Database of Intracardiac ECG Recordings in Paediatric Patients

Richard Ředina1, Jakub Hejc2, David Pospisil3, Marina Ronzhina1, Petra Novotna4, Zdenek Starek5
1Brno University of Technology, 2International Clinical Research Center, St. Anne’s University Hospital, Brno, Czech Republic, 3Department of Internal Cardiology Medicine, The University Hospital Brno, 4Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, 5International Clinical Research Center, St. Anne's University Hospital, Brno, Czech Republic


Abstract

Classical ECG analysis has brought a breakthrough in the diagnosis of heart diseases in the last century. With improvements in technology, doctors are now able to read ECGs using catheters placed directly in the heart. Signals obtained in this way may herald a further shift in diagnostic capabilities. Cardiac arrhythmias are still a burden for patients. Their early detection or even prediction can speed up treatment and lead to a general improvement in the quality of patients’ life. For this task, intracardiac ECG records can be a valuable source of information The recordings were obtained during electrophysiological operations on paediatric patients with arrhythmias. 12-lead surface ECGs and 5-lead iEGc were recorded when the catheter was placed in the coronary sinus. The iECG recordings were acquired using a St. Jude WorkMate 4.3 EP system (2000 Hz, 72 nV/LSB) on a 10-polar catheter. Annotations capturing atrial activity were manually created by the experienced electrophysiologists. The database consists of a total of 326 partial records, from one hundred patients. The average age of the patients was 14 years (12 – 17) and 48 of them were females. The average length of one record was 8.5 seconds (6.4 – 12.2). The database contains a global annotation for each record that lists the pathologies found in the record, followed by local annotations that indicate atrial activity. A large proportion of the records (n = 191) contained only sinus rhythm. Ventricular preexcitation (n = 58) and atrial premature beat (n = 47) were the most common pathologies. We believe, that the unique database presented in the paper will create a room for further advanced analysis of heart rhythm.In future research, the database can be used to develop the algorithms for signal pre-processing and removing the noise, atrial/ventricular activity segmentation, or classification of selected arrhythmias.