LUDB: A New Open-Access Validation Tool for Electrocardiogram Delineation Algorithms

Alena I Kalyakulina,Konstantin A Kosonogov,Alexander V Nikolskiy,Viktor A Moskalenko,Mikhail V Ivanchenko,Grigory V Osipov,Igor I Yusipov,Nikolai Yu Zolotykh

doi:10.1109/access.2020.3029211

Alena I Kalyakulina, Konstantin A Kosonogov + Show 6 more

Open Access

https://doi.org/10.1109/access.2020.3029211

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Abstract

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 morfologies. 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.

Highlights

Recording the electrical activity of heart, or electrocardiography, is one of the basic medical diagnostic means for assessing cardiac activity, in particular, determining the heart rate and rhythm disturbances
For both Lobachevsky University Database (LUDB) and QTDB, the sensitivity values for the onsets and peaks of the P, QRS and T waves are above 97%, and the standard deviation σ is almost within the limits set by the standard [35]: it must be at most 2σCSE
The more challenging task of detecting P and T waves is performed almost well by all methods on QTDB, but the method by Kalyakulina et al substantially outperforms ecg-kit for LUDB

Summary

INTRODUCTION

Recording the electrical activity of heart, or electrocardiography, is one of the basic medical diagnostic means for assessing cardiac activity, in particular, determining the heart rate and rhythm disturbances. Validating delineation algorithms requires standardized datasets with complexes and waves that are manually annotated by specialists. The boundaries of P, QRS and T complexes at each lead are manually annotated by cardiologists for all 200 records, and each subject is supplemented with noticed abnormalities (same as in the other studies, we skip U-wave due to its small amplitude and noise issues). Delineation of P-wave is viewed as the most complex task by both the cardiologists and mathematicians [4], [30] The amplitude of this wave often compares to noise or flutter, so that a quality detection procedure has to FIGURE 6. The algorithm explores ECG signal from each lead separately It selects the best candidates for the corresponding wave, determines its peak and boundaries. When the complexes are missed in less than one third of leads, their delineation is restored by the multi-lead analysis, as exemplified in Fig. 10, and a corresponding morphological anomaly is noted down

ALGORITHM VALIDATION

CONCLUSION