21st Symposium on Signal Processing Images and Artificial Vision STSIVA 2016
Issue Date:
30-Aug-2016
metadata.dc.ucuenca.embargoend:
1-Jan-2022
metadata.dc.source:
2016 21st Symposium on Signal Processing, Images and Artificial Vision, STSIVA 2016
metadata.dc.identifier.doi:
10.1109/STSIVA.2016.7743303
Publisher:
INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC.
metadata.dc.description.city:
Bucaramanga
metadata.dc.type:
Article
Abstract:
Heart rate variability (HRV) is a simple, non-invasive measure that can be used to quantify autonomic nervous system modulation. This method has been used to detect alterations of autonomic cardiovascular regulation in diabetes and metabolic syndrome (MetS). MetS is characterized by the clustering of glucose intolerance, central obesity, dyslipidemia, and hypertension. This study analyze the HRV using nonlinear methods, in three study groups: 15 subjects with MetS, 10 subjects for control group (C), 15 subjects athletes (D), belonging to a data base with electrocardiographic signals during the test oral glucose tolerance (OGTT). In order to characterize the study groups, two analyzes were performed, one statistical to find significant differences, and a simple correspondence analysis. In the obtained results, significant differences were observed (p < 0.05-Wilcoxon) between MetS and C groups at the baseline phase in the index average descriptor de Poincaré (SD2) (76.368 ± 26.511ms versus 102.546 ± 35.706ms) and entropy approximate (ApEn) (1.220 ± 0.089 versus 1.307 ± 0.116). The simple correspondence took into account two components representing 59.19% of the total variance, and these components suggests that the descriptor de Poincare (SD1) and correlation dimension (D2) parameters can discriminate between groups. The results suggest that nonlinear parameters SD1, SD2, ApEn and D2, show that the heart rate dynamics and the regularity of the HRV are affected in subjects with MetS.
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