Authors:
O. Barquero-Pérez
1
;
R. Goya-Esteban
1
;
E. Sarabia-Cachadiña
2
and
J. Naranjo-Orellana
3
Affiliations:
1
Dept. Signal Theory and Communications, Universidad Rey Juan Carlos, Fuenlabrada, Madrid, Spain
;
2
Centro de Estudios Universitarios Cardenal Spínola CEU, Sevilla, Spain
;
3
Departamento Deporte e Informática, Universidad Pablo de Olavide, Sevilla, Spain
Keyword(s):
Autonomic Nervous Systems, Heart Rate Variability, Generalized Multiscale Entropy, Peripheral Arterial Disease.
Abstract:
Peripheral Arterial Disease (PAD) is a chronic condition that significantly impacts autonomic balance, as reflected in Heart Rate Variability (HRV). However, the characterization of autonomic balance in PAD patients using HRV is still unclear. Generalized Multiscale Entropy (GMSE) is a nonlinear method capable of characterizing the complexity of HRV across multiple time scales, offering a more nuanced understanding of autonomic dysfunction in PAD patients. 14 healthy male subjects (60±5 years) and 14 male intermittent claudication patients (64±6 years) underwent 10 minutes of ECG recording from which RR interval time series were obtained. This study provides a comparative analysis of different GMSE methods for constructing coarse-grained time series, specifically using the mean, mean absolute deviation (MAD), standard deviation (σ), and variance (σ2) approaches. By applying these methods, we investigate their efficacy in differentiating between healthy individuals and PAD patients. O
ur results demonstrate that the variance coarse-grained method offers superior discriminatory power, revealing statistically significant differences. These findings suggest that the variance-based GMSE method is the most effective approach for assessing autonomic imbalance in PAD patients, with potential applications in improving diagnostic tools and treatment strategies.
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