Stress ECG and Laboratory Database for the Assessment of Diabetic Cardiovascular Autonomic Neuropathy

Development of a diabetic patient database in order to study cardiovascular autonomic neuropathy (CAN) using as a primary source, stress ECG is presented. The selected platform (ecgML) allows user-friendly environment to analyze and interpret graphs, signals and data. It also allows the ability to perform annotations and reports done by users from different fields. In order to feed the database, the input data is codify using MatLab. The database is composed by two populations: 1) Type 2 Diabetes mellitus group and 2) a control group with no medical history of cardiovascular disease. At the present, there are 62 records available from these two groups. The database also contains laboratory parameters, concurrent medical diagnoses reports verified by cardiologists and other clinicians, automatic annotations for each beat and trend series from parameters extracted from the ECG signals such as RR intervals and ST segment measurements. All this information will become very useful for CAN investigations.