Logistic Regression-HSMM-based Heart Sound Segmentation

Description

The identification of the exact positions of the first and second heart sounds within a phonocardiogram (PCG), or heart sound segmentation, is an essential step in the automatic analysis of heart sound recordings, allowing for the classification of pathological events. While threshold-based segmentation methods have shown modest success, probabilistic models, such as hidden Markov models, have recently been shown to surpass the capabilities of previous methods. Segmentation performance is further improved when apriori information about the expected duration of the states is incorporated into the model, such as in a hidden semi-Markov model (HSMM). This code provides Matlab algorithms to perform HSMM-based heart sound segmentation.

Update Frequency

Not updated

License

GNU General Public License version 3

Documentation

https://doi.org/10.13026/vnt9-kf93

Managed By

PhysioNet

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Contact

https://physionet.org/about/#contact_us

How to Cite

Logistic Regression-HSMM-based Heart Sound Segmentation was accessed on DATE from https://registry.opendata.aws/hss.