  We report Lobachevsky University Database (LUDB) of ECG signals, an open tool
for validating ECG delineation algorithms, that is superior to the existing
publicly available data bases in several aspects. LUDB contains 200 recordings
of 10-second 12-lead electrocardiograms (ECG) from different subjects,
representative of a variety of signal morphologies. The boundaries and peaks of
QRS complexes and P and T waves are manually annotated by cardiologists for all
recordings and independently for each lead, and all records received an expert
classification by abnormalities. We present a case study for the recently
proposed wavelet-based algorithm and the broadly used ecg-kit tool, and
demonstrate the advantage of multi-lead ECG data analysis. LUDB contributes to
the diversity of public databases employed in developing and validating novel
ECG analysis algorithms, including the most advanced based on deep learning
neural networks.
