Study of Diabetic Cardiovascular Autonomic Neuropathy Using the Hilbert-Huang Transform

Estudio de la Neuropatía Autonómica Cardiovascular Diabética Empleando la Transformada de Hilbert-Huang

Abstract

Diabetes mellitus is a chronic disease that affects more than 366 million people worldwide. Among its complications is Cardiovascular Autonomic Neuropathy (CAP), causing severe injuries to the Autonomous Nervous System (ANS), responsible for cardiovascular control and respiratory dynamics. The deterioration of the ANS can be assessed from the study of signals such as Heart Rate Variability (HRV) and QT interval variability (QTV), temporal sequences obtained from the Electrocardiogram (ECG). In this work, a five-stage stress test (PE) ECG was used under the modified Bruce protocol (1.-rest, 2.-moderate effort, 3.-maximum effort, 4.-early recovery and 5-recovery). , applied to diabetic patients with cardiac complications (GD) and healthy subjects (CG). Two methods were proposed to evaluate the SNA: (i) frequency analysis: measuring the energy by frequency bands using the Hilbert-Huang Transform (HHT) and the Autoregressive (AR) model in short duration segments (150 samples) to each stage of the PE and (ii) time analysis: characterizing Stationary Segments (SE) obtained from the study sequences by applying the Bernaola-Galván algorithm. The spectral analysis of HRV reported a significant difference (p<0.05) in segment two of the PE, which could contribute to the diagnosis of the disease. In time, the extraction of SE from HRV and VQT showed that more than one SE can be obtained in each stage of the PE as well as no SE can be obtained in any of them. Characterizing the ES of HRV and VQT showed that the number of segments found and their average duration time is greater for the DG than for the CG, which may be due to the deterioration caused by diabetes on the ANS nerves.