Datasets
Standard Dataset
Cardiopulmonary Sounds Database
- Citation Author(s):
- Submitted by:
- Julio Valdez
- Last updated:
- Thu, 02/16/2023 - 08:59
- DOI:
- 10.21227/8jzz-3x76
- Data Format:
- Research Article Link:
- License:
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Abstract
This data set contains information on cardiopulmonary signals that were recorded simultaneously. The signals are separated into two folders, one titled heart sounds and the other lung sounds. In addition, two matlab programs are included, one with which the signals can be recorded and another to make graphs in time and frequency. It also has a pdf file that details the nomenclature of the signals.
This data set can be useful for various signal processing algorithms: filtering, PCA, LDA, ICA, CNN, etc.
Instructions:
In the Database file you will find all the relevant information about how the signals were obtained.
Dataset Files
- Cardiopulmonary Sounds Database.zip (13.10 MB)
- Scrips Cardiopulmonary Sounds Database.zip (3.19 kB)
Documentation
| Attachment | Size |
|---|---|
 Database.pdf | 247.13 KB |
Comments
To work on deep learning models to predict heart disease from the recorded sounds
Dear author,
I would like to perform some machine learning techniques to analysis the signals in this database.
I would like to use your data to evaluate my model.
Sincerely,
F. O. Djibrillah
Dear F. O. Djibrillah,
We are delighted that you use our database for your research, I would only ask you to cite us in your work in case you publish it.
It would also be useful to predict lung diseases, since they are sounds of the lung and heart recorded simultaneously.
It would also be useful to predict lung diseases, since they are sounds of the lung and heart recorded simultaneously.
I want to work on the respiratory sounds dataset for analyzing the sounds from the various organs of the body. Could you please provide me the dataset, that would be much appreciated. My email: anupam20555@iiitd.ac.in
Thanks
Anupam
Dear Julio Valdez,
Could you share the dataset for experimentation with foundation models? We pretend to evaluate your dataset comparing multiple AI models.
Thank you,