ECG classification via integration of adaptive beat segmentation and relative heart rate with deep learning networks
We propose a state-of-the-art deep learning approach for accurate electrocardiogram (ECG)
signal analysis, addressing both waveform delineation and beat type classification tasks. For …
signal analysis, addressing both waveform delineation and beat type classification tasks. For …
[HTML][HTML] Clinical performance of AED shock advisory system with integrated Analyze Whilst Compressing algorithm for analysis of the ECG rhythm during out-of …
JP Didon, I Jekova, B Frattini, S Ménétré, C Derkenne… - Resuscitation …, 2024 - Elsevier
Objective This study involving automated external defibrillators (AEDs) in early treatment of
refibrillation aims to evaluate the performance of a new shock advisory system (SAS) during …
refibrillation aims to evaluate the performance of a new shock advisory system (SAS) during …
“To shock or not to shock? This is no longer a question”… with the new AED technologies
E Roman-Pognuz, G Ristagno - Resuscitation, 2024 - resuscitationjournal.com
Minimally interrupted chest compression (CC) combined with prompt defibrillation is crucial
to ensure high-quality cardiopulmonary resuscitation (CPR) and improve survival after …
to ensure high-quality cardiopulmonary resuscitation (CPR) and improve survival after …
[PDF][PDF] Shock Advisory Neural Network for Continuous Detection of Ventricular Fibrillation, Organized Rhythm and Asystole during Cardiopulmonary Resuscitation
I Jekova, S Ménétré, T Stoyanov, JP Didon, V Krasteva - cinc.org
This study presents a shock-advisory system (SAS) for continuous rhythm analysis during
cardiopulmonary resuscitation (CPR) aiming to align with different resuscitation actions in …
cardiopulmonary resuscitation (CPR) aiming to align with different resuscitation actions in …