ECG-based pulse detection during cardiac arrest using random forest classifier

Medical & Biological Engineering & Computing
Andoni ElolaMohamud R Daya

Abstract

Sudden cardiac arrest is one of the leading causes of death in the industrialized world. Pulse detection is essential for the recognition of the arrest and the recognition of return of spontaneous circulation during therapy, and it is therefore crucial for the survival of the patient. This paper introduces the first method based exclusively on the ECG for the automatic detection of pulse during cardiopulmonary resuscitation. Random forest classifier is used to efficiently combine up to nine features from the time, frequency, slope, and regularity analysis of the ECG. Data from 191 cardiac arrest patients was used, and 1177 ECG segments were processed, 796 with pulse and 381 without pulse. A leave-one-patient out cross validation approach was used to train and test the algorithm. The statistical distributions of sensitivity (SE) and specificity (SP) for pulse detection were estimated using 500 patient-wise bootstrap partitions. The mean (std) SE/SP for nine-feature classifier was 88.4 (1.8) %/89.7 (1.4) %, respectively. The designed algorithm only requires 4-s-long ECG segments and could be integrated in any commercial automated external defibrillator. The method permits to detect the presence of pulse accurately, minimizing int...Continue Reading

References

Dec 1, 1986·IEEE Transactions on Bio-medical Engineering·P S Hamilton, W J Tompkins
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Sep 29, 2000·Resuscitation·J Nyman, M Sihvonen
Nov 13, 2004·Physiological Measurement·Irena Jekova, Vessela Krasteva
Feb 1, 2008·IEEE Transactions on Bio-medical Engineering·Martin RisdalTrygve Eftestøl
Jan 19, 2012·Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society·César O NavarroJohn McC Anderson
Jun 26, 2013·Resuscitation·Charles F Babbs
Oct 20, 2015·Resuscitation·Jasmeet SoarUNKNOWN Adult advanced life support section Collaborators
Feb 20, 2016·Resuscitation·Ali Bahrami RadTrygve Eftestøl
Apr 4, 2017·IEEE Transactions on Bio-medical Engineering·Ali Bahrami RadAggelos K Katsaggelos

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feature extraction

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