HLS-CMDS: Heart and Lung Sounds Dataset Recorded from a Clinical Manikin using Digital Stethoscope
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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.
本数据集包含535条心肺音录音，均通过数字听诊器（digital stethoscope）从临床模拟人体模型（clinical manikin）采集，涵盖单一心音、单一肺音及二者的混合录音；其中包含50条心音、50条肺音与145条混合音。每条混合音均同步配套采集了对应的源心音（145条）与源肺音（145条）。 数据集覆盖不同的胸部解剖听诊部位，包含正常与异常心音及肺音。每条录音均经过滤波处理以强化特定声音类型的特征，可用于人工智能（AI）在自动化心肺疾病检测、声音分类以及音频信号处理相关深度学习算法等领域的研究与应用。 若在研究中使用本数据集，请引用以下论文： Torabi, Y., Shirani, S., & Reilly, J. P. (2024), 采用数字听诊器采集的模拟人体心肺音数据集（Manikin-Recorded Cardiopulmonary Sounds Dataset Using Digital Stethoscope），arXiv预印本，https://doi.org/10.48550/arXiv.2410.03280 数据类型（Data Type）：音频文件（.wav）与逗号分隔值（Comma Separated Values，CSV）文件。 每个分类均配有对应的CSV元数据文件，用于标注对应音频文件的元信息。其中HS.csv、LS.csv及Mix.csv分别包含对应音频文件的元数据，包括文件名、受试者性别、心音与肺音类型以及录音采集的解剖部位。 声音类型（Sound Types）包括：正常心音、舒张晚期杂音、收缩中期杂音、收缩晚期杂音、心房颤动、第四心音、收缩早期杂音、第三心音、心动过速、房室传导阻滞；正常肺音、哮鸣音、细湿啰音、鼾音（Rhonchi）、胸膜摩擦音（Pleural Rub）及粗湿啰音。 听诊标记点（Auscultation Landmarks）包括：胸骨右缘上区（Right Upper Sternal Border）、胸骨左缘上区（Left Upper Sternal Border）、左胸骨下缘（Lower Left Sternal Border）、右肋缘（Right Costal Margin）、左肋缘（Left Costal Margin）、心尖区（Apex）、右上前区（Right Upper Anterior）、左上前区（Left Upper Anterior）、右中前区（Right Mid Anterior）、左中前区（Left Mid Anterior）、右下前区（Right Lower Anterior）及左下前区（Left Lower Anterior）。 应用场景（Applications）包括：基于AI的心肺疾病检测、无监督声音分离技术以及面向音频信号处理的深度学习研究。
