These are the thesis that have been supervised or done by the members of the BioRes group.

Artificial intelligence tools for pulseless electrical activity characterization during cardiac arrest

Jon Urteaga, supervised by E Aramendi and A Elola, year 2024

Machine learning and signal processing algorithms for the analysis of ventilatioins and airway management in out-of-hospital cardiac arrest

Xabier Jaureguibeitia, supervised by U Irusta and E Aramendi. UPV-EHU, year 2023.

Machine learning and signal processing contributions to identify circulation states during out-of-hospital cardiac arrest

   Andoni Elola, supervised by E Aramendi and U Irusta. UPV-EHU, year 2021.

Signal processing and machine learning contributions to rhythm analysis during CPR.

   Iraia Isasi, supervised by U Irusta and E Aramendi. UPV-EHU, year 2020.

Nuevas técnicas de procesado para la predicción del éxito de la desfibrilación en la parada cardiorrespiratoria extrahospitalaria.

   Beatriz Chicote, supervised by U Irusta and E Aramendi. UPV-EHU, year 2019.

Thoracic impedance for cardiopulmonary resuscitation quality assessment and for circulation detection.

   Erik Alonso, supervised by J Ruiz and E Aramendi. UPV-EHU, year 2014.

New strategies to minimize hands-off intervals in cardiopulmonary resuscitation.

   Unai Ayala, supervised by U Irusta and J Ruiz. UPV-EHU, year 2014.

New Signal Processing Algorithms for Automated External Defibrillators.

   Unai Irusta, supervised by J Ruiz. UPV-EHU, year 2010.
 

Eliminación de la interferencia debida a la resucitación cardiopulmonar en el contexto de la desfibrilación cardíaca.

   Sofía Ruiz de Gauna, supervised by E Aramendi. UPV-EHU, year 2008.

Sistema Multicanal para la Completa Caracterización en Tiempo Real de la Calidad en el Suministro Eléctrico.

   Elisabete Aramendi, supervised by J Ruiz. UPV-EHU, year 1998.