ArticleInternational journal of biological sciences2019
A Lung Sound Category Recognition Method Based on Wavelet Decomposition and BP Neural Network.
Article in International journal of biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Respiratory sound analysis for ICU clinical decision support: deep learning-based classification of normal and abnormal sounds using real ICU data.BMC medical informatics and decision making · 2026Article
- Optimization of ultrasonic extraction and kinetic modeling of jieduquyuziyin prescription polysaccharides via explainable machine learning.Ultrasonics sonochemistry · 2025Article
- A Multimodal AI Framework for Automated Multiclass Lung Disease Diagnosis from Respiratory Sounds with Simulated Biomarker Fusion and Personalized Medication Recommendation.International journal of molecular sciences · 2025Article
- High-accuracy lung sound classification for healthy versus unhealthy diagnosis using artificial neural network.Frontiers in bioengineering and biotechnology · 2025Article
- Review
- Acoustic-Based Deep Learning Architectures for Lung Disease Diagnosis: A Comprehensive Overview.Diagnostics (Basel, Switzerland) · 2023Review
- A review on lung disease recognition by acoustic signal analysis with deep learning networks.Journal of big data · 2023Article
- Sputum deposition classification for mechanically ventilated patients using LSTM method based on airflow signals.Heliyon · 2022Article
- Prediction of Mumps Incidence Trend in China Based on Difference Grey Model and Artificial Neural Network Learning.Iranian journal of public health · 2021Article
- Back Propagation Neural Network-Based Ultrasound Image for Diagnosis of Cartilage Lesions in Knee Osteoarthritis.Journal of healthcare engineering · 2021Article
- An Automated System for Classification of Chronic Obstructive Pulmonary Disease and Pneumonia Patients Using Lung Sound Analysis.Sensors (Basel, Switzerland) · 2020Article
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Authors and funding
4 authors.
Funding
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Abstract
In this paper, a method of characteristic extraction and recognition on lung sounds is given. Wavelet de-noised method is adopted to reduce noise of collected lung sounds and extract wavelet characteristic coefficients of the de-noised lung sounds by wavelet decomposition. Considering the problem that lung sounds characteristic vectors are of high dimensions after wavelet decomposition and reconstruction, a new method is proposed to transform the characteristic vectors from reconstructed signals into reconstructed signal energy. In addition, we use linear discriminant analysis (LDA) to reduce the dimension of characteristic vectors for comparison in order to obtain a more efficient way for recognition. Finally, we use BP neural network to carry out lung sounds recognition where comparatively high-dimensional characteristic vectors and low- dimensional vectors are set as input and lung sounds categories as output with a recognition accuracy of 82.5% and 92.5%.
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