Measuring body temperature time series regularity using approximate entropy and sample entropy

Author

Cuesta-Frau, D. ; Miró-Martínez, P. ; Oltra-Crespo, S. ; Varela-Entrecanales, M. ; Aboy, M. ; Novak, D. ; Austin, D.

Author_Institution

Technol. Inst. of Inf., Polytech. Univ. of Valencia, Alcoi, Spain

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

3461

Lastpage

3464

Abstract

Approximate Entropy (ApEn) and Sample Entropy (SampEn) have proven to be a valuable analyzing tool for a number of physiological signals. However, the characterization of these metrics is still lacking. We applied ApEn and SampEn to body temperature time series recorded from patients in critical state. This study was aimed at finding the optimal analytical configuration to best distinguish between survivor and non-survivor records, and at gaining additional insight into the characterization of such tools. A statistical analysis of the results was conducted to support the parameter and metric selection criteria for this type of physiological signal.

Keywords

biothermics; entropy; statistical analysis; temperature measurement; time series; ApEn; SampEn; approximate entropy; body temperature measurement; physiological signals; sample entropy; statistical analysis; time series; Algorithms; Artificial Intelligence; Body Temperature; Computer Simulation; Computers; Entropy; Humans; Intensive Care; Intensive Care Units; Models, Statistical; Monitoring, Physiologic; Pattern Recognition, Automated; Signal Processing, Computer-Assisted; Software; Treatment Outcome;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5334602

Filename

5334602