Clasificación de los sonidos cardíacos usando ondículas y redes neuronales
Keywords:
Phonocardiogram, heart, PCG, PhysioNetAbstract
The auscultation of cardiac sounds is a clinical examination that allows to determine if a patient should be referred to a specialist. The phonocardiogram (PCG) corresponds to the recording of these sounds. The objective of this work is the evaluation of the combination of two of the proposed algorithms during PhysioNet 2016 challenge, the first is based on wavelets and the second on a neural convolutional network to evaluate the performance in the classification of cardiac sounds (normal/abnormal). The results show a better balance between specificity and sensitivity with respect to the wavelet method, although its performance is inferior to the method based on neural networks. The proposed method has a lower computational cost.
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Goda, M. Á., Hajas, P. (2016). Morphological determination of pathological PCG signals by time and frequency domain analysis. Computing in Cardiology Conference (CinC), 1133-1136. https://doi.org/10.23919/CIC.2016.7868947
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