# Deep Learning and Big Data in Healthcare: A Double Review for Critical Beginners
## 6 Applications in ECG Processing
### ECG Fundamentals and Databases
This database consists of arrhythmias and normal sinus rhythm, and it includes 154 ECG recordings from real patients of 3-h length each. The last 30 min of each recording have been labeled by experts as arrhythmia-free or belonging to one among seven types of arrhythmias or non-normal beats [185]. The _Stress Detection for Automobile Drivers Database_ (DriveDB) was created with the purpose of investigating the feasibility of automated recognition of stress, and other physiological parameters apart from ECG were recorded on it and included (specifically, electromyogram and skin conductivity) from nine subjects in 18 driving sessions [186; 187]. The _ECG-ID Database_ was specifically developed for its use in biometrics, and up to 310 recordings of 20-s ECG were obtained from 90 people for this purpose [186; 188]. Especially relevant is also the _European ST-T Database_, which is intended for the evaluation of algorithms for analysis of ST and T-wave changes, and it consists of 90 two-hour excerpts of recordings from 79 subjects. It contains several informative abnormalities, such as myocardial ischemia, hypertension, ventricular dyskinesia, and medication effects [186; 189]. The _Long-Term ST Database_ includes 86 ECG recordings from 80 subjects, between 21 and 24 h in duration each one, with a variety of events of STsegment changes, including ischemic ST episodes, axis-related non-ischemic ST episodes, episodes of slow ST level drift, and episodes containing mixtures of these phenomena [186; 190]. Also very widely used are the _MIT-BIH Arrhythmia Database_ and the _MIT-BIH Normal Sinus Rhythm Database_, both in research or in equipment certification in the industry. The former is one of the most used as standard test material for evaluation of arrhythmia detectors, and it is composed of 48 half-hour excerpts of two-channel ambulatory ECG recordings obtained from 47 subjects [186; 191]. The latter is composed by 18 long-term ECG recordings belonging to the former _MIT-BIH Arrhythmia Database_ from subjects without any arrhythmia or other abnormalities [186; 192]. The _PTB Diagnostic ECG Database_ contains 549 recordings from 290 healthy and unhealthy subjects (in various cardiac conditions) with one to five recordings per subject [186; 193], whereas the _QT Database_ is a collection of 105 15-min recording extracts from public databases, with the specific objective of aiding the development of automatic methods of measurement of QT waveforms [186; 194]. Also relevant is the _UofT ECG Database_ (UofTDB), also specifically created for ECG-based biometrics, where the fingertips of1020 subjects were captured. A subset of these subjects were recorded for up to six sessions over a period of six months, with different postures (sit, stand, supine, and tripod) and exercise condition, each recording being between 2- and 5-min long [195]. Finally, a special mention has to be given to the _MIMIC Database_, which is a collection of multiparameter recordings of 72 Intensive Care Unit patients that includes signals and periodic measurements obtained from a bedside monitor, as well as clinical data obtained from the patient's medical record. The recordings vary in length, although almost all of them are at least 20 h, and many of them reach 40 h and even more. There are also several annotation sets available, which are associated among them and correspond to ECG beat labels, annotations for alarms related to changes in the patient's status, annotations related to changes in the functioning of the monitor, arterial blood pressure, pulmonary arterial pressure, central venous pressure, and fingertip plethysmograph annotations [186; 196]. Figure 2: Representation of the placement of the ten electrodes in the 12-lead ECG configuration and the limb leads (I, II, III, AVR, aVL, and aVF), intracardiac electrogram signals, and ECG signals with normal (sinus rhythm) and non-normal rhythms.