The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 minute of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation ...to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation.
TY - DATA
AU - Benini, Sergio
AU - Ivanović, Marija D.
AU - Savardi, Mattia
AU - Kršić, Jelena
AU - Hadžievski, Ljupčo
AU - Baronio, Fabio
PY - 2020
UR - https://vinar.vin.bg.ac.rs/handle/123456789/9549
AB - The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 minute of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation.
T2 - Mendeley Data
T1 - Cardially - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients
DO - 10.17632/wpr5nzyn2z.1
ER -
@misc{
author = "Benini, Sergio and Ivanović, Marija D. and Savardi, Mattia and Kršić, Jelena and Hadžievski, Ljupčo and Baronio, Fabio",
year = "2020",
abstract = "The provided database of 260 ECG signals was collected from patients with out-of-hospital cardiac arrest while treated by the emergency medical services. Each ECG signal contains a 9 second waveform showing ventricular fibrillation, followed by 1 minute of post-shock waveform. Patients’ ECGs are made available in multiple formats. All ECGs recorded during the prehospital treatment are provided in PFD files, after being anonymized, printed in paper, and scanned. For each ECG, the dataset also includes the whole digitized waveform (9 s pre- and 1 min post-shock each) and numerous features in temporal and frequency domain extracted from the 9 s episode immediately prior to the first defibrillation shock. Based on the shock outcome, each ECG file has been annotated by three expert cardiologists, - using majority decision -, as successful (56 cases), unsuccessful (195 cases), or indeterminable (9 cases). The code for preprocessing, for feature extraction, and for limiting the investigation to different temporal intervals before the shock is also provided. These data could be reused to design algorithms to predict shock outcome based on ventricular fibrillation analysis, with the goal to optimize the defibrillation strategy (immediate defibrillation versus cardiopulmonary resuscitation and/or drug administration) for enhancing resuscitation.",
journal = "Mendeley Data",
title = "Cardially - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients",
doi = "10.17632/wpr5nzyn2z.1"
}
Benini, S., Ivanović, M. D., Savardi, M., Kršić, J., Hadžievski, L.,& Baronio, F.. (2020). Cardially - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients. in Mendeley Data.
https://doi.org/10.17632/wpr5nzyn2z.1
Benini S, Ivanović MD, Savardi M, Kršić J, Hadžievski L, Baronio F. Cardially - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients. in Mendeley Data. 2020;.
doi:10.17632/wpr5nzyn2z.1 .
Benini, Sergio, Ivanović, Marija D., Savardi, Mattia, Kršić, Jelena, Hadžievski, Ljupčo, Baronio, Fabio, "Cardially - ECG waveform dataset for predicting defibrillation outcome in out-of-hospital cardiac arrested patients" in Mendeley Data (2020),
https://doi.org/10.17632/wpr5nzyn2z.1 . .
