Among non-invasive techniques, heart rate variability (HRV) analysis has become widely used for assessing the balance of the autonomic nervous system. Research in this area has not stopped and alternative tools for the study and interpretation of HRV, are still being proposed. Nevertheless, frequency-domain analysis of HRV is controversial when the heartbeat sequence is non-stationary. The Hilbert-Huang Transform (HHT) is a relative new technique for timefrequency analyses of non-linear and non-stationary signals. The main purpose of this work is to investigate the influence of time series´ length and noise in HRV from synthetic signals, using HHT and to compare it with Welch method. Synthetic heartbeat time series with different sizes and levels of signal to noise ratio (SNR) were investigated. Results shows i) sequence´s length did not affect the estimation of HRV spectral parameter, ii) favorable performance for HHT for different SNR. Additionally, HHT can be applied to non-stationary signals from nonlinear systems and it will be useful to HRV analysis to interpret autonomic activity when acute and transient phenomena are assessed.
This article presents a study of ventricular repolarization in diabetic and metabolic syndrome subjects. The corrected QT interval (QTc) was estimated using four correction formulas commonly employed in the literature: Bazett, Fridericia, Framingham and Hodges. After extracting the Q, R and T waves from the electrocardiogram of 52 subjects (19 diabetic, 15 with metabolic syndrome and 18 control), using a wavelet-based approach, the RR interval and QT interval were determined. Then, QTc interval was computed using the formulas previously mentioned. Additionally, laboratory test (fasting glucose, cholesterol, triglycerides) were also evaluated. Results show that metabolic syndrome subjects have normal QTc. However, a longer QTc in this population may be a sign of future complication. The corrected QT interval by Fridericia's formula seems to be the most appropriated for metabolic syndrome subjects (low correlation coefficient between RR and QTc). Significant differences were obtained in the blood glucose and triglyceride levels, principally due to the abnormal sugar metabolization of metabolic syndrome and diabetic subjects. Further studies are focused on the acquisition of a larger database of metabolic syndrome and diabetics subjects and the repetition of this study using other populations, like high performance athletes.