Multimedia Respiratory Database (RespiratoryDatabase@TR): Auscultation Sounds and Chest X-rays
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Abstract (arXiv)
Auscultation is a method for diagnosis of especially internal medicine diseases such as cardiac, pulmonary and cardio-pulmonary by listening the internal sounds from the body parts. It is the simplest and the most common physical examination in the assessment processes of the clinical skills. In this study, the lung and heart sounds are recorded synchronously from left and right sides of posterior and anterior chest wall and back using two digital stethoscopes in Antakya State Hospital. The chest X-rays and the pulmonary function test variables and spirometric curves, the St. George respiratory questionnaire (SGRQ-C) are collected as multimedia and clinical functional analysis variables of the patients. The 4 channels of heart sounds are focused on aortic, pulmonary, tricuspid and mitral areas. The 12 channels of lung sounds are focused on upper lung, middle lung, lower lung and costophrenic angle areas of posterior and anterior sides of the chest. The recordings are validated and labelled by two pulmonologists evaluating the collected chest x-ray, PFT and auscultation sounds of the subjects. The database consists of 30 healthy subjects and 45 subjects with pulmonary diseases such as asthma, chronic obstructive pulmonary disease, bronchitis. The novelties of the database are the combination ability between auscultation sound results, chest X-ray and PFT; synchronously assessment capability of the lungs sounds; image processing based computerized analysis of the respiratory using chest X-ray and providing opportunity for improving analysis of both lung sounds and heart sounds on pulmonary and cardiac diseases.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 0 of its 20 references that are in the map. First posted on arXiv 21 Jan 2021.
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 2.
5 papers.
- 2024Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarkingcited by 23
- 2025Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learningcited by 5
- 2022Fused Audio Instance and Representation for Respiratory Disease Detectioncited by 0
- 2026RA-QA: A Benchmarking System for Respiratory Audio Question Answering Under Real-World Heterogeneitycited by 0
- 2026RAMoEA-QA: Hierarchical Specialization for Robust Respiratory Audio Question Answeringcited by 0
- 2026RAMoEA-QA: Hierarchical Specialization for Robust Respiratory Audio Question Answering6 Mar 2026
- 2026RA-QA: A Benchmarking System for Respiratory Audio Question Answering Under Real-World Heterogeneity4 Feb 2026
- 2025Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning27 Feb 2025
- 2024Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking23 Jun 2024
- 2022Fused Audio Instance and Representation for Respiratory Disease Detection22 Apr 2022