HLS-CMDS: Heart and Lung Sounds Dataset Recorded from a Clinical Manikin using Digital Stethoscope

This dataset contains 535 recordings of heart and lung sounds captured using a digital stethoscope from a clinical manikin, including both individual and mixed recordings of heart and lung sounds; It includes 50 heart sounds, 50 lung sounds, and 145 mixed sounds. For each mixed sound, the corresponding source heart sound (145 recordings) and source lung sound (145 recordings) were also recorded. It includes recordings from different anatomical chest locations, with normal and abnormal sounds. Each recording has been filtered to highlight specific sound types, making it valuable for artificial intelligence (AI) research and applications in automated cardiopulmonary disease detection, sound classification, and deep learning algorithms related to audio signal processing. If you use this dataset in your research, please cite the following paper:

Torabi, Y., Shirani, S., & Reilly, J. P. (2024), Manikin-Recorded Cardiopulmonary Sounds Dataset Using Digital Stethoscope, arXiv preprint, https://doi.org/10.48550/arXiv.2410.03280

Data Type: Audio files (.wav), Comma Separated Values (.CSV)

Each category is accompanied by a corresponding CSV file that provides metadata for the respective audio files. The CSV files (HS.csv, LS.csv, and Mix.csv) contain metadata about the corresponding audio files, including the file name, gender, heart and lung sound type, and the anatomical location where we recorded the sound.

Sound Types: Normal Heart, Late Diastolic Murmur, Mid Systolic Murmur, Late Systolic Murmur, Atrial Fibrillation, Fourth Heart Sound, Early Systolic Murmur, Third Heart Sound, Tachycardia, Atrioventricular Block, Normal Lung, Wheezing, Fine Crackles, Rhonchi, Pleural Rub, and Coarse Crackles.

Auscultation Landmarks: Right Upper Sternal Border, Left Upper Sternal Border, Lower Left Sternal Border, Right Costal Margin, Left Costal Margin, Apex, Right Upper Anterior, Left Upper Anterior, Right Mid Anterior, Left Mid Anterior, Right Lower Anterior, and Left Lower Anterior.

Applications: AI-based cardiopulmonary disease detection, unsupervised sound separation techniques, and deep learning for audio signal processing.