Ventricular Fibrillation and Tachycardia Classification Using a Machine Learning Approach

@article{Li2014VentricularFA,
  title={Ventricular Fibrillation and Tachycardia Classification Using a Machine Learning Approach},
  author={Qiao Li and Cadathur Rajagopalan and Gari D. Clifford},
  journal={IEEE Transactions on Biomedical Engineering},
  year={2014},
  volume={61},
  pages={1607-1613}
}
Correct detection and classification of ventricular fibrillation (VF) and rapid ventricular tachycardia (VT) is of pivotal importance for an automatic external defibrillator and patient monitoring. In this paper, a VF/VT classification algorithm using a machine learning method, a support vector machine, is proposed. A total of 14 metrics were extracted from a specific window length of the electrocardiogram (ECG). A genetic algorithm was then used to select the optimal variable combinations… CONTINUE READING

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