BackBrowsing by Author "Eftestøl, Trygve"
Now showing items 1-5 of 5
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A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions
; ; ; ; ; Alonso, Erik
; ; (IEEE, 2019-06)
Goal: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally ... -
A Multistage Algorithm for ECG Rhythm Analysis During Piston-Driven Mechanical Chest Compressions
; ; ; ; Alonso, Erik; ; (IEEE, 2019-01)
Goal: An accurate rhythm analysis during cardiopulmonary resuscitation (CPR) would contribute to increase the survival from out-of-hospital cardiac arrest. Piston-driven mechanical compression devices are frequently used ... -
Automatic Cardiac Rhythm Classification with Concurrent Manual Chest Compressions
(IEEE, 2019-08-13)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
(Public Library Science, 2016-07-21)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 ... -
Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks
(MDPI, 2020-05-27)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 ...