Gathering experimental data to test computer methods developed during a research is a hard work. Nowadays, some databases have been stored online that can be freely downloaded, however there is not a wide range of databases yet and not all pathologies are covered. Researchers with low resources are in need of more data they can consult for free. To cope with this we present an on-line portal containing a compilation of ECG databases recorded over the last two decades for research purposes. The first version of this portal contains four databases of ECG records: ischemic cardiopathy (72 patients, 3-lead ECG each), ischemic preconditioning (20 patients, 3-lead ECG each), diabetes (51 patients, 8-lead ECG each) and metabolic syndrome (25 subjects, 12-lead ECG each). In addition, one computer program and three routines are provided in order to correctly read the signals, and two digital filters along with two ECG waves detectors are provided for further processing. This portal will be constantly growing, other ECG databases and signal processing software will be uploaded. With this project, we give the scientific community a resource to avoid hours of data collection and to develop free software.

This paper focuses on the effect of a sudden increase of plasma glucose concentration in the cardiac autonomic modulation using time-domain and frequency-domain heart rate variability (HRV) measures. Plasma glucose and insulin levels, measured each 30 min during an oral glucose tolerance test, and \(\overline {\text {RR}}\) (mean of the RR interval), SDNN (standard deviation of normal-to-normal heartbeats), rMSSD (root-mean-square of successive differences between normal heartbeats), TP (total spectral power), LF and HF (power of the low- and high-frequency bands), LF norm and HF norm (LF and HF in normalized units), and LF/HF ratio of the HRV signal, obtained from 5-min-long ECG recordings during each phase of the test, were analyzed for subjects with the metabolic syndrome, marathon runners, and a control group. Results show that, after the glucose load, subjects with the metabolic syndrome experienced an increased sympathetic and decreased parasympathetic tone, which suggests an imbalance in cardiac autonomic modulation as a consequence of hyperglycemia and hyperinsulinemia. The significance of this study lies in the use of the ECG to assess the effects of a sudden increase in plasma glucose concentration on the cardiac autonomic modulation in subjects with different cardiovascular and metabolic conditions.

The diagnosis of low insulin sensitivity is commonly done through the HOMA-IR index, in which fasting insulin and glucose blood levels are evaluated. Insulin and blood glucose levels are used for insulin sensitivity assessment by surrogate methods (HOMA-IR, Matsuda, etc), but anthropometric measurements like body weight, height and waist circumference are not considered, even if these variables also are related to low insulin sensitivity and metabolic syndrome. In this study we evaluate the impact of anthropometric measurements on the HOMA-IR, Matsuda and Caumo indexes to estimate insulin sensitivity. Specifically, we compare insulin sensitivity indexes with and without the anthropometric measurements in their equations on three different groups: patients with metabolic syndrome, sedentaries and marathoners. Results show relationships between anthropometric variables and insulin sensitivity indexes. On the other hand, subjects are mapped differently for insulin sensitivity assessment when anthropometric variables are taken into account. In addition, subjects diagnosed with normal insulin sensitivity could be considered as having low insulin sensitivity when anthropometric variables are considered.