Current diabetes reviews [Curr Diabetes Rev] 2015; Vol. 11 (2), pp. 102-6.
Heart Rate, Humans, Jervell-Lange Nielsen Syndrome, Predictive Value of Tests, Risk Factors, Arrhythmias, Cardiac diagnosis, Death, Sudden, Cardiac epidemiology, Diabetes Mellitus physiopathology, and Electrocardiography
Prevalence of diabetes mellitus (DM) is progressively increasing, contributing to a parallel increase in cardiovascular morbidity and mortality, and more than doubling the incidence of sudden cardiac death (SCD). Certain electrocardiographic (ECG) characteristics, such as alternans of the T wave (TWA), heart rate variability (HRV) and dispersion of the QT interval, have been found to be predictive of the risk of SCD. This review focuses on ECG changes that could be found in diabetics and their potential implication for SCD risk.
BioMed research international [Biomed Res Int] 2015; Vol. 2015, pp. 135676. Date of Electronic Publication: 2015 Oct 19.
Aged, Aged, 80 and over, Female, Heart Diseases diagnosis, Humans, Male, Reproducibility of Results, Sensitivity and Specificity, Electrocardiography methods, Health Status, Heart Diseases physiopathology, Heart Rate, Pattern Recognition, Automated methods, and Records
Traditional means for identity validation (PIN codes, passwords), and physiological and behavioral biometric characteristics (fingerprint, iris, and speech) are susceptible to hacker attacks and/or falsification. This paper presents a method for person verification/identification based on correlation of present-to-previous limb ECG leads: I (r I), II (r II), calculated from them first principal ECG component (r PCA), linear and nonlinear combinations between r I, r II, and r PCA. For the verification task, the one-to-one scenario is applied and threshold values for r I, r II, and r PCA and their combinations are derived. The identification task supposes one-to-many scenario and the tested subject is identified according to the maximal correlation with a previously recorded ECG in a database. The population based ECG-ILSA database of 540 patients (147 healthy subjects, 175 patients with cardiac diseases, and 218 with hypertension) has been considered. In addition a common reference PTB dataset (14 healthy individuals) with short time interval between the two acquisitions has been taken into account. The results on ECG-ILSA database were satisfactory with healthy people, and there was not a significant decrease in nonhealthy patients, demonstrating the robustness of the proposed method. With PTB database, the method provides an identification accuracy of 92.9% and a verification sensitivity and specificity of 100% and 89.9%.
Aging clinical and experimental research [Aging Clin Exp Res] 2004 Oct; Vol. 16 (5), pp. 342-8.
Aged, Aged, 80 and over, Case-Control Studies, Cross-Sectional Studies, Databases, Factual, Electrophysiology, Female, Heart Failure physiopathology, Humans, Hypertension physiopathology, Italy, Male, Aging physiology, and Electrocardiography statistics numerical data
Background and Aims: In the last few years there has been active interest in the study of QT interval dispersion (QT-d) calculated from the 12-lead ECG, as a non-invasive method of investigating the homogeneity of ventricular recovery time. The aim of this study was to evaluate QT interval dispersion, analyzing in particular gender and age relationships. Discussion of its electrophysiologic and clinic meaning is still open; moreover, the method must be standardized and normal values should be clearly defined. Methods: The two common indices, range and standard deviation of QT, were taken into account. The study sample is part of the population-based Italian Longitudinal Study on Aging (ILSA) with individuals older than 64 years. Three groups were identified by clinical data: 256 healthy subjects, 98 patients with only cardiac diseases, and 472 patients with only hypertension. Results: Age (< 75 and > 75) and gender subgroups were considered, showing that age and gender influence the QT-d differently in the three groups. QT-d indices were influenced in the healthy group by gender (p < 0.001), in the cardiopathy group by age (p < 0.001), and in the hypertension group by age (p < 0.02) and gender (p < 0.01). Then the two gender groups were considered separately. In the female group, QT-d increased significantly with age only in the healthy group (p < 0.02), whereas in the male group it increased significantly in the cardiopathy and hypertension groups (p < 0.01). Conclusions: The two QT-d indices behaved in a very similar way in all the comparisons. In older people, gender and age influenced the three clinical selected groups differently. However, it was shown that is not possible to indicate a clear, definite threshold value classifying with accuracy a single subject in the clinical groups; and a clear-cut, direct clinic application is still doubtful.
In this study, we introduce and discuss a development of a highly interactive and user-friendly environment for an ECG signal analysis. The underlying neural architecture being a crux of this environment comes in the form of a self-organizing map. This map helps discover a structure in a set of ECG patterns and visualize a topology of the data. The role of the designer is to choose from some already visualized regions of the self-organizing map characterized by a significant level of data homogeneity and substantial difference from other regions. In the sequel, the regions are described by means of information granules-fuzzy sets that are essential in the characterization of the main relationships existing in the ECG data. The study introduces an original method of constructing membership functions that incorporates class membership as an important factor affecting changes in membership grades. The study includes a comprehensive descriptive modeling of highly dimensional ECG data.