An open access database for the evaluation of respiratory sound classification algorithms.
Bruno M Rocha1,2, Dimitris Filos3, Luís Mendes1,4
1Department of Informatics Engineering, Centre for Informatics and Systems (CISUC), University of Coimbra, Coimbra, Portugal.
Physiological Measurement
|February 2, 2019
Summary
A new public respiratory sound database aids algorithm development. This resource, with over 900 recordings and detailed annotations, supports research in respiratory sound classification.
Area of Science:
- Biomedical Engineering
- Medical Informatics
- Pulmonology
Background:
- Automatic analysis of respiratory sounds is crucial but lacks standardized evaluation datasets.
- Development of new algorithms is hindered by the absence of large, publicly available databases.
Purpose of the Study:
- To introduce a publicly accessible respiratory sound database for algorithm evaluation.
- To facilitate research and development in respiratory sound classification.
Main Methods:
- Compiled a database of 920 respiratory sound recordings from 126 participants.
- Provided two sets of annotations: 6,898 respiratory cycles and 10,775 specific adventitious sound events (crackles, wheezes).
Main Results:
- The best performing system in the associated challenge achieved 52.5% accuracy with respiratory cycle annotations.
- The best system achieved 91.2% accuracy with specific adventitious sound event annotations.
Conclusions:
- The release of this comprehensive respiratory sound database will significantly benefit the research community.
- This resource is expected to advance the field of respiratory sound classification and analysis.
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