DocumentCode :
1332634
Title :
Complexity of the short-term heart-rate variability
Author :
Valencia, Jose F., Jr. ; Vallverdú, Montserrat ; Schroeder, Rico ; Voss, Andreas, Jr. ; Vázquez, Rafael ; Bayés De Luna, Antonio ; Caminal, Pere, Jr.
Author_Institution :
Univ. Politec. de Catalunya, Barcelona, Spain
Volume :
28
Issue :
6
fYear :
2009
Firstpage :
72
Lastpage :
78
Abstract :
This work has proposed a methodology based on the concept of entropy rates to study the complexity of the short-term heart-rate variability (HRV) for improving risk stratification to predict sudden cardiac death (SCD) of patients with established ischemic-dilated cardiomyopathy (IDC). The short-term HRV was analyzed during daytime and nighttime by means of RR series. An entropy rate was calculated on the RR series, previously transformed to symbol sequences by means of an alphabet. A statistical analysis permitted to stratify high- and low-risk patients of suffering SCD, with a specificity (SP) of 95% and sensitivity (SE) of 83.3%. To get a better characterization of short-term HRV, the study has also considered the adjustment of the parameters involved in the proposed methodology. Finally, a statistical analysis was applied to recognize valid prognostic markers.
Keywords :
cardiovascular system; electrocardiography; entropy; medical signal processing; patient diagnosis; risk analysis; statistical analysis; RR series; coarse graining approach; complexity; entropy rates; ischemic-dilated cardiomyopathy; risk stratification; short-term heart-rate variability; statistical analysis; sudden cardiac death; symbol sequences; Cardiac disease; Cardiology; Cardiovascular diseases; Cardiovascular system; Entropy; Failure analysis; Heart rate variability; Medical treatment; Nonlinear dynamical systems; Statistical analysis; Aged; Algorithms; Cardiomyopathy, Dilated; Death, Sudden, Cardiac; Entropy; Heart Rate; Humans; Linear Models; Male; Middle Aged; Nonlinear Dynamics; Predictive Value of Tests; Prognosis; Risk Assessment; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Statistics, Nonparametric;
fLanguage :
English
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
Publisher :
ieee
ISSN :
0739-5175
Type :
jour
DOI :
10.1109/MEMB.2009.934621
Filename :
5335722
Link To Document :
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