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Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform
- Source :
- International Journal of Biological Sciences
- Publication Year :
- 2018
- Publisher :
- Ivyspring International Publisher, 2018.
-
Abstract
- Sputum sounds are biological signals used to evaluate the condition of sputum deposition in a respiratory system. To improve the efficiency of intensive care unit (ICU) staff and achieve timely clearance of secretion in patients with mechanical ventilation, we propose a method consisting of feature extraction of sputum sound signals using the wavelet transform and classification of sputum existence using artificial neural network (ANN). Sputum sound signals were decomposed into the frequency subbands using the wavelet transform. A set of features was extracted from the subbands to represent the distribution of wavelet coefficients. An ANN system, trained using the Back Propagation (BP) algorithm, was implemented to recognize the existence of sputum sounds. The maximum precision rate of automatic recognition in texture of signals was as high as 84.53%. This study can be referred to as the optimization of performance and design in the automatic technology for sputum detection using sputum sound signals.
- Subjects :
- 0301 basic medicine
Discrete wavelet transform
Artificial neural network
Computer science
Feature extraction
Respiratory System
Wavelet Analysis
Applied Microbiology and Biotechnology
03 medical and health sciences
Wavelet
fluids and secretions
Sputum sound analysis
medicine
Humans
Molecular Biology
Ecology, Evolution, Behavior and Systematics
medicine.diagnostic_test
business.industry
Sputum
Wavelet transform
Pattern recognition
Cell Biology
Auscultation
Backpropagation
respiratory tract diseases
030104 developmental biology
Respiratory system diagnosis
Artificial intelligence
Neural Networks, Computer
medicine.symptom
business
Algorithms
Developmental Biology
Research Paper
Subjects
Details
- Language :
- English
- ISSN :
- 14492288
- Volume :
- 14
- Issue :
- 8
- Database :
- OpenAIRE
- Journal :
- International Journal of Biological Sciences
- Accession number :
- edsair.doi.dedup.....26b26c357556b32abf39b2985a29763a