proposed in this work, is sensitive to the different dynamical systems generating the time series, as the ternary coding is sensitive to the presence of stationary states, i.e. a consecutive repetition of the same RR interval value. LZ method reliably differentiates healthy vs. disease group. Further clinical investigations on the LZ complexity and on its relationship to the risk of sudden death, can supply new diagnostic indications.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISBN:9780780384392
0780384393
ISSN:1557-170X
DOI:10.1109/IEMBS.2004.1404105