“Advanced life support therapy and on out-of-hospital cardiac arrest patients: Applying signal processing and pattern recognition methods”

Authors: Trygve Eftestøl, Martin Risdal, Joar Eilevstjønn and Petter A. Steen,
Affiliation: University of Stavanger, Laerdal Medical and Ullevål University Hospital
Reference: 2005, Vol 26, No 4, pp. 221-235.

Keywords: Cardiac arrest, ventricular fibrillation, cardiopulmonary resuscitation, ECG analysis, decision support, defibrillation, CPR artefact removal

Abstract: In the US alone, several hundred thousands die of sudden cardiac arrests each year. Basic life support defined as chest compressions and ventilations and early defibrillation are the only factors proven to increase the survival of patients with out-of-hospital cardiac arrest, and are key elements in the chain of survival defined by the American Heart Association. The current cardiopulmonary resuscitation guidelines treat all patients the same, but studies show need for more individualiza- tion of treatment. This review will focus on ideas on how to strengthen the weak parts of the chain of survival including the ability to measure the effects of therapy, improve time efficiency, and optimize the sequence and quality of the various components of cardiopulmonary resuscitation.

PDF PDF (2364 Kb)        DOI: 10.4173/mic.2005.4.3

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  title={{Advanced life support therapy and on out-of-hospital cardiac arrest patients: Applying signal processing and pattern recognition methods}},
  author={Eftestøl, Trygve and Risdal, Martin and Eilevstjønn, Joar and Steen, Petter A.},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}