Publikationen in Zusammenarbeit mit Forschern von Universidad del País Vasco/Euskal Herriko Unibertsitatea (16)

2021

  1. End-tidal carbon dioxide (ETCO2) and ventricular fibrillation amplitude spectral area (AMSA) for shock outcome prediction in out-of-hospital cardiac arrest. Are they two sides of the same coin?

    Resuscitation, Vol. 160, pp. 142-149

2020

  1. Shock Decision Algorithms for Automated External Defibrillators Based on Convolutional Networks

    IEEE Access, Vol. 8, pp. 154746-154758

2019

  1. Abstract 124: A Machine-Learning Based Shock Advice Algorithm for Reliable Rhythm Diagnosis During Out-Of-Hospital Cardiac Arrest

    Circulation, Vol. 140, Núm. Suppl_2

  2. Algoritmo basado en redes neuronales recurrentes para la detección de ritmos desfibrilables

    Hacia una salud personalizada y universal. XXXVII Congreso Anual de la Sociedad Española de Ingeniería Biomédica: Actas del Congreso CASEIB 2019

  3. Value of capnography to predict defibrillation success in out-of-hospital cardiac arrest

    Resuscitation, Vol. 138, pp. 74-81

2018

  1. Fuzzy and sample entropies as predictors of patient survival using short ventricular fibrillation recordings during out of hospital cardiac arrest

    Entropy, Vol. 20, Núm. 8

2017

  1. Predicción del éxito de la desfibrilación mediante entropía difusa en términos de recuperación de ritmo cardíaco regular, pulso y supervivencia

    XXXV Congreso anual de la Sociedad Española de Ingeniería Biomédica: Libro de actas

2016

  1. Application of entropy-based features to predict defibrillation outcome in cardiac arrest

    Entropy, Vol. 18, Núm. 9

  2. Circulation detection using the electrocardiogram and the thoracic impedance acquired by defibrillation pads

    Resuscitation, Vol. 99, pp. 56-62

  3. Nonlinear energy operators for defibrillation shock outcome prediction

    Computing in Cardiology

2015

  1. A method to measure ventilation rate during cardiopulmonary resuscitation using the capnogram

    Computing in Cardiology

  2. Alternatives to Estimate the Compression Depth from the Acceleration Signal during Cardiopulmonary Resuscitation

    Computing in Cardiology

  3. Difference in survival from pre-hospital cardiac arrest between cities and villages in the Basque Autonomous Community

    Resuscitation, Vol. 96, pp. 114

  4. Estimation of the chest compression depth using an accelerometer positioned on the rescuer's back of the hand or forearm

    Resuscitation, Vol. 96, pp. 16

  5. Feasibility of compression depth estimation from the acceleration signal during cardiopulmonary resuscitation in long-distance trains

    Computing in Cardiology

  6. Sample entropy as a shock outcome predictor during basis life support

    Computing in Cardiology