• An automatic system for the comprehensive retrospective analysis of cardiac rhythms in resuscitation episodes 

      Rad, Ali Bahrami; Eftestøl, Trygve Christian; Irusta, Unai; Kvaløy, Jan Terje; Wik, Lars; Kramer-Johansen, Jo; Katsaggelos, Aggelos K.; Engan, Kjersti (Journal article; Peer reviewed, 2018)
      AIM: An automatic resuscitation rhythm annotator (ARA) would facilitate and enhance retrospective analysis of resuscitation data, contributing to a better understanding of the interplay between therapy and patient response. ...
    • Automatic Cardiac Rhythm Classification With Concurrent Manual Chest Compressions 

      Isasi, Iraia; Irusta, Unai; Rad, Ali Bahrami; Aramendi, Elisabete; Zabihi, Morteza; Eftestøl, Trygve Christian; Kramer-Johansen, Jo; Wik, Lars (Journal article; Peer reviewed, 2019-08)
      Electrocardiogram (EKG) based classification of out-of-hospital cardiac arrest (OHCA) rhythms is important to guide treatment and to retrospectively elucidate the effects of therapy on patient response. OHCA rhythms are ...
    • Machine learning techniques for the detection of shockable rhythms in automated external defibrillators 

      Figuera, Carlos; Irusta, Unai; Morgado, Eduardo; Aramendi, Elisabete; Ayala, Unai; Wik, Lars; Kramer-Johansen, Jo; Eftestøl, Trygve; Alonso-Atienza, Felipe (Journal article; Peer reviewed, 2016-07)
      Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for ...
    • Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia 

      Picon, Artzai; Irusta, Unai; Alvarez-Gila, Aitor; Aramendi, Elisabete; Alonso-Atienza, Felipe; Figuera, Carlos; Ayala, Unai; Garrote, Estibaliz; Wik, Lars; Kramer-Johansen, Jo; Eftestøl, Trygve Christian (Journal article; Peer reviewed, 2019-05)
      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 ...
    • Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks 

      Isasi, Iraia; Irusta, Unai; Aramendi, Elisabete; Eftestøl, Trygve Christian; Kramer-Johansen, Jo; Wik, Lars (Peer reviewed; Journal article, 2020-05)
      Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The objective of this study was to design ...