| Machine learning techniques for the detection of shockable rhythms in automated external defibrillators C Figuera, U Irusta, E Morgado, E Aramendi, U Ayala, L Wik, ... PloS one 11 (7), e0159654, 2016 | 97 | 2016 |
| Rhythm analysis during cardiopulmonary resuscitation: past, present, and future S Ruiz de Gauna, U Irusta, J Ruiz, U Ayala, E Aramendi, T Eftestøl BioMed research international 2014 (1), 386010, 2014 | 95 | 2014 |
| A method to remove CPR artefacts from human ECG using only the recorded ECG SR de Gauna, J Ruiz, U Irusta, E Aramendi, T Eftestøl, ... Resuscitation 76 (2), 271-278, 2008 | 90 | 2008 |
| A high-temporal resolution algorithm to discriminate shockable from nonshockable rhythms in adults and children U Irusta, J Ruiz, E Aramendi, SR De Gauna, U Ayala, E Alonso Resuscitation 83 (9), 1090-1097, 2012 | 81 | 2012 |
| Deep neural networks for ECG-based pulse detection during out-of-hospital cardiac arrest A Elola, E Aramendi, U Irusta, A Picón, E Alonso, P Owens, A Idris Entropy 21 (3), 305, 2019 | 80 | 2019 |
| Suppression of the cardiopulmonary resuscitation artefacts using the instantaneous chest compression rate extracted from the thoracic impedance E Aramendi, U Ayala, U Irusta, E Alonso, T Eftestøl, J Kramer-Johansen Resuscitation 83 (6), 692-698, 2012 | 75 | 2012 |
| Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia A Picon, U Irusta, A Álvarez-Gila, E Aramendi, F Alonso-Atienza, ... PloS one 14 (5), e0216756, 2019 | 70 | 2019 |
| Detection of ventricular fibrillation in the presence of cardiopulmonary resuscitation artefacts E Aramendi, SR de Gauna, U Irusta, J Ruiz, MF Arcocha, JM Ormaetxe Resuscitation 72 (1), 115-123, 2007 | 67 | 2007 |
| Reliability and accuracy of the thoracic impedance signal for measuring cardiopulmonary resuscitation quality metrics E Alonso, J Ruiz, E Aramendi, D González-Otero, SR de Gauna, U Ayala, ... Resuscitation 88, 28-34, 2015 | 59 | 2015 |
| Automatic detection of chest compressions for the assessment of CPR-quality parameters U Ayala, T Eftestøl, E Alonso, U Irusta, E Aramendi, S Wali, ... Resuscitation 85 (7), 957-963, 2014 | 59 | 2014 |
| Circulation detection using the electrocardiogram and the thoracic impedance acquired by defibrillation pads E Alonso, E Aramendi, M Daya, U Irusta, B Chicote, JK Russell, ... Resuscitation 99, 56-62, 2016 | 55 | 2016 |
| Application of entropy-based features to predict defibrillation outcome in cardiac arrest B Chicote, U Irusta, R Alcaraz, JJ Rieta, E Aramendi, I Isasi, D Alonso, ... Entropy 18 (9), 313, 2016 | 48 | 2016 |
| Evaluation of a new proposal for an arcing fault detection method based on wavelet packet analysis A Lazkano, J Ruiz, E Aramendi, LA Leturiondo European transactions on electrical power 14 (3), 161-174, 2004 | 48 | 2004 |
| ECG-based pulse detection during cardiac arrest using random forest classifier A Elola, E Aramendi, U Irusta, J Del Ser, E Alonso, M Daya Medical & biological engineering & computing 57, 453-462, 2019 | 43 | 2019 |
| Reliable extraction of the circulation component in the thoracic impedance measured by defibrillation pads J Ruiz, E Alonso, E Aramendi, J Kramer-Johansen, T Eftestøl, U Ayala, ... Resuscitation 84 (10), 1345-1352, 2013 | 40 | 2013 |
| Capnography: A support tool for the detection of return of spontaneous circulation in out-of-hospital cardiac arrest A Elola, E Aramendi, U Irusta, E Alonso, Y Lu, MP Chang, P Owens, ... Resuscitation 142, 153-161, 2019 | 39 | 2019 |
| Rhythm analysis during cardiopulmonary resuscitation using convolutional neural networks I Isasi, U Irusta, E Aramendi, T Eftestøl, J Kramer-Johansen, L Wik Entropy 22 (6), 595, 2020 | 38 | 2020 |
| Feasibility of the capnogram to monitor ventilation rate during cardiopulmonary resuscitation E Aramendi, A Elola, E Alonso, U Irusta, M Daya, JK Russell, P Hubner, ... Resuscitation 110, 162-168, 2017 | 38 | 2017 |
| High impedance arcing fault detector for three-wire power distribution networks A Lazkano, J Ruiz, LA Leturiondo, E Aramendi 2000 10th Mediterranean Electrotechnical Conference. Information Technology …, 2000 | 36 | 2000 |
| A machine learning shock decision algorithm for use during piston-driven chest compressions I Isasi, U Irusta, A Elola, E Aramendi, U Ayala, E Alonso, ... IEEE transactions on biomedical engineering 66 (6), 1752-1760, 2018 | 35 | 2018 |
