Number of the records: 1  

A new database with annotations of P waves in ECGs with various types of arrhythmias

  1. 1.
    0563515 - ÚPT 2023 RIV GB eng J - Journal Article
    Šaclová, L. - Němcová, A. - Smíšek, Radovan - Smítal, L. - Vítek, M. - Ronzhina, M.
    A new database with annotations of P waves in ECGs with various types of arrhythmias.
    Physiological Measurement. Roč. 43, č. 10 (2022), č. článku 10NT01. ISSN 0967-3334. E-ISSN 1361-6579
    Institutional support: RVO:68081731
    Keywords : annotation of P wave * ECG * ECG database * ECG pathology
    OECD category: Medical engineering
    Impact factor: 3.2, year: 2022
    Method of publishing: Limited access
    https://iopscience.iop.org/article/10.1088/1361-6579/ac944e

    Objective.The aim of this study is to create a database for the development, evaluation and objective comparison of algorithms for P wave detection in ECG signals.BrnoUniversity ofTechnology ECG SignalDatabase with Annotations ofP-Wave (BUT PDB) is an ECG signal database with marked peaks of P waves annotated by ECG experts. Currently, there are only a few databases of pathological ECG signals with P-wave annotations, and some are incorrect.Approach.The pathological ECG signals used in this work were selected from three existing databases of ECG signals: MIT-BIH Arrhythmia Database, MIT-BIH Supraventricular Arrhythmia Database and Long Term AF Database. The P-wave positions were manually annotated by two ECG experts in all selected signals.Main results.The final BUT PDB composed of selected signals consists of 50 two-minute, two-lead pathological ECG signal records with annotated P waves. Each record also contains a description of the diagnosis (pathology) present in the selected part of the record and information about positions and types of QRS complexes.Significance.The BUT PDB is created for developing new, more accurate and robust methods for P wave detection. These algorithms will be used in medical practice and will help cardiologists to evaluate ECG records, establish diagnoses and save time.
    Permanent Link: https://hdl.handle.net/11104/0335462

     
     
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.