Zerrendatu honen arabera: egilea "Kramer-Johansen, Jo"
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An Accurate Shock Advise Algorithm for Use During Piston-Driven Chest Compressions
Ayala, Unai (IEEE, 2018)Mechanically delivered chest compressions induce artifacts in the ECG that can lead to an incorrect diagnosis of the shock advice algorithms implemented in the defibrillators. This forces the rescuer to stop cardiopulmonary ... -
Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators
Ayala, Unai (PLOS, 2016)Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survivalof out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrilla-tors (AED). AED algorithms for ... -
Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia
Ayala, Unai (2019)Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ... -
Removing piston-driven mechanical chest compression artefacts from the ECG
Ayala, Unai (CinC Computing In Cardiology, 2017)Piston-driven mechanical chest compression (CC) devices induce a quasi-periodic artefact in the ECG, making rhythm diagnosis unreliable. Data from 230 out-of-hospital cardiac arrest (OHCA) patients were collected in which ...
