Finding Features for Real-Time Premature Ventricular Contraction Detection Using a Fuzzy Neural Network System

@article{Lim2009FindingFF,
  title={Finding Features for Real-Time Premature Ventricular Contraction Detection Using a Fuzzy Neural Network System},
  author={Joon S. Lim},
  journal={IEEE Transactions on Neural Networks},
  year={2009},
  volume={20},
  pages={522-527}
}
Fuzzy neural networks (FNNs) have been successfully applied to generate predictive rules for medical or diagnostic data. This brief presents an approach to detect premature ventricular contractions (PVCs) using the neural network with weighted fuzzy membership functions (NEWFMs). The NEWFM classifies normal and PVC beats by the trained bounded sum of weighted fuzzy membership functions (BSWFMs) using wavelet transformed coefficients from the MIT-BIH PVC database. The eight generalized… CONTINUE READING
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