A novel technique for validating diagnosed respiratory noises in infants and children
The goal of this paper is to develop a novel technique to validate diagnosed respiratory noises in infants and children with high accuracy and reduced time consumption. A large number of recorded lung sounds are acquired with varied cases of normal and abnormal respiratory sounds. Wavelet-based Dyna...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2018-12-01
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| Series: | Alexandria Engineering Journal |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016818301005 |
| Summary: | The goal of this paper is to develop a novel technique to validate diagnosed respiratory noises in infants and children with high accuracy and reduced time consumption. A large number of recorded lung sounds are acquired with varied cases of normal and abnormal respiratory sounds. Wavelet-based Dynamic Time Warping technique is utilized in the proposed approach and the recognition accuracy was found to be above 88% in average. All the sounds represent infants and children below 13 years old and collected from AUCH-Alexandria, Egypt. Keywords: Dynamic time warping, Discrete wavelet transform, Respiratory noises |
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| ISSN: | 1110-0168 |