Inicio  /  Applied Sciences  /  Vol: 10 Par: 23 (2020)  /  Artículo
ARTÍCULO
TITULO

Multi-Time-Scale Features for Accurate Respiratory Sound Classification

Alfonso Monaco    
Nicola Amoroso    
Loredana Bellantuono    
Ester Pantaleo    
Sabina Tangaro and Roberto Bellotti    

Resumen

The automated classification of respiratory sound has gained increasing attention in recent years and has been the subject of a growing number of international scientific challenges for the development of accurate classification algorithms to support clinical practice. The COVID-19 pandemic has highlighted an urgent need for such developments. In this work, an accurate algorithm for the classification of respiratory sounds?specifically, crackles, wheezes or a combination of them?is presented.

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